CN110674430B

CN110674430B - Medical image processing method, device, terminal and storage medium based on browser

Info

Publication number: CN110674430B
Application number: CN201910792035.6A
Authority: CN
Inventors: 彭胜聪
Original assignee: Ping'an Haoyi Investment Management Co ltd
Current assignee: Ping'an Haoyi Investment Management Co ltd
Priority date: 2019-08-26
Filing date: 2019-08-26
Publication date: 2023-11-14
Anticipated expiration: 2039-08-26
Also published as: CN110674430A

Abstract

The invention provides a medical image processing method based on a browser, which comprises the following steps: acquiring an original medical image; obtaining a first image and a second image according to pixel values in the original medical image; determining a first pixel value and a second pixel value in the first image and a third pixel value and a fourth pixel value in the second image; geometrically transforming the first image and the second image; calculating to obtain a target pixel value according to the first, second, third and fourth geometrically transformed pixel values; the target pixel values are processed and displayed in accordance with a digital imaging and communications protocol of medicine. The invention also provides a medical image processing device, a terminal and a storage medium based on the browser. According to the invention, the original medical image can be displayed at the browser end, the server is not required to assist in processing and participating in operation, and the pixel value in the original medical image is read through the WebGL technology supported by the browser, so that the calculation speed is greatly improved, the response time is shortened, and the method is beneficial to use in a high concurrency scene.

Description

Medical image processing method, device, terminal and storage medium based on browser

Technical Field

The invention relates to the technical field of medical image data processing, in particular to a medical image processing method, device, terminal and storage medium based on a browser.

Background

With the development of medical imaging technology and computer technology, imaging technologies and equipment such as X-ray imaging, computed Tomography (CT), magnetic resonance imaging (MR), ultrasound imaging (US), and Positron Emission Tomography (PET) play a significant role in clinical and research and development work in medical institutions. Medical image data generated by these medical imaging devices is typically stored in a storage system such as an image archiving and communication system (Picture archiving and communication system, PACS). When a user needs, the user can request inquiry and retrieval from a server of the storage system, and the three-dimensional medical image is displayed on the WEB after being visually rendered through the server.

Because medical images, particularly three-dimensional medical images, have large data volumes, the visual rendering of the medical images requires a high-performance display card and occupies a large amount of display memory, and therefore the medical images are difficult to review on a common office computer, a tablet computer or a smart phone, which is unfavorable for use in high-concurrency scenes.

Therefore, how to display the medical image on the browser of the terminal is a technical problem to be solved.

Disclosure of Invention

In view of the above, it is necessary to provide a medical image processing method, device, terminal and storage medium based on a browser, which can display an original medical image at the browser end without server auxiliary processing and participation in operation, and read pixel values in the original medical image through WebGL technology supported by the browser, so as to greatly improve the calculation speed, shorten the response time, and be beneficial to use in high concurrency scenes.

A first aspect of the present invention provides a browser-based medical image processing method, the method comprising:

acquiring an original medical image;

obtaining a first image and a second image according to pixel values in the original medical image;

determining a first pixel value of a red channel and a second pixel value of a green channel in the first image according to a preset first segmentation algorithm;

determining a third pixel value of a red channel and a fourth pixel value of a green channel in the second image according to a preset second segmentation algorithm;

geometrically transforming the first image and the second image;

Extracting a first pixel value and a second pixel value after geometric transformation, and a third pixel value and a fourth pixel value after geometric transformation;

calculating to obtain a target pixel value according to the geometrically transformed first pixel value, second pixel value, third pixel value and fourth pixel value;

the target pixel values are processed and displayed in accordance with a digital imaging and communications protocol of medicine.

Preferably, the first image and the second image are obtained according to pixel values in the original medical image:

scanning original pixel values in the original medical image;

determining a positive number of the original pixel values as pixel values at corresponding positions in the first image, and determining pixel values at the rest positions in the first image as 0;

negative ones of the original pixel values are determined as pixel values at corresponding locations in the second image, and pixel values at remaining locations in the second image are determined as 0.

Preferably, the determining the first pixel value of the red channel and the second pixel value of the green channel in the first image according to a preset first segmentation algorithm includes:

judging whether the pixel value in the first image is smaller than a preset pixel threshold value or not;

When the pixel value in the first image is smaller than the preset pixel threshold value, determining that a first pixel value at a corresponding position of a red channel in the first image is 0, and determining that a second pixel value at a corresponding position of a green channel in the first image is the pixel value in the first image;

when the pixel value in the first image is greater than or equal to the preset pixel threshold value, determining a first tangential value and a first residual value according to the maximum pixel value in the original medical image; determining a first pixel value at a corresponding position of a red channel in the first image as the first cut value, and determining a second pixel value at a corresponding position of a green channel in the first image as the first remainder value.

Preferably, the determining the third pixel value of the red channel and the fourth pixel value of the green channel in the second image according to the preset second segmentation algorithm includes:

judging whether the absolute value of the pixel value in the second image is smaller than a preset pixel threshold value or not;

when the absolute value of the pixel value in the second image is smaller than the preset pixel threshold value, determining that the third pixel value at the corresponding position of the red channel in the second image is 0, and determining that the fourth pixel value at the corresponding position of the green channel in the second image is the pixel value in the absolute value of the pixel value in the second image;

When the absolute value of the pixel value in the second image is larger than or equal to the preset pixel threshold value, determining a second segmentation value and a second residual value according to the minimum pixel value in the original medical image; and determining a third pixel value at a corresponding position of a red channel in the second image as the second segmentation value, and determining a second pixel value at a corresponding position of a green channel in the second image as the second residual value.

Preferably, the determining the first score and the first residual value according to the maximum pixel value in the original medical image includes: dividing the maximum pixel value by the preset pixel threshold value, and then rounding downwards to obtain a first sub-value; dividing the pixel value in the first image by the first sub-value, then rounding downwards to obtain a first tangential value, dividing the pixel value in the first image by the first sub-value, and then taking the remainder to obtain a first residual value.

Preferably, the determining the second score value and the second residual value according to the minimum pixel value in the original medical image includes: dividing the minimum pixel value by the preset pixel threshold value, then rounding downwards and taking an absolute value to obtain a second sub-value; dividing the absolute value of the pixel value in the second image by the second sub-value, then rounding downwards to obtain a second dividing value, dividing the absolute value of the pixel value in the second image by the second sub-value, and then taking the remainder to obtain a second remainder.

Preferably, the calculating the target pixel value according to the geometrically transformed first pixel value, second pixel value, third pixel value and fourth pixel value includes:

the first pixel value after the geometric transformation and the first sub-value are subjected to product to obtain a new first pixel value;

the third pixel value after the geometric transformation and the second sub-value are subjected to product to obtain a new third pixel value;

and calculating to obtain a target pixel value according to the new first pixel value, the geometrically transformed second pixel value, the new third pixel value and the geometrically transformed fourth pixel value.

Preferably, the target pixel value is calculated by the following formula:

X0＝X1+X2-X3-X4；

wherein X0 represents the target pixel value, X1 represents the new first pixel value, X2 represents the geometrically transformed second pixel value, X3 represents the new third pixel value, and X4 represents the geometrically transformed fourth pixel value.

A second aspect of the present invention provides a browser-based medical image processing apparatus, the apparatus comprising:

the acquisition module is used for acquiring the original medical image;

the first determining module is used for obtaining a first image and a second image according to the pixel values in the original medical image;

The second determining module is used for determining a first pixel value of a red channel and a second pixel value of a green channel in the first image according to a preset first dividing algorithm;

a third determining module, configured to determine a third pixel value of a red channel and a fourth pixel value of a green channel in the second image according to a preset second segmentation algorithm;

the geometric transformation module is used for carrying out geometric transformation on the first image and the second image;

the extraction module is used for extracting the first pixel value and the second pixel value after geometric transformation, and the third pixel value and the fourth pixel value after geometric transformation;

the calculation module is used for calculating a target pixel value according to the geometrically transformed first pixel value, the geometrically transformed second pixel value, the geometrically transformed third pixel value and the geometrically transformed fourth pixel value;

and the display module is used for processing and displaying the target pixel value according to the medical digital imaging and communication protocol.

A third aspect of the present invention provides a terminal comprising a processor for implementing the browser-based medical image processing method when executing a computer program stored in a memory.

A fourth aspect of the present invention provides a computer-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the browser-based medical image processing method.

In summary, according to the browser-based medical image processing method, the browser-based medical image processing device, the browser-based medical image processing terminal and the browser-based medical image processing storage medium, the acquired original medical image is processed to obtain the first image and the second image; determining a first pixel value of a red channel and a second pixel value of a green channel in the first image according to a preset first segmentation algorithm; determining a third pixel value of a red channel and a fourth pixel value of a green channel in the second image according to a preset second segmentation algorithm; performing geometric transformation on the first image and the second image, and extracting a first pixel value and a second pixel value after geometric transformation, and a third pixel value and a fourth pixel value after geometric transformation; finally, calculating to obtain a target pixel value according to the geometrically transformed first pixel value, second pixel value, third pixel value and fourth pixel value; the target pixel values are processed and displayed in accordance with a digital imaging and communications protocol of medicine. According to the technical scheme provided by the invention, a background server is not needed to assist in processing when the original medical image is called up, a server is not needed to participate in operation, the medical image can be directly displayed at a browser end, and the pixel value in the original medical image is read through the WebGL technology supported by the browser, so that the calculation speed is greatly improved, the response time is shortened, and the method is beneficial to use in a high-concurrency scene.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are required to be used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are only embodiments of the present invention, and that other drawings can be obtained according to the provided drawings without inventive effort for a person skilled in the art.

Fig. 1 is a flowchart of a browser-based medical image processing method according to an embodiment of the present invention.

Fig. 2 is a block diagram of a medical image processing device based on a browser according to a second embodiment of the present invention.

Fig. 3 is a schematic structural diagram of a terminal according to a third embodiment of the present invention.

The invention will be further described in the following detailed description in conjunction with the above-described figures.

Detailed Description

In order that the above-recited objects, features and advantages of the present invention will be more clearly understood, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings. It should be noted that, without conflict, the embodiments of the present invention and features in the embodiments may be combined with each other.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, and the described embodiments are merely some, rather than all, embodiments of the present invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention.

Example 1

In this embodiment, the browser-based medical image processing method may be applied to a terminal, and for a terminal that needs to perform browser-based medical image processing, the browser-based medical image processing function provided by the method of the present invention may be directly integrated on the terminal, or may be run in the terminal in the form of a software development kit (Software Development Kit, SKD).

As shown in fig. 1, the method for processing medical images based on a browser aims to complete geometric transformation and display of medical images at a browser end without auxiliary processing and calculation participation of a server, and specifically includes the following steps, according to different requirements, the sequence of steps in the flowchart may be changed, and some may be omitted.

S11, acquiring an original medical image.

In this embodiment, the original medical image is generally stored in the server, because the terminal configuration is low, and the data used is downsampled, lossy compressed data, and the original medical image in the server is uncompressed data. The raw medical image may include, but is not limited to: radiography, CT imaging, MR imaging, ultrasound imaging and PET imaging.

It should be noted that, since the pixel value of the original medical image is not the 2D image as commonly seen, the pixel value of the original medical image may be positive or negative, and the number of the pixel values is greater than 256. Therefore, to complete the display of the original medical image at the terminal, the pixel values of the original medical image need to be processed so as to be displayed like a two-dimensional image on a normal terminal.

The terminal in this embodiment may support 3D drawing protocol (Web Graphics Library, webGL) technology, which is a browser-supported technology, allowing JavaScript and OpenGL ES 2.0 to be combined together, and by adding one JavaScript binding of OpenGL ES 2.0, webGL may provide hardware 3D accelerated rendering for HTML5 Canvas, creating complex navigation and data visualization.

S12, obtaining a first image and a second image according to the pixel values in the original medical image.

In this embodiment, after the original medical image is obtained from the background server, the texture2D function of the GLSL is used to obtain the pixel values in the original medical image. The GLSL is a loader programming language for WebGL programming.

Compared with the traditional Web programming method, the method has the advantages that the calculation speed can be greatly improved and the response time can be shortened by adopting WebGL to acquire the original medical image and the pixel values in the original medical image.

scanning original pixel values in the original medical image;

In this embodiment, each original pixel value in the original medical image may be scanned, and a positive number pixel value (i.e., a pixel value greater than 0) and a negative number pixel value (i.e., a pixel value less than 0) in the original medical image may be obtained, where the positive number pixel value is classified as a class to form a first image, and the negative number pixel value is classified as a class to form a second image.

Because the number of the positive number pixel values and the number of the negative number pixel values are smaller than the number of the pixel values in the original medical image, the positive number pixel values can be directly filled in the position, corresponding to the positive number pixel values in the original medical image, in the first image, and the pixel values in other positions in the first image are filled with 0; the position of the second image corresponding to the negative number pixel value in the original medical image can be directly filled with the negative number pixel value, and the pixel values of other positions in the second image are filled with 0, so that the sizes of the obtained first image and second image are the same as the size of the original medical image. And the pixel value in the first image thus obtained is greater than or equal to 0, and the pixel value in the second image thus obtained is less than or equal to 0.

S13, determining a first pixel value of a red channel and a second pixel value of a green channel in the first image according to a preset first segmentation algorithm.

In this embodiment, after the first image is obtained according to the original pixel value of the original medical image, the first pixel value of the red channel and the second pixel value of the green channel in the first image are further determined, so as to provide a basis for performing the geometric transformation of the pixel values.

In this embodiment, the pixel threshold may be preset according to the number of pixel levels that can be displayed by the terminal, for example, the number of pixel levels of the terminal in the related art is 256 (the number of pixels displayed is 0 to 255), and then the preset pixel threshold may be set to 256, which is taken as a dividing line.

In this embodiment, when the pixel value X1 of a certain pixel in the first image is smaller than the preset pixel threshold, it is determined that the first pixel value at the corresponding position of the red channel in the first image is 0, and the second pixel value at the corresponding position of the green channel is the pixel value X1 in the first image.

In this embodiment, when a pixel value X1 of a certain pixel in the first image is greater than or equal to a preset pixel threshold, a first cut-out value and a first residual value are first determined according to a maximum pixel value in the original medical image, then a first pixel value at a corresponding position of a red channel in the first image is determined according to the first cut-out value, and a second pixel value at a corresponding position of a green channel in the first image is determined according to the first residual value.

Specifically, the determining the first score and the first residual value according to the maximum pixel value in the original medical image includes:

dividing the maximum pixel value by the preset pixel threshold value, and then rounding downwards to obtain a first sub-value;

dividing the pixel value in the first image by the first sub-value, then rounding downwards to obtain a first tangential value, dividing the pixel value in the first image by the first sub-value, and then taking the remainder to obtain a first residual value.

For example, assuming that the maximum pixel value Y1 in the original medical image is divided by the preset pixel threshold, then rounding down to obtain a first sub-value spilth=math.floor (Y1/preset pixel threshold) +1, dividing the pixel value X1 in the first image by the first sub-value, rounding down to obtain a first score value=math.floor (X1/spiltH), dividing the pixel value X1 in the first image by the first sub-value, and then taking the remainder to obtain a first residual value=x1% spiltH.

Math.floor (X) returns the largest integer less than parameter X, i.e., the floating point number is rounded down, e.g., math.floor (-8.5) gives a result of-9 and Math.floor (8.5) gives a result of 8.

S14, determining a third pixel value of a red channel and a fourth pixel value of a green channel in the second image according to a preset second segmentation algorithm.

In this embodiment, after the second image is obtained according to the original pixel value of the original medical image, the third pixel value of the red channel and the fourth pixel value of the green channel in the second image are further determined, so as to provide a basis for performing the geometric transformation of the pixel values.

In this embodiment, when the absolute value of the pixel value X2 of a certain pixel in the second image is smaller than the preset pixel threshold, it is determined that the third pixel value at the corresponding position of the red channel in the second image is 0, and the fourth pixel value at the corresponding position of the green channel in the second image is the absolute value of the pixel value X2 in the absolute value of the pixel value in the second image.

In this embodiment, when the absolute value of the pixel value X2 of a certain pixel in the second image is greater than or equal to the preset pixel threshold, a second segmentation value and a second residual value are first determined according to the minimum pixel value in the original medical image, then a third pixel value at the corresponding position of the red channel in the second image is determined according to the second segmentation value, and a second pixel value at the corresponding position of the green channel in the second image is determined according to the second residual value.

Specifically, the determining the second score value and the second residual value according to the minimum pixel value in the original medical image includes:

dividing the minimum pixel value by the preset pixel threshold value, then rounding downwards and taking an absolute value to obtain a second sub-value;

dividing the absolute value of the pixel value in the second image by the second sub-value, then rounding downwards to obtain a second dividing value, dividing the absolute value of the pixel value in the second image by the second sub-value, and then taking the remainder to obtain a second remainder.

For example, assuming that the minimum pixel value Y2 in the original medical image is divided by the preset pixel threshold, the minimum pixel value is rounded down and then taken as an absolute value to obtain a second sub-value spilt=math.abs (math.floor (Y2/preset pixel threshold) +1), the absolute value of the pixel value in the second image is divided by the second sub-value and then rounded down to obtain a second cut value=math.floor (X2/spilt), and the absolute value of the pixel value in the second image is divided by the second sub-value and then taken as a residual to obtain a second residual value=jdata% spilt.

By taking the absolute value of each pixel value in the second image, the pixel values in the red channel and the green channel corresponding to the second image can be changed into positive numbers, so that the pixel level of the pixel value of the common two-dimensional image can be obtained.

S15, performing geometric transformation on the first image and the second image.

In this embodiment, geometric transformations are performed on the R channel and the G channel corresponding to the first image and the second image, where the geometric transformations may be scaling, translation, rotation, and flipping. The present invention is not described in detail herein with respect to geometrical variations, which are prior art.

S16, extracting the first pixel value and the second pixel value after geometric transformation, and the third pixel value and the fourth pixel value after geometric transformation.

In this embodiment, after the geometric change, the pixel values of the red channel and the green channel in the first image after the geometric change and the pixel values of the red channel and the green channel in the second image after the geometric change are obtained again. That is, the first pixel value and the second pixel value in the geometrically transformed first image, and the third pixel value and the fourth pixel value in the geometrically transformed second image are extracted again.

S17, calculating to obtain a target pixel value according to the geometrically transformed first pixel value, second pixel value, third pixel value and fourth pixel value.

In this embodiment, the target pixel value may be calculated according to the geometrically transformed first pixel value, second pixel value, third pixel value, and fourth pixel value.

The target pixel value is calculated by the following formula:

X0＝X1+X2-X3-X4；

For example, assuming that a first pixel value in a first geometrically transformed image is denoted by R1, a second pixel value in the first geometrically transformed image is denoted by G1, a third pixel value in the second geometrically transformed image is denoted by R2, and a fourth pixel value in the second geometrically transformed image is denoted by R2, then a new first pixel value=r1×spilth, a new third pixel value=r2×spiltl, and the target pixel value=new first pixel value+second geometrically transformed pixel value-new third pixel value-fourth geometrically transformed pixel value=r1×spilth+g1—r2×spiltl-R2.

And S18, processing and displaying the target pixel value according to the medical digital imaging and communication protocol.

In this embodiment, digital imaging and communications in medicine (Digital Imaging and Communications in Medicine, DICOM) is an international standard for medical images and related information (ISO 12052), defining a medical image format of quality that can be used for data exchange that meets clinical needs. The image formed by the new pixel values is similar to a common two-dimensional image, and can be displayed on a browser of a terminal after format conversion according to the DICOM protocol.

In summary, according to the browser-based medical image processing method disclosed by the invention, the acquired original medical image is processed to obtain the first image and the second image; determining a first pixel value of a red channel and a second pixel value of a green channel in the first image according to a preset first segmentation algorithm; determining a third pixel value of a red channel and a fourth pixel value of a green channel in the second image according to a preset second segmentation algorithm; performing geometric transformation on the first image and the second image, and extracting a first pixel value and a second pixel value after geometric transformation, and a third pixel value and a fourth pixel value after geometric transformation; finally, calculating to obtain a target pixel value according to the geometrically transformed first pixel value, second pixel value, third pixel value and fourth pixel value; the target pixel values are processed and displayed in accordance with a digital imaging and communications protocol of medicine. According to the technical scheme provided by the invention, a background server is not needed to assist in processing when the original medical image is called up, a server is not needed to participate in operation, the medical image can be directly displayed at a browser end, and the pixel value in the original medical image is read through the WebGL technology supported by the browser, so that the calculation speed is greatly improved, the response time is shortened, and the method is beneficial to use in a high-concurrency scene.

And secondly, the new image obtained after the original medical image is processed by the technical scheme provided by the invention accords with the format of the medical image, and the medical image can be read on a common browser without changing browser equipment, so that the equipment cost is saved.

Example two

In some embodiments, the browser-based medical image processing apparatus 20 may include a plurality of functional modules composed of program code segments. Program code for each program segment in the browser-based medical image processing device 20 may be stored in a memory of the terminal and executed by the at least one processor to perform (see fig. 1 for details) the functions of browser-based medical image processing.

In this embodiment, the medical image processing device 20 based on the browser is aimed at completing the geometric transformation and display of the medical image at the browser end, without the auxiliary processing and participation of the server, and can be divided into a plurality of functional modules according to the functions executed by the device. The functional module may include: the device comprises an acquisition module 201, a first determination module 202, a second determination module 203, a third determination module 204, a geometric transformation module 205, an extraction module 206, a calculation module 207 and a display module 208. The module referred to in the present invention refers to a series of computer program segments capable of being executed by at least one processor and of performing a fixed function, stored in a memory. In the present embodiment, the functions of the respective modules will be described in detail in the following embodiments.

The acquisition module 201 is configured to acquire an original medical image.

The terminal in this embodiment may support 3D drawing protocol (Web Graphics Library, webGL) technology, which is a browser-supported technology, allowing JavaScript and OpenGL ES2.0 to be combined together, and by adding one JavaScript binding of OpenGL ES2.0, webGL may provide hardware 3D accelerated rendering for HTML5 Canvas, creating complex navigation and data visualization.

A first determining module 202 is configured to obtain a first image and a second image according to pixel values in the original medical image.

Preferably, the first determining module 202 obtains a first image and a second image according to pixel values in the original medical image:

scanning original pixel values in the original medical image;

The second determining module 203 is configured to determine a first pixel value of a red color channel and a second pixel value of a green color channel in the first image according to a preset first segmentation algorithm.

Preferably, the determining, by the second determining module 203, the first pixel value of the red channel and the second pixel value of the green channel in the first image according to a preset first segmentation algorithm includes:

The third determining module 204 is configured to determine a third pixel value of a red color channel and a fourth pixel value of a green color channel in the second image according to a preset second segmentation algorithm.

Preferably, the determining, by the third determining module 204, the third pixel value of the red color channel and the fourth pixel value of the green color channel in the second image according to a preset second segmentation algorithm includes:

A geometric transformation module 205, configured to perform geometric transformation on the first image and the second image.

The extracting module 206 is configured to extract the geometrically transformed first pixel value and the geometrically transformed second pixel value, and the geometrically transformed third pixel value and fourth pixel value.

The calculating module 207 is configured to calculate a target pixel value according to the geometrically transformed first pixel value, second pixel value, third pixel value, and fourth pixel value.

Preferably, the calculating module 207 calculates the target pixel value according to the geometrically transformed first pixel value, second pixel value, third pixel value and fourth pixel value, including:

The target pixel value is calculated by the following formula:

X0＝X1+X2-X3-X4；

A display module 208 for processing and displaying the target pixel values according to a digital imaging and communication protocol.

In summary, according to the browser-based medical image processing device disclosed by the invention, the acquired original medical image is processed to obtain the first image and the second image; determining a first pixel value of a red channel and a second pixel value of a green channel in the first image according to a preset first segmentation algorithm; determining a third pixel value of a red channel and a fourth pixel value of a green channel in the second image according to a preset second segmentation algorithm; performing geometric transformation on the first image and the second image, and extracting a first pixel value and a second pixel value after geometric transformation, and a third pixel value and a fourth pixel value after geometric transformation; finally, calculating to obtain a target pixel value according to the geometrically transformed first pixel value, second pixel value, third pixel value and fourth pixel value; the target pixel values are processed and displayed in accordance with a digital imaging and communications protocol of medicine. According to the technical scheme provided by the invention, a background server is not needed to assist in processing when the original medical image is called up, a server is not needed to participate in operation, the medical image can be directly displayed at a browser end, and the pixel value in the original medical image is read through the WebGL technology supported by the browser, so that the calculation speed is greatly improved, the response time is shortened, and the method is beneficial to use in a high-concurrency scene.

Example III

Fig. 3 is a schematic structural diagram of a terminal according to a third embodiment of the present invention. In the preferred embodiment of the invention, the terminal 3 comprises a memory 31, at least one processor 32, at least one communication bus 33, a transceiver 34 and a browser 35.

It will be appreciated by those skilled in the art that the configuration of the terminal shown in fig. 3 is not limiting of the embodiments of the present invention, and that it may be a bus type configuration, a star type configuration, or a combination of hardware and software, or a different arrangement of components, as the terminal 3 may include more or less hardware or software than is shown.

In some embodiments, the terminal 3 includes a terminal capable of automatically performing numerical calculation and/or information processing according to a preset or stored instruction, and its hardware includes, but is not limited to, a microprocessor, an application specific integrated circuit, a programmable gate array, a digital processor, an embedded device, and the like. The terminal 3 may further comprise a client device, which includes, but is not limited to, any electronic product capable of performing man-machine interaction with a client through a keyboard, a mouse, a remote controller, a touch pad, a voice control device, etc., for example, a personal computer, a tablet computer, a smart phone, a digital camera, etc.

It should be noted that the terminal 3 is only used as an example, and other electronic products that may be present in the present invention or may be present in the future are also included in the scope of the present invention by way of reference.

In some embodiments, the memory 31 is used to store program codes and various data, such as the browser-based medical image processing apparatus 20 installed in the terminal 3, and to implement high-speed, automatic access to programs or data during operation of the terminal 3. The Memory 31 includes Read-Only Memory (ROM), programmable Read-Only Memory (PROM), erasable programmable Read-Only Memory (EPROM), one-time programmable Read-Only Memory (One-time Programmable Read-Only Memory, OTPROM), electrically erasable rewritable Read-Only Memory (EEPROM), compact disc Read-Only Memory (Compact Disc Read-Only Memory, CD-ROM) or other optical disc Memory, magnetic tape Memory, or any other medium that can be used for computer-readable carrying or storing data.

In some embodiments, the at least one processor 32 may be comprised of an integrated circuit, for example, a single packaged integrated circuit, or may be comprised of multiple integrated circuits packaged with the same or different functions, including one or more central processing units (Central Processing unit, CPU), microprocessors, digital processing chips, graphics processors, combinations of various control chips, and the like. The at least one processor 32 is a Control Unit (Control Unit) of the terminal 3, connects the respective components of the entire terminal 3 using various interfaces and lines, and performs various functions of the terminal 3 and processes data, such as a function of performing medical image processing of a browser, by running or executing programs or modules stored in the memory 31, and calling data stored in the memory 31.

In some embodiments, the at least one communication bus 33 is arranged to enable connected communication between the memory 31 and the at least one processor 32 or the like.

Although not shown, the terminal 3 may further include a power source (such as a battery) for supplying power to the respective components, and preferably, the power source may be logically connected to the at least one processor 32 through a power management device, so as to perform functions of managing charging, discharging, power consumption management, etc. through the power management device. The power supply may also include one or more of any of a direct current or alternating current power supply, recharging device, power failure detection circuit, power converter or inverter, power status indicator, etc. The terminal 3 may further include various sensors, bluetooth modules, wi-Fi modules, etc., which will not be described herein.

It should be understood that the embodiments described are for illustrative purposes only and are not limited to this configuration in the scope of the patent application.

The integrated units implemented in the form of software functional modules described above may be stored in a computer readable storage medium. The software functional modules described above are stored in a storage medium and include instructions for causing a computer device (which may be a personal computer, a terminal, or a network device, etc.) or a processor (processor) to perform portions of the methods described in the various embodiments of the invention.

In a further embodiment, in connection with fig. 2, the at least one processor 32 may execute the operating device of the terminal 3 and various installed applications (such as the browser-based medical image processing device 20), program code, etc., such as the various modules described above.

The memory 31 has program code stored therein, and the at least one processor 32 can invoke the program code stored in the memory 31 to perform related functions. For example, each of the modules depicted in fig. 2 is a program code stored in the memory 31 and executed by the at least one processor 32 to perform the functions of the respective modules for the purpose of browser-based medical image processing.

In one embodiment of the present invention, the memory 31 stores a plurality of instructions that are executed by the at least one processor 32 to implement browser-based medical image processing functionality.

Specifically, the specific implementation method of the above instruction by the at least one processor 32 may refer to the description of the relevant steps in the corresponding embodiment of fig. 1, which is not repeated herein.

In the several embodiments provided by the present invention, it should be understood that the disclosed apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the modules is merely a logical function division, and there may be other manners of division when actually implemented.

The modules described as separate components may or may not be physically separate, and components shown as modules may or may not be physical units, may be located in one place, or may be distributed over multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

In addition, each functional module in the embodiments of the present invention may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units can be realized in a form of hardware or a form of hardware and a form of software functional modules.

It will be evident to those skilled in the art that the invention is not limited to the details of the foregoing illustrative embodiments, and that the present invention may be embodied in other specific forms without departing from the spirit or essential characteristics thereof. The present embodiments are, therefore, to be considered in all respects as illustrative and not restrictive, the scope of the invention being indicated by the appended claims rather than by the foregoing description, and all changes which come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein. Any reference sign in a claim should not be construed as limiting the claim concerned. Furthermore, it will be obvious that the term "comprising" does not exclude other elements or that the singular does not exclude a plurality. A plurality of units or means recited in the apparatus claims can also be implemented by means of one unit or means in software or hardware. The terms first, second, etc. are used to denote a name, but not any particular order.

Finally, it should be noted that the above-mentioned embodiments are merely for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications and equivalents may be made to the technical solution of the present invention without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. A browser-based medical image processing method, the method comprising:

acquiring an original medical image;

obtaining a first image and a second image according to pixel values in the original medical image, wherein the method comprises the following steps: scanning original pixel values in the original medical image; determining a positive number of the original pixel values as pixel values at corresponding positions in the first image, and determining pixel values at the rest positions in the first image as 0; determining a negative pixel value of the original pixel values as a pixel value at a corresponding position in the second image, and determining pixel values at the rest positions in the second image as 0;

determining a first pixel value of a red channel and a second pixel value of a green channel in the first image according to a preset first segmentation algorithm, including: judging whether the pixel value in the first image is smaller than a preset pixel threshold value or not; when the pixel value in the first image is smaller than the preset pixel threshold value, determining that a first pixel value at a corresponding position of a red channel in the first image is 0, and determining that a second pixel value at a corresponding position of a green channel in the first image is the pixel value in the first image; when the pixel value in the first image is greater than or equal to the preset pixel threshold value, determining a first tangential value and a first residual value according to the maximum pixel value in the original medical image; determining a first pixel value at a corresponding position of a red channel in the first image as the first cut value, and determining a second pixel value at a corresponding position of a green channel in the first image as the first remainder value;

Determining a third pixel value of a red channel and a fourth pixel value of a green channel in the second image according to a preset second segmentation algorithm, including: judging whether the absolute value of the pixel value in the second image is smaller than a preset pixel threshold value or not; when the absolute value of the pixel value in the second image is smaller than the preset pixel threshold value, determining that the third pixel value at the corresponding position of the red channel in the second image is 0, and determining that the fourth pixel value at the corresponding position of the green channel in the second image is the pixel value in the absolute value of the pixel value in the second image; when the absolute value of the pixel value in the second image is larger than or equal to the preset pixel threshold value, determining a second segmentation value and a second residual value according to the minimum pixel value in the original medical image; determining a third pixel value at a corresponding position of a red channel in the second image as the second cut-off value, and determining a second pixel value at a corresponding position of a green channel in the second image as the second residual value;

geometrically transforming the first image and the second image;

Calculating a target pixel value according to the geometrically transformed first pixel value, second pixel value, third pixel value and fourth pixel value, including: the first pixel value after the geometric transformation is subjected to product calculation with a first sub-value to obtain a new first pixel value; the third pixel value after the geometric transformation is subjected to product calculation with the second sub-value to obtain a new third pixel value; calculating to obtain a target pixel value according to the new first pixel value, the geometrically transformed second pixel value, the new third pixel value and the geometrically transformed fourth pixel value;

2. The method of claim 1, wherein determining a first score value and a first residual value from a maximum pixel value in the original medical image comprises: dividing the maximum pixel value by the preset pixel threshold value, and then rounding downwards to obtain a first sub-value; dividing the pixel value in the first image by the first sub-value, then rounding downwards to obtain a first tangential value, dividing the pixel value in the first image by the first sub-value, and then taking the remainder to obtain a first residual value;

The determining a second score value and a second residual value according to the minimum pixel value in the original medical image comprises: dividing the minimum pixel value by the preset pixel threshold value, then rounding downwards and taking an absolute value to obtain a second sub-value; dividing the absolute value of the pixel value in the second image by the second sub-value, then rounding downwards to obtain a second dividing value, dividing the absolute value of the pixel value in the second image by the second sub-value, and then taking the remainder to obtain a second remainder.

3. The method of claim 2, wherein the target pixel value is calculated by the formula:

X0=X1+X2-X3-X4；

4. A browser-based medical image processing apparatus, the apparatus comprising:

the acquisition module is used for acquiring the original medical image;

the first determining module is configured to obtain a first image and a second image according to pixel values in the original medical image, and includes: scanning original pixel values in the original medical image; determining a positive number of the original pixel values as pixel values at corresponding positions in the first image, and determining pixel values at the rest positions in the first image as 0; determining a negative pixel value of the original pixel values as a pixel value at a corresponding position in the second image, and determining pixel values at the rest positions in the second image as 0;

A second determining module, configured to determine a first pixel value of a red channel and a second pixel value of a green channel in the first image according to a preset first segmentation algorithm, including: judging whether the pixel value in the first image is smaller than a preset pixel threshold value or not; when the pixel value in the first image is smaller than the preset pixel threshold value, determining that a first pixel value at a corresponding position of a red channel in the first image is 0, and determining that a second pixel value at a corresponding position of a green channel in the first image is the pixel value in the first image; when the pixel value in the first image is greater than or equal to the preset pixel threshold value, determining a first tangential value and a first residual value according to the maximum pixel value in the original medical image; determining a first pixel value at a corresponding position of a red channel in the first image as the first cut value, and determining a second pixel value at a corresponding position of a green channel in the first image as the first remainder value;

a third determining module, configured to determine a third pixel value of a red channel and a fourth pixel value of a green channel in the second image according to a preset second segmentation algorithm, where the third determining module includes: judging whether the absolute value of the pixel value in the second image is smaller than a preset pixel threshold value or not; when the absolute value of the pixel value in the second image is smaller than the preset pixel threshold value, determining that the third pixel value at the corresponding position of the red channel in the second image is 0, and determining that the fourth pixel value at the corresponding position of the green channel in the second image is the pixel value in the absolute value of the pixel value in the second image; when the absolute value of the pixel value in the second image is larger than or equal to the preset pixel threshold value, determining a second segmentation value and a second residual value according to the minimum pixel value in the original medical image; determining a third pixel value at a corresponding position of a red channel in the second image as the second cut-off value, and determining a second pixel value at a corresponding position of a green channel in the second image as the second residual value;

the calculation module is configured to calculate a target pixel value according to the geometrically transformed first pixel value, second pixel value, third pixel value, and fourth pixel value, and includes: the first pixel value after the geometric transformation is subjected to product calculation with a first sub-value to obtain a new first pixel value; the third pixel value after the geometric transformation is subjected to product calculation with the second sub-value to obtain a new third pixel value; calculating to obtain a target pixel value according to the new first pixel value, the geometrically transformed second pixel value, the new third pixel value and the geometrically transformed fourth pixel value;

5. A terminal comprising a processor for implementing the browser-based medical image processing method according to any one of claims 1 to 3 when executing a computer program stored in a memory.

6. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the browser-based medical image processing method according to any one of claims 1 to 3.