US20130188857A1 - Information processing apparatus, information processing system, information processing method, program, and recording medium - Google Patents

Information processing apparatus, information processing system, information processing method, program, and recording medium Download PDF

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US20130188857A1
US20130188857A1 US13/824,228 US201113824228A US2013188857A1 US 20130188857 A1 US20130188857 A1 US 20130188857A1 US 201113824228 A US201113824228 A US 201113824228A US 2013188857 A1 US2013188857 A1 US 2013188857A1
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mark
tissue sample
information processing
sample image
unit
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Yoshiko Yoshihara
Tomoharu Kiyuna
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NEC Corp
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NEC Corp
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Definitions

  • the present invention relates to an information processing apparatus, an information processing system, an information processing method, a program, and a recording medium.
  • a region of cancer cells is selected, and the number of the cancer cells is counted.
  • information on a tumor region is acquired based on a HE-stained image, and this information is aligned with an IHC-stained image, and thus, a tumor region in the IHC-stained image is specified.
  • Patent Document 1 WO 2008/108059
  • the present invention is intended to provide an information processing apparatus, an information processing system, an information processing method, a program, and a recording medium, capable of selecting a region of cancer cells in any tissue sample image and easily and accurately counting the number of the cancer cells.
  • the information processing apparatus is an information processing apparatus including: an acquisition unit for acquiring image data obtained by reading a tissue sample image obtained by putting a mark specifying a selected area on an image obtained by immunostaining and then imaging a biological tissue; and a counting unit for counting the number of cancer cells in the selected area specified by the mark based on the image data of the tissue sample image acquired by the acquisition unit, wherein a diagnosis based on the tissue sample image is supported.
  • the information processing system is an information processing system including: the information processing apparatus according to the present invention; an input terminal; and a display terminal, wherein the information processing apparatus includes: a receiving unit for receiving the image data via a network; and a sending unit for sending, via a network, the number of cancer cells counted in the selected area specified by the mark by the counting unit, and the image data received by the receiving unit is input and sent via a network by the input terminal, and the number of cancer cells counted in the selected area specified by the mark by the counting unit is received via a network and displayed by the display terminal.
  • the information processing method is an information processing method using the information processing apparatus according to the present invention, the method including: an acquiring step of acquiring, by the acquisition unit, image data obtained by reading a tissue sample image with a mark specifying a selected area; and a counting step of counting, by the counting unit, the number of cancer cells in the selected area specified by the mark based on the image data of the tissue sample image acquired by the acquiring step.
  • the program according to the present invention is a program capable of executing the information processing method according to the present invention on a computer.
  • the recording medium according to the present invention is a computer-readable recording medium including: the program according to the present invention.
  • a region of cancer cells in any tissue sample image can be selected, and the number of the cancer cells can be counted easily and accurately.
  • FIG. 1 is a block diagram showing a configuration of an information processing apparatus according to the first embodiment of the present invention.
  • FIG. 2 is a block diagram showing a configuration of an information processing system according to the second embodiment of the present invention.
  • FIG. 3 is a sequence diagram showing a processing sequence in the information processing system according to the second embodiment of the present invention.
  • FIG. 4A is a block diagram showing a hardware configuration of a pathological image diagnosis support apparatus according to the second embodiment of the present invention.
  • FIG. 4B is a block diagram showing a configuration of a RAM in the pathological image diagnosis support apparatus according to the second embodiment of the present invention.
  • FIG. 4C is a block diagram showing a configuration of a storage in the pathological image diagnosis support apparatus according to the second embodiment of the present invention.
  • FIG. 5 is a flowchart showing a procedure for operating the pathological image diagnosis support apparatus according to the second embodiment of the present invention.
  • FIG. 6 is a figure showing the first example of a tissue sample image with a mark according to the second embodiment of the present invention.
  • FIG. 7 is a figure showing the second example of a tissue sample image with marks according to the second embodiment of the present invention.
  • FIG. 8 is a figure showing an image for checking a selected area according to the second embodiment of the present invention.
  • FIG. 9 is a figure showing the first example of a send image according to the second embodiment of the present invention.
  • FIG. 10 is a figure showing the second example of a send image according to the second embodiment of the present invention.
  • FIG. 11 is a figure showing the third example of a tissue sample image with marks according to the second embodiment of the present invention.
  • FIG. 12 is a sequence diagram showing a processing sequence in an information processing system according to the third embodiment of the present invention.
  • FIG. 13 is a figure showing a selected area divided into meshes in the third embodiment of the present invention.
  • FIG. 14 is a sequence diagram showing a processing sequence in an information processing system according to the fourth embodiment of the present invention.
  • FIG. 15 is a figure showing superimposition of a selected area according to the fourth embodiment of the present invention.
  • FIG. 1 shows the information processing apparatus 100 which supports a diagnosis based on a tissue sample image 150 obtained by immunostaining and then imaging a biological tissue.
  • the information processing apparatus 100 includes: an acquisition section (acquisition unit) 110 for acquiring image data 155 obtained by reading the tissue sample image 150 with a mark 151 put thereon and specifying a selected area 152 .
  • the information processing apparatus 100 further includes: a counting section (counting unit) 120 for counting the number of cancer cells in the selected area specified by the mark 151 based on the image data 155 of the tissue sample image 150 acquired by the acquisition section 110 .
  • a region of cancer cells in any tissue sample image can be easily and accurately selected, and the number of the cancer cells can be easily and accurately counted.
  • the “selected area” is also referred to as a “focus area” in the present invention.
  • FIG. 2 is a block diagram showing a configuration of an information processing system 250 including a pathological image diagnosis support apparatus 200 as the information processing apparatus according to the second embodiment.
  • the pathological image diagnosis support apparatus 200 is connected, via a network 240 , to a plurality of client PCs 220 each of which includes a color scanner 221 for reading (inputting) a tissue sample image thereinto.
  • the pathological image diagnosis support apparatus 200 is also connected to a pathological image diagnosis center 230 for sending an image or results obtained through processes by the pathological image diagnosis support apparatus 200 so that specialized physicians can analyze and diagnose.
  • the pathological image diagnosis support apparatus 200 corresponds to the information processing apparatus according to the present invention.
  • each of the client PCs 220 and the color scanners 221 corresponds to an “input terminal” of the information processing system according to the present invention. It can be said that each of the client PCs 220 also corresponds to a “display terminal” of the information processing system according to the present invention. It can be said that the pathological image diagnosis center 230 also corresponds to a “display terminal” of the information processing system according to the present invention.
  • the network 240 may be a public network including the Internet or an in-hospital LAN.
  • the communication control section 201 of the pathological image diagnosis support apparatus 200 receives a tissue sample image with a mark sent from a client PC 220 via a network (i.e., image data obtained by reading the tissue sample image with a mark by a color scanner 221 ). That is, it can be said that the communication control section 201 corresponds to a “receiving unit” for receiving, via a network 240 , the tissue sample image with a mark.
  • the received tissue sample image with a mark (image data) is stored in an image storage section (image storage unit) 202 . It can be said that the image storage section (image storage unit) 202 corresponds to an “acquisition unit” for acquiring image data obtained by reading the tissue sample image with a mark.
  • a mark on the tissue sample image with the mark is recognized together with the position thereof.
  • a mark position storage section (mark position storage unit) 204 the position of the recognized mark is stored. This storage allows superimposing a tissue sample image in the fourth embodiment described below.
  • a mark-specified region selection section (a selection unit or a mark-specified region selection unit) 205 a mark-specified region is selected based on the tissue sample image with the mark and the position of the mark stored in the image storage section 202 .
  • the inside of the mark which is a closed curve is a specified region.
  • a region including the position of the mark may be automatically set as a mark-specified region.
  • a mark is not limited to only one, and there may be a plurality of marks.
  • a specified region dividing section (a dividing unit or a specified region dividing unit) 206 a mark-specified region of the third embodiment described below is divided into meshes, and the divided regions are transmitted to a cancer cell counter (counting unit) 207 .
  • the cancer cell counter 207 counts the number of cancer cells with each staining intensity in a parenchymal cell region to be observed in the mark.
  • a display data generation section (display data generation unit) 208 send data is generated based on a count value obtained by counting the number of cancer cells with each staining intensity by the cancer cell counter 207 ,the tissue sample image, or the mark. Desired display data in a diagnosable format is selected as the display data by the client PC 220 .
  • the selected display data is sent from the communication control section 201 to the client PC 220 via the network and is displayed on a display screen. Alternatively, the selected display data is sent to the pathological image diagnosis center 230 so that specialized physicians can analyze and diagnose.
  • the communication control section 201 also corresponds to a “sending unit” for sending, via a network 240 , a count value obtained by counting the number of cancer cells in the selected area specified by the mark of the tissue sample image by the counting unit.
  • a processing sequence in the information processing system according to the second embodiment is shown below with reference to FIG. 3 .
  • a color scanner 221 reads a slide with a mark which is a tissue sample image with a mark.
  • the read tissue sample image with a mark is then sent from the color scanner 221 to a client PC 220 and is sent to a pathological image diagnosis support apparatus 200 which is the information processing apparatus. That is, it can be said that a series of the sequences S 301 and S 303 corresponds to an “inputting and sending step” of, by the input terminal, inputting (reading) and sending, via a network, image data received by a receiving unit (communication control section 201 ).
  • the pathological image diagnosis support apparatus 200 receives the image data from a communication control section 201 (receiving step), then acquires the image data in an image storage section (acquisition unit) 202 (acquiring step), and recognizes the mark in the mark recognition section 203 .
  • the mark is a mark put on the slide of the tissue sample image by a physician with a magic marker in order to separate a focus area of stained positive cells (an area in which the number of cancer cells is counted) from the other area, for example.
  • sequences S 307 to S 313 indicated by a dotted line in FIG. 3 a result of the mark recognition is displayed on the client PC 220 , and the selected area in the mark is checked. These sequences, however, are performed optionally. For example, when the mark is not closed as a closed curve, it becomes necessary for a user to check an area in which the number of cancer cells is counted. A mark other than this may be a point indicating the center position of the area or a line segment indicating a part of the edge of the area.
  • a screen for selecting an area hereinafter referred to as an “area selection screen” (see FIG. 8 described below) is generated.
  • the generated area selection screen is then sent from the pathological image diagnosis support apparatus 200 to the client PC 220 .
  • the area selection screen is displayed on the client PC 220 , and the area is checked.
  • an instruction of counting the number of cancer cells in the area by a user is sent to the pathological image diagnosis support apparatus 200 .
  • a sequence S 315 the pathological image diagnosis support apparatus 200 counts the number of cancer cells in the selected area in the mark. If a checking sequence, i.e., a series of the sequences S 307 to S 313 indicated by a dotted line is not performed, the sequence is shifted from the sequence S 305 to the sequence S 315 . In a sequence S 317 (sending step), the counted number of cancer cells is sent. The sending of the counted number of cancer cells includes sending of display data of the selected area.
  • a series of sequences S 321 to S 329 of FIG. 3 is a variation of the processing sequence.
  • a slide with or without a mark is read as a tissue sample image.
  • a mark is added on a display screen of the acquired tissue sample image by the client PC 220 (see FIG. 7 described below).
  • the tissue sample image with the added mark or the tissue sample image with the mark which has been put thereon and the added mark is sent from the client PC 220 to the pathological image diagnosis support apparatus 200 .
  • the pathological image diagnosis support apparatus 200 counts the number of cancer cells in each selected area in the put mark and/or the added mark.
  • the counted number of cancer cells is sent. The sending of the counted number of cancer cells includes sending of display data of the selected area.
  • FIG. 4A is a block diagram showing a hardware configuration of the pathological image diagnosis support apparatus 200 as an information processing apparatus according to the second embodiment.
  • the pathological image diagnosis support apparatus 200 includes: a CPU (Central Processing Unit) 410 ; a ROM (Read Only Memory) 420 ; a communication control section 201 ; a RAM (Random Access Memory) 430 ; and a storage 440 .
  • a CPU Central Processing Unit
  • ROM Read Only Memory
  • communication control section 201 a communication control section 201
  • RAM Random Access Memory
  • the CPU 410 is an arithmetic and control processor and executes programs so that functions of sections of FIGS. 2 and 3 can be achieved.
  • the ROM 420 stores fixed data such as initial data and initial programs and programs.
  • the communication control section 201 communicates, via the network 240 , with client PCs 220 and the pathological image diagnosis center 230 which are outside devices.
  • the RAM 430 is a temporal storage section used as a working area for temporal storage by the CPU 410 .
  • image data to be processed 431 and display data 432 are temporally stored in the RAM 430 .
  • the RAM 430 includes a program execution region 433 for executing programs by the CPU 410 .
  • the storage 440 is a nonvolatile storage of diagnosis support information 441 , various parameters 442 , and various programs 443 .
  • the image data 431 to be processed in the RAM 430 includes the following data.
  • the display data 432 sent to the client PC 220 via the communication control section 201 includes the following data.
  • the diagnosis support information 441 in the storage 440 includes the following data.
  • various parameters 442 in the storage 440 include the following parameters.
  • various programs 443 in the storage 440 include the following programs.
  • a procedure for operating a pathological image diagnosis support apparatus 200 having the above-described configuration is described in detail below with reference to flowcharts and examples of display screens.
  • a CPU 410 executes programs shown in each flowchart so that functions of the components in FIG. 2 are achieved.
  • FIG. 5 is a flowchart showing an overall procedure for supporting diagnosis in the present embodiment.
  • a step S 500 the pathological image diagnosis support apparatus 200 waits for a tissue sample image with a mark to be sent from a client PC 220 .
  • the tissue sample image with a mark is received, it is stored in a step S 510 (acquiring step).
  • FIG. 6 shows the first example of the tissue sample image with a mark
  • FIG. 7 shows the second example of the tissue sample image with marks.
  • a mark 601 which is a closed curve enclosing a region 602 in which a user desires to count the number of cancer cells is drawn in, for example, dark blue although it is not distinguished in FIG. 6 .
  • FIGS. 6 and 7 a rectangular mark 701 and marks 702 to 704 which are closed curves, enclosing each region in which a user desires to count the number of cancer cells are drawn in the respective colors although it is not distinguished in FIG. 7 , for example.
  • the difference between FIGS. 6 and 7 is as follows.
  • the mark is drawn on a slide by a user with a magic marker or the like.
  • the marks are overlaid on the display screen of the client PC 220 .
  • the mark drawn on a slide and the mark overlaid on the display screen may be present together.
  • a mark is extracted from the received tissue sample image with the mark, and a selected area is recognized.
  • Various methods are known as a method for extracting a mark or a method for recognizing a selected area, and any of them can be used.
  • a step S 530 is a step of checking a selected area with a user, corresponding to a series of sequences S 307 to S 313 .
  • a step S 531 an image is generated by mapping a selected area into the tissue sample image.
  • the selected area-mapped image thus obtained is sent to the client PC 220 .
  • FIG. 8 shows an example of a display of the selected area-mapped image.
  • a selected area-mapped image 800 of FIG. 8 a closed curve 801 extracted from a mark is displayed in pink, and a selected area 802 is filled in green.
  • the display is converted into a display easily checked by a user.
  • the pathological image diagnosis support apparatus 200 waits for a user to check and accept, and when it is instructed to count the number of cancer cells, the step is shifted to a step S 540 .
  • step S 540 (counting step) the number of the cancer cells with each staining intensity in the selected area in the mark is counted.
  • the pathological image diagnosis support apparatus 200 waits for all of selected areas indicated by the marks to be processed completely in a step S 550 .
  • step S 560 display data of the counted number of cancer cells is generated in order to send it to the client PC 220 .
  • FIG. 9 shows the first example of a display screen displaying the counted number.
  • FIG. 10 shows the second example of a display screen displaying the counted number. The display screen of FIG.
  • a display screen 1000 of FIG. 10 includes: an enlarged tissue sample image 1001 of one selected area; a reduced-size image 1002 of the selected area; and a thumbnail image 1003 of the tissue sample image.
  • the display screen 1000 further includes: thumbnail images 1004 of five selected areas, each including a bar-graph; and a bar-graph 1010 according to the selected area.
  • the bar-graph 1010 includes: a region 1011 indicating the number of cells with “strong” staining intensity, a region 1012 indicating the number of cells with “weak” staining intensity, and a region 1013 indicating the number of cells with “none” of staining intensity, for example.
  • the thumbnail image 1003 of the entire tissue sample image and the thumbnail images 1004 of five selected area, each including a bar-graph are displayed as buttons.
  • FIG. 10 shows the case where the third selected area indicated by the numeral “3” is selected.
  • a dark box of the third selected area indicated by the numeral “3” among the thumbnail images of the five selected areas indicates the result that the third selected area is selected.
  • sending step the generated display data is sent to the client PC 220 .
  • a step S 580 whether or not a user added a selected area and instructed to count the number of cells is determined from the result displayed on the client PC 220 .
  • the pathological image diagnosis support apparatus 200 waits for a tissue sample image with a mark specifying the added selected area to be sent in the step S 500 .
  • the steps from S 510 to S 570 are performed.
  • FIG. 11 shows a tissue sample image with marks specifying added selected areas. In a display image 1100 of FIG. 11 , marks 1106 of the added selected areas are superimposed on a tissue sample image 1101 in addition to marks 1105 of selected areas in each of which the number of cells has been counted.
  • the marks 1105 are indicated by red, and the marks 1106 are indicated by yellow, so that they are distinguishable, for example.
  • the numerals 1102 to 1104 indicate thumbnail images of selected areas in each of which the number of cells has been counted as buttons for selection as indicated by the numerals 1002 to 1004 of FIG. 10 .
  • the third embodiment shows an example of dividing a selected area into meshes and counting the number of cells in each small area of each mesh when the large number of cancer cells is contained or masses of cancer cells are spread in the selected area in a mark, for example.
  • a selected area may be divided into meshes, the number of cells in each mesh may be counted, and the total number of cells may be used as the counted number.
  • the total number of cells may be used as the counted number.
  • the storage 440 includes a mesh size parameter 483 as one of various parameter 442 .
  • the mesh size parameter 483 is used as a parameter for dividing a selected area into meshes when the large number of cancer cells is contained or masses of cancer cells are spread in the selected area in a mark, for example (see FIG. 13 ).
  • the storage 440 further includes a mesh division program 494 as one of various programs 443 . This program is used to divide a selected area into meshes and executes S 1201 of FIG. 12 .
  • a processing sequence in the information processing system according to the third embodiment is shown below with reference to FIG. 12 .
  • a color scanner 221 reads a slide with a mark which is a tissue sample image with a mark.
  • the read tissue sample image with a mark is then sent from the color scanner 221 to a client PC 220 and is sent to a pathological image diagnosis support apparatus 200 which is an information processing apparatus.
  • the pathological image diagnosis support apparatus 200 recognizes the mark.
  • the above-described sequences are the same as those in FIG. 3 of the second embodiment.
  • the pathological image diagnosis support apparatus 200 divides the selected area selected with the mark into meshes.
  • the selected area is divided using the mesh size parameter 483 shown in FIG. 4C .
  • the mesh size is appropriately set according to the size, the enlargement ratio, the resolution, the number of cells in one mesh, and the like, for example.
  • FIG. 13 shows an example of a display obtained by dividing a selected area selected with a mark into meshes. In a display image 1300 of FIG. 13 , the selected area in a mark 1301 is divided into 81 mesh regions 1302 .
  • a sequence S 1203 the number of cells in each mesh is counted, and the total counted number of cells in the 81 mesh regions 1302 is calculated by the pathological image diagnosis support apparatus 200 . Then, in a sequence S 1205 , the total counted number of cancer cells is sent to the client PC 220 as a result of the total counted number of cancer cells. It is desired that the send data includes display data of the selected area with meshes superimposed thereon of FIG. 13 .
  • a process is terminated.
  • a selection instruction meshes specified according to the selection instruction are acquired in a sequence S 1209 .
  • the client PC 220 sends information (the mesh number or mesh position information) on the meshes selected in a sequence S 1211 to the pathological image diagnosis support apparatus 200 .
  • the pathological image diagnosis support apparatus 200 counts the number of cells in each selected mesh in a sequence S 1213 and sends the counted number of cancer cells in each selected mesh in a sequence S 1215 to the client PC 220 .
  • a plurality of tissue sample images obtained through staining by a plurality of staining methods shares a mark extracted from one tissue sample image with the mark.
  • a mark extracted from a HE-stained slide with the mark is applied to an IHC-stained slide without the mark, and then the number of cancer cells in the mark is counted.
  • FIG. 14 is a figure showing a processing sequence in the information processing system according to the fourth embodiment.
  • a color scanner 221 reads a HE-stained slide with a mark which is a tissue sample image with a mark.
  • the read tissue sample image with a mark is then sent from the color scanner 221 to a client PC 220 and is further sent to a pathological image diagnosis support apparatus 200 .
  • the pathological image diagnosis support apparatus 200 recognizes the mark.
  • the pathological image diagnosis support apparatus 200 stores a position of the mark.
  • a sequence S 1403 the color scanner 221 reads an IHC-stained slide without the mark which is a tissue sample image without the mark.
  • the read tissue sample image without the mark is then sent from the color scanner 221 to the client PC 220 and is further sent to the pathological image diagnosis support apparatus 200 .
  • the pathological image diagnosis support apparatus 200 When the pathological image diagnosis support apparatus 200 receives a tissue sample image of the same biological tissue stained by another staining method, the sequence is shifted to a sequence S 1409 .
  • the position of the mark stored in the sequence S 1401 is read out.
  • the tissue sample image with the mark read from the HE-stained slide with the mark is aligned with the tissue sample image without the mark read from the IHC-stained slide without a mark.
  • FIG. 15 schematically shows the alignment. In FIG.
  • the numeral 1500 indicates a HE-stained tissue sample image
  • the numeral 1521 indicates an IHC-stained ER tissue sample image
  • the numeral 1522 indicates an IHC-stained PgR tissue sample image
  • the numeral 1523 indicates an IHC-stained HER2 tissue sample image.
  • the numeral 1510 indicates a HE-stained tissue sample image
  • the numeral 1511 indicates a mark in the tissue sample image with the mark.
  • the numeral 1530 indicates an IHC-stained tissue sample image.
  • the alignment is performed by pattern matching such as rotating an image, for example. The alignment is described in detail in the patent document 1 and the like and can be performed appropriately by those skilled in the art.
  • the mark 1511 put on the HE-stained tissue sample image 1510 can also serve as a mark 1531 of the IHC-stained tissue sample image 1530 .
  • a sequence S 1415 the counted number of cancer cells is sent to the client PC 220 .
  • display data of the selected area is sent in addition to the counted number of cancer cells.
  • the present invention may be applied to a system composed of a plurality of units or a single unit.
  • the present invention is applicable also in the case where the control program for achieving the functions of the embodiments is supplied from a system or apparatus directly or remotely. Therefore, the scope of the present invention encompasses a control program installed in a computer so as to achieve functions of the present invention, a medium storing the control program, and a WWW server from which the control program is downloaded.

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Cited By (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20150105658A1 (en) * 2013-10-16 2015-04-16 Samsung Electronics Co., Ltd. Ultrasonic imaging apparatus and control method thereof
US20150147772A1 (en) * 2010-09-30 2015-05-28 Nec Corporation Information processing apparatus, information processing system, information processing method, program, and recording medium
US20150279032A1 (en) * 2014-03-26 2015-10-01 Sectra Ab Automated cytology/histology viewers and related methods
US20150324521A1 (en) * 2014-05-09 2015-11-12 Canon Kabushiki Kaisha Information processing apparatus, information processing method, and storage medium storing program
CN105388176A (zh) * 2014-08-28 2016-03-09 日本株式会社日立高新技术科学 荧光x射线分析装置以及其样品显示方法
US20180180550A1 (en) * 2016-04-29 2018-06-28 Synaptive Medical (Barbados) Inc. Multi-modal optical imaging system for tissue analysis
US10489633B2 (en) 2016-09-27 2019-11-26 Sectra Ab Viewers and related methods, systems and circuits with patch gallery user interfaces
CN113724235A (zh) * 2021-09-02 2021-11-30 山东省千佛山医院 镜下环境改变条件时半自动化的Ki67/ER/PR阴性、阳性细胞计数***及方法
US11443426B2 (en) * 2018-01-18 2022-09-13 Nantomics, Llc Real-time whole slide pathology image cell counting

Families Citing this family (9)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP6336391B2 (ja) 2012-09-06 2018-06-06 ソニー株式会社 情報処理装置、情報処理方法、およびプログラム
CN107884319B (zh) * 2016-09-30 2023-05-02 日本电气株式会社 用于对粉尘传感器进行标定的***和方法
CN107036956A (zh) * 2017-05-22 2017-08-11 粉蓝医疗科技（杭州）有限公司 细胞核统计方法和装置
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WO2019106973A1 (ja) * 2017-11-29 2019-06-06 ソニー株式会社 標識選択支援システム、標識選択支援装置、標識選択支援方法、及び標識選択支援用プログラム
US20210033599A1 (en) * 2018-04-26 2021-02-04 Nec Corporation Information processing apparatus, control method, and program
CN111290685A (zh) * 2020-02-28 2020-06-16 杭州依图医疗技术有限公司 细胞染色图像的显示方法、病理图像分析***及存储介质
CN112580748B (zh) * 2020-12-30 2022-10-14 电子科技大学 一种对染色图像的分类细胞计数的方法
WO2023199617A1 (ja) * 2022-04-10 2023-10-19 株式会社ニコン 検出装置、検出方法、および検出プログラム

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20030215936A1 (en) * 2000-12-13 2003-11-20 Olli Kallioniemi High-throughput tissue microarray technology and applications
US20040085443A1 (en) * 2000-12-13 2004-05-06 Kallioniemi Olli P Method and system for processing regions of interest for objects comprising biological material
US6775402B2 (en) * 1997-03-03 2004-08-10 Bacus Laboratories, Inc. Method and apparatus for creating a virtual microscope slide
US7177454B2 (en) * 1995-11-30 2007-02-13 Clarient, Inc. Automated detection of objects in a biological sample

Family Cites Families (15)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6091842A (en) 1996-10-25 2000-07-18 Accumed International, Inc. Cytological specimen analysis system with slide mapping and generation of viewing path information
JPH10197522A (ja) * 1997-01-14 1998-07-31 Mitsubishi Electric Corp 病理組織診断支援装置
CA2295918A1 (en) * 1997-07-17 1999-01-28 Accumed International, Inc. Inspection system with specimen preview
JP2002042110A (ja) * 2000-07-27 2002-02-08 Ateeru:Kk 画像計測システム、画像計測方法及び画像計測用プログラムを記録したコンピュータ読み取り可能な記録媒体
US6615063B1 (en) * 2000-11-27 2003-09-02 The General Hospital Corporation Fluorescence-mediated molecular tomography
JP3721105B2 (ja) * 2001-08-22 2005-11-30 日本電気株式会社 組織検査法を利用する胃癌の切除手術後の予後検査方法
AU2002333589A1 (en) 2001-09-12 2003-03-24 Burstein Technologies, Inc. Methods for differential cell counts including related apparatus and software for performing same
US20070135999A1 (en) * 2005-12-13 2007-06-14 Applied Spectral Imaging Ltd. Method, apparatus and system for characterizing pathological specimen
WO2007109678A2 (en) * 2006-03-20 2007-09-27 Baylor College Of Medicine Method and system for non-contact fluorescence optical tomography with patterned illumination
US8070682B2 (en) * 2006-07-19 2011-12-06 The University Of Connecticut Method and apparatus for medical imaging using combined near-infrared optical tomography, fluorescent tomography and ultrasound
WO2008108059A1 (ja) * 2007-03-01 2008-09-12 Nec Corporation 乳癌病理画像診断支援システム、乳癌病理画像診断支援方法、乳癌病理画像診断支援プログラム、及び、乳癌病理画像診断支援プログラムを記録した記録媒体
CN101221118A (zh) * 2007-12-07 2008-07-16 东华大学 一种智能识别与计数痰涂片显微图像结核菌的***和方法
JP5648479B2 (ja) * 2008-10-09 2015-01-07 日本電気株式会社 病理組織診断支援システム、病理組織診断支援プログラム、病理組織診断支援方法
JP5387147B2 (ja) * 2009-06-03 2014-01-15 日本電気株式会社 病理画像診断システム、病理画像処理方法、病理画像診断プログラム
US20130188857A1 (en) * 2010-09-30 2013-07-25 Nec Corporation Information processing apparatus, information processing system, information processing method, program, and recording medium

Patent Citations (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7177454B2 (en) * 1995-11-30 2007-02-13 Clarient, Inc. Automated detection of objects in a biological sample
US7558415B2 (en) * 1995-11-30 2009-07-07 Carl Zeiss Microimaging Ais, Inc. Automated detection of objects in a biological sample
US6775402B2 (en) * 1997-03-03 2004-08-10 Bacus Laboratories, Inc. Method and apparatus for creating a virtual microscope slide
US7146372B2 (en) * 1997-03-03 2006-12-05 Olympus America Inc. Method and apparatus for creating a virtual microscope slide
US20030215936A1 (en) * 2000-12-13 2003-11-20 Olli Kallioniemi High-throughput tissue microarray technology and applications
US20040085443A1 (en) * 2000-12-13 2004-05-06 Kallioniemi Olli P Method and system for processing regions of interest for objects comprising biological material

Cited By (16)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20150147772A1 (en) * 2010-09-30 2015-05-28 Nec Corporation Information processing apparatus, information processing system, information processing method, program, and recording medium
US9704018B2 (en) * 2010-09-30 2017-07-11 Nec Corporation Information processing apparatus, information processing system, information processing method, program, and recording medium
US20150105658A1 (en) * 2013-10-16 2015-04-16 Samsung Electronics Co., Ltd. Ultrasonic imaging apparatus and control method thereof
US9984457B2 (en) 2014-03-26 2018-05-29 Sectra Ab Automated grossing image synchronization and related viewers and workstations
US20150279032A1 (en) * 2014-03-26 2015-10-01 Sectra Ab Automated cytology/histology viewers and related methods
US9547898B2 (en) * 2014-03-26 2017-01-17 Sectra Ab Automated cytology/histology viewers and related methods
US20150324521A1 (en) * 2014-05-09 2015-11-12 Canon Kabushiki Kaisha Information processing apparatus, information processing method, and storage medium storing program
US11238974B2 (en) * 2014-05-09 2022-02-01 Canon Kabushiki Kaisha Information processing apparatus, information processing method, and storage medium storing program
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KR102296009B1 (ko) 2014-08-28 2021-08-30 가부시키가이샤 히다치 하이테크 사이언스 형광 x 선 분석 장치 및 그 시료 표시 방법
KR20160026654A (ko) * 2014-08-28 2016-03-09 가부시키가이샤 히다치 하이테크 사이언스 형광 x 선 분석 장치 및 그 시료 표시 방법
US20180180550A1 (en) * 2016-04-29 2018-06-28 Synaptive Medical (Barbados) Inc. Multi-modal optical imaging system for tissue analysis
US10768114B2 (en) * 2016-04-29 2020-09-08 Synaptive Medical (Barbados) Inc. Multi-modal optical imaging system for tissue analysis
US10489633B2 (en) 2016-09-27 2019-11-26 Sectra Ab Viewers and related methods, systems and circuits with patch gallery user interfaces
US11443426B2 (en) * 2018-01-18 2022-09-13 Nantomics, Llc Real-time whole slide pathology image cell counting
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