WO2009128213A1 - 医用診断装置および医用診断装置の画質改善方法 - Google Patents
医用診断装置および医用診断装置の画質改善方法 Download PDFInfo
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Definitions
- the present invention relates to a medical diagnostic apparatus that acquires a signal reflected or transmitted from a subject and generates an image, and a medical diagnostic apparatus and a medical apparatus having a function of improving image quality by image processing on an acquired captured image
- the present invention relates to a method for improving image quality of a diagnostic apparatus.
- noises and the blunting of the edges cause a deterioration in image quality and have an adverse effect on diagnosis.
- noise removal processing and signal component enhancement processing by image processing Application of is desired.
- Patent Documents 1 and 2 As a noise removal technique by image processing applied to a medical image, processing using a linear filter, median filter, or wavelet transform is well known (Patent Documents 1 and 2).
- signal component enhancement processing methods include a method using an edge enhancement spatial filter such as a Laplacian filter, and a signal enhancement by extracting a high frequency component and amplifying the extracted high frequency component.
- Patent Documents 1 to 6 perform only one of noise removal processing and signal component enhancement processing.
- Patent Document 7 and Patent Document 8 A technique for performing both noise removal processing and signal component enhancement processing is disclosed.
- the conventional signal component enhancement processing method using a Laplacian filter and the method of amplifying high-frequency components generally have a problem that ringing occurs in the vicinity of the edge and the image quality is likely to deteriorate.
- edge enhancement processing using a morphological filter has been attracting attention as processing that can enhance signal components while suppressing ringing in the vicinity of the edge.
- the technique described in Non-Patent Document 1 is one of them.
- the present invention provides high-quality image quality improvement means for the purpose of further improving image quality.
- Patent Document 7 As a method for performing both noise removal processing and signal component enhancement processing, there are image quality improvement methods described in Patent Document 7 and Patent Document 8.
- the former method when image processing is performed on a captured image by wavelet transformation, the expansion coefficient after wavelet transformation is reduced, and the high-frequency component adaptively based on edge information obtained from the high-frequency component of the wavelet transformation.
- the noise removal process and the signal component enhancement process can be performed simultaneously.
- Non-Patent Document 1 a morphological filter as described in Non-Patent Document 1 has recently been used as an alternative to a technique using a Laplacian filter, which is a conventional signal component enhancement processing technique, or a technique for amplifying high-frequency components.
- the edge emphasis processing using the method has been attracting attention as a processing capable of emphasizing a signal component while suppressing ringing in the vicinity of the edge.
- This technique is a technique in which the lightness value closer to the input image for each pixel is used as the lightness value of the output image among the dilated image and the degenerated image obtained by using the morphological filter.
- a good signal component enhancement effect can be obtained for a document image.
- a general medical image has a problem that a change in the brightness value of the image becomes discontinuous at the boundary of switching between the expanded image and the degenerated image, resulting in a strange pattern.
- image quality improvement when processing is performed using the same parameters without considering the imaging conditions, imaging target, image type, image characteristics, etc. of the captured image, sufficient image quality is obtained depending on the image. It's hard to be done. For example, when a large structural element is used in signal component enhancement processing using a morphological filter, a good sharpening effect can be obtained for a large pattern, but the fine pattern is crushed and unnatural. On the other hand, when a small structural element is used, a fine pattern shape is naturally maintained, but a sufficient sharpening effect cannot be obtained for a large pattern.
- the processing time and the image quality improvement performance in the image quality improvement processing are usually in a trade-off relationship.
- the required processing time differs depending on the inspection application. For example, when inspecting a part with high motion such as the heart, it is necessary to observe a moving image at a high frame rate, and thus processing with a small amount of calculation is required. . However, with a simple process with a small amount of calculation, sufficient performance cannot be obtained when inspecting a site with a gradual fluctuation.
- the above-mentioned problem is solved by adopting the following image quality improvement method in the medical diagnostic apparatus.
- noise removal processing and signal component enhancement processing are sequentially performed.
- the signal component enhancement process on the image after noise removal, it is possible to sharpen the edge that has been blunted by the noise removal process or to enhance the signal component while suppressing the amplification of noise.
- composition is performed by weighted addition of the captured image, the image after noise removal, and the image after signal component enhancement.
- the granularity of the medical image can be adjusted to a good ratio by combining the captured images.
- the effect of signal component enhancement can be enhanced while maintaining a good granularity ratio.
- a weight w deno for weights w x and the signal component weights for the enhancement after image w e sum after the noise removal of the value obtained by subtracting from the constant image for the captured image to maintain the same brightness level and the captured image be able to.
- an index representing the naturalness of the image is calculated based on an index representing the granularity and the index representing the strength of the artifact, and the noise suppression degree and the signal component enhancement degree are automatically calculated according to this index.
- Non-Patent Document 1 The technique using the morphological filter described in Non-Patent Document 1 is improved to obtain a good signal component enhancement effect while suppressing ringing.
- the improved technique of the present invention after obtaining a dilated image and a degenerated image using a morphological filter, when combining them, continuous interpolation is performed on a portion where a strange pattern is likely to occur and its vicinity. To achieve smooth connection.
- the processing parameters are set so as to obtain a high-performance image quality effect and an appropriate image display speed according to the imaging conditions, imaging target, image type, and image characteristics.
- image display speed processing that does not slow down the display speed at the same time as obtaining the maximum performance of moving images with respect to the image display speed determined by the captured image conditions, image type, imaging target, and image characteristics. Use parameters.
- the present invention relates to a medical diagnostic apparatus, which improves image quality by sequentially performing noise removal processing and signal component enhancement processing on a captured image obtained by imaging a test object and then combining them.
- this is a device that processes the image with improved image quality and performs a medical diagnosis.
- FIG. 1A is a flowchart showing a flow of processing in the medical diagnostic apparatus according to the present invention.
- an object to be inspected is imaged (S11), and an image quality improvement process is performed on the image of the object to be inspected (S12), and this process improves the image quality.
- image processing post-processing
- S13 information obtained by this image processing is displayed on a display screen or transmitted to a higher-level information management system (S14).
- FIG. 1B shows an example of a processing flow in the image quality improvement processing of S12.
- noise removal is performed on the captured image x by the noise removal processing 101 to obtain a noise-removed image y deno .
- the captured image x is a vector having a scalar value x [m, n] for each position (m, n).
- the signal component enhancement processing by the signal component enhancement processing 102 against the noise removed image y deno obtains the signal component enhanced image y e.
- the captured image x, a noise removed image y deno synthesized signal component enhanced image y e by signal combining processing 103 obtains the image y after the image quality improvement.
- the image y after image quality improvement, the image y e after signal component enhancement, and the image y deno after noise removal are vectors having scalar values at each position (m, n), like the captured image x.
- FIG. 2A is a diagram showing an embodiment of a configuration of a medical diagnostic apparatus that handles signals transmitted from a subject such as an MRI diagnostic apparatus, an X-ray apparatus, and a CT apparatus.
- the medical diagnostic apparatus 201 roughly includes an imaging unit 21 that images a subject and acquires an image, an image processing unit 22 that processes the acquired image, an image display unit 23 that displays the processed image, and an imaging unit 21 and an image.
- the control unit 24 is configured to control the entire unit including the processing unit 22 and the image display unit 23.
- the imaging means 21 acquires a transmission sensor 203 that transmits an electric signal after being converted into an electromagnetic wave / X-ray, a transmission circuit unit 202 that generates a drive signal to the transmission sensor, and an electromagnetic wave / X-ray transmitted from the subject 200.
- the image processing means 22 is obtained from an image data storage unit 207 that stores a large amount of image data, an image data I / O control unit 208 that controls access to the image data storage unit 207, and an image data I / O control unit 208.
- the image display means 23 includes a scan conversion unit 215 that converts processed image data obtained through the image data I / O control unit 208 into a predetermined display form, and an image display unit 217 that displays an image.
- the control unit 24 includes an input unit 218 and a system control unit 216 for inputting imaging conditions and various processing parameters from a user.
- the system control unit 216 includes a transmission circuit unit 202, a reception circuit unit 205, and an image generation unit 206.
- the image data I / O control unit 208 and the input unit 218 are managed in total.
- FIG. 2B is a diagram showing an embodiment of a configuration of a medical diagnostic apparatus that handles a signal reflected from a subject such as an ultrasonic diagnostic apparatus.
- the transmission / reception part of FIG. 2B is different from FIG. 2A, and instead of the configuration in which the transmission circuit unit 202, the transmission sensor 203, the reception sensor 204, and the reception circuit unit 205 in FIG.
- the system includes a transmission / reception sensor 219 and a transmission / reception circuit unit 220.
- FIG. 2A showing a case where the present invention is applied to a medical diagnostic apparatus that handles a signal transmitted from a subject such as an MRI diagnostic apparatus, an X-ray apparatus, or a CT apparatus.
- a medical diagnostic apparatus that handles a signal transmitted from a subject
- a subject such as an MRI diagnostic apparatus, an X-ray apparatus, or a CT apparatus.
- the image generation unit 206 is read as 206 ', the description is as shown in FIG. 2B.
- the image generation unit 206 may perform position correction so that an image obtained by performing transmission and reception in continuous time frames and the display position of the tissue are the same.
- the image quality improvement processing described in FIG. 1B is performed using the noise removal unit 211 of the image data processing unit 209 for the noise removal processing 101 and the signal component enhancement unit for the signal component enhancement processing 102.
- the signal synthesis processing 103 is processed by the signal synthesis unit 213, respectively.
- the pre-processing unit 210 and the post-processing unit 214 in the image data processing unit 209 perform processing other than image quality improvement.
- a process of converting a rectangular image such as scan conversion into a fan-shaped image is an example.
- the system control unit 216 controls operations of the transmission / reception circuit unit 220, the image generation unit 206, the image data I / O control unit 208, the scan conversion unit 215, and the like.
- the noise removal processing 101 performed by the noise removal processing unit 211 is a process using a linear filter, a median filter, or a wavelet transform as disclosed in Patent Document 1 or 2 described in the section of the related art. Or the like.
- FIG. 3A shows an example of a synthesis processing flow of the signal component enhanced image y e , the captured image x, and the noise-removed image y deno of the present invention.
- This synthesis is performed by weighted addition 301 of the signal component enhanced image y e , the captured image x, and the noise-removed image y deno .
- the respective weighting factors for y e , x, and y deno are w e , w x , and w deno .
- the image quality improved image y is calculated as the following equation (1).
- FIG. 3B shows another embodiment. After capturing the image x is generated the noise image y n by differential processing 302 with the noise removed image y deno, synthesis signal component enhanced image y e, captured image x, weighting factor to the noise image y n w 'e, This is performed by weighted addition 303 using w ′ x and w ′ n . In the case of this processing, the image quality improved image y is calculated as in the following equations (2) and (3).
- the method for synthesizing after extracting the noise image y n is the embodiment of FIG. 3 (b), there is an advantage that it is easy to adjust the degree of suppression of noise.
- 3 (a) and 3 (b) show an example of composition by product-sum operation, but composition using other operations may be performed.
- the weighted addition 401 in the signal synthesis processing 103-3 shown in FIG. 4A and the weighted addition 407 in the signal synthesis processing 103-3 shown in FIG. 4B are 301 in FIG. This corresponds to the combination of 302 and 303 in FIG.
- FIG. 4A shows an example of a processing flow for automatically adjusting the weight of weighted addition according to the naturalness of the image.
- the signal component enhanced image y e by naturalness calculation 402 with naturalness calculated captured image x, and the noise removal after image y deno, each image y e, x, y deno
- the corrected y e obtained by weight correction 404 is obtained.
- x, and feedback weighting factor w e of y deno, w x, a w deno the weighted addition 401 implementing the weighted addition 401 again.
- the processes 401 to 404 are repeatedly performed until it is determined in step 403 that there is no need for weight correction.
- the result of weighted addition when it is determined that weight correction is not necessary is defined as an image quality improved image y.
- the naturalness of an image is a psychological concept, and its subjective evaluation can be quantified and expressed on an objective evaluation scale.
- an objective evaluation scale that represents the naturalness of a medical image can be expressed as a combination of objective evaluation parameters that represent the gradation, sharpness, graininess, and the strength of artifacts peculiar to medical images.
- naturalness may be obtained by weighted addition of these objective evaluation parameters, or a more complicated calculation formula may be used.
- Non-Patent Document 2 As an objective evaluation parameter representing gradation, there is contrast, DanielDJ. Jobson et al .: TheStatistics of Visual Representation, Visual Information Processing XI, Proc. SPIE 4736, (2002) (Non-Patent Document 2) It is preferable to use the standard deviation of the brightness value in the local region of the image as in the method described in the above.
- objective evaluation parameters representing the granularity evaluation values such as RMS granularity and Wiener spectrum can be used.
- the objective evaluation parameter indicating the strength of the artifact may be calculated using a method disclosed in, for example, Japanese Patent Application Laid-Open No. 2002-253546 (Patent Document 9).
- FIG. 4B shows an example of another processing flow.
- the naturalness calculated by the naturalness calculation 405 is used, and the weight is calculated by the weight calculation 406. Then, an image quality improved image y is obtained by weighted addition 407 using the obtained weight.
- FIG. 5 is a diagram illustrating an example of a processing flow of the sharpening process.
- a sharpening process is performed using a morphological filter.
- the expansion image y dil and the reduction image y ero are generated, and then the weighted addition processing 503 generates the sharpened image y s (6 )
- the dilated image y dir and the degenerated image y ero are calculated as in the following equations (4) and (5), respectively.
- g is a vector representing the filter coefficient of a morphological filter called a structural element.
- FIG. 6 shows an embodiment for a one-dimensional waveform in a cross section in an image.
- a degenerate waveform 603 is generated by a locus drawn by the center point of the structural element.
- the 604 structural element-g is moved so as to touch from above, it is generated by a locus drawn by the center point of the expansion waveform 605.
- FIG. 7 is a diagram showing an example of a one-dimensional waveform in a certain section in an image.
- a graph 701 shows an example of a sharpening method that smoothly switches from the lightness value of the expansion waveform to the lightness value of the degeneration waveform by weighted addition of the lightness value of the expansion waveform and the lightness value of the degeneration waveform. .
- expansion processing and degeneration processing are performed on the input waveform 703 to obtain an expansion waveform y dir of 706 and a degeneration waveform y ero of 705. Then, among the brightness values of the expanded waveform and the degenerated waveform, a value close to the brightness value of the input waveform is set as the brightness value of the output waveform.
- Weighted addition is performed using an index w dir indicating the degree of expansion and an index w ero indicating the degree of degeneration so as to smoothly switch the lightness value of the expansion waveform to the lightness value of the degeneration waveform.
- index w dir indicating the degree of expansion
- index w ero indicating the degree of degeneration
- the output image is divided into three regions, each of which is a region [A] in which the brightness value of the expanded image is the brightness value of the output image, and the brightness value of the degenerated image is the output brightness.
- the output waveform 704 can be obtained.
- a graph 702 shows an example of w ero , w dir , and w. 707 is w, 708 is w dir , and 709 is w ero .
- the method for obtaining ys by the expression (6) has been described. However, ys may be obtained by using another calculation method.
- edge extraction processing that can be used as part of signal component enhancement processing will be described with reference to FIG.
- an edge image y edge having a bright brightness value and a narrow width is generated by a top hat transformation 801 using a morphological filter.
- the image after denoising y deno or the sharpened image y s is subjected to the reduction processing by the reduction processing 802 and then the expansion processing 803 is performed on the reduction image y ero , thereby opening the opening image.
- Generate y opening .
- the edge image y edge can be extracted by the process 804 of subtracting the opening image y opening from the input image.
- FIGS. 9A and 9B and FIGS. 9B and 9B show an example of a processing flow in combination with four types of sharpening processing and other enhancement processing.
- FIG. 9A shows signal component enhancement processing 102-1 (hereinafter, when substantially the same processing as signal component enhancement processing 102 in FIG. 1 is performed, a serial number is added after hyphen 102 and displayed). It is one Example figure showing the processing flow in.
- the sharpening process 901 and the edge extraction process 902 are configured in parallel. That is, while the noise removed image y deno, by performing the sharpening process 901 obtains the sharpened image y s.
- an edge image y edge is extracted by performing an edge extraction process 902 on the image y deno after noise removal.
- the synthesis processing 903 of the edge components by combining the edge image y edge and sharpened image y s, obtains a signal component enhanced image y e.
- a signal component enhancement processing image is calculated as in the following equation (10).
- the weight w edge may be fixed or may change for each position.
- the sharpening processing 901 and the edge extraction processing 904 are configured in series. That is, for first noise removal after image y deno, by performing a sharpening process 901 obtains the sharpened image y s.
- an edge extraction process 904 is similar to the processing of 902 relative to sharpened image y s, obtaining an edge image y edge.
- a synthetic 905 of edge components to obtain the signal component enhanced image y e.
- the sharpening processing 901 and the contrast correction processing 906 are configured in parallel. That is, while the noise removed image y deno, by performing the sharpening process 901 obtains the sharpened image y s.
- contrast correction processing 906 is performed on the image y deno after noise removal.
- contrast correction processing 906 global contrast correction may be performed, local contrast correction may be performed, or these processes may be combined.
- an image y e after signal component enhancement is obtained by synthesizing the post-contrast correction image y c and the sharpened image y s by the signal enhancement synthesis process 907.
- the signal enhancement combining process calculates the image y e after signal enhancement combining processing as in the following equation (11).
- the sharpening processing 901 and the contrast correction processing 908 are configured in series. That is, for first noise removal after image y deno, by performing a sharpening process 901 obtains the sharpened image y s. Then, by performing the contrast correction processing 908 is similar to the processing of 906 relative to sharpened image y s, and generates a contrast corrected image y c. Finally, the signal enhancement combining processing 909, obtains a signal component enhanced image y e.
- FIG. 11 is an example showing a flow of image quality improvement processing in the present invention.
- processing parameters are determined based on imaging conditions, image types, and imaging targets, which are image imaging information.
- the processing parameters for each image capturing information are tabulated in advance.
- a function 1102 that can acquire an external parameter whose value can be adjusted by the user based on the processing parameter obtained from the table can be provided.
- noise removal processing 101-1, signal component enhancement processing 102-5, and signal synthesis processing 103-5 are performed using the determined processing parameters.
- FIG. 12 is an example showing a table 1201 in which processing parameters for each image pickup information in the ultrasonic medical diagnostic apparatus used in the internal processing parameter determination processing 1101 and the external processing parameter determination processing 1102 in FIG. 11 are described.
- the values in the table 1201 may be prepared in advance based on the output of the internal processing parameter determination processing 1101, or the values input or selected by the user through the interface by the external processing parameter acquisition processing 1102 are acquired. May be.
- Each row of the table 1201 represents a processing parameter used in each image capturing information.
- the imaging information includes the imaging conditions in the column 1202, the image type in the column 1203, the imaging target in 1204, and the characteristics of the image in 1205.
- imaging conditions for example, in the case of ultrasound, the type of ultrasound probe, display magnification, frequency band used for ultrasound transmission / reception signals, application of spatial compound method, application of frequency compound method, scanning of ultrasound transmission signal Pitch and the like.
- the processing parameter includes a parameter related to a sharpening process using a morphology filter shown in a column 1206, and a parameter related to a process such as a noise removal process, a signal component enhancement process, and a signal synthesis process.
- the processing parameter described in the top row is applied among the rows that match the image capturing information in the table.
- FIG. 10 shows an embodiment for a one-dimensional waveform in a certain section in the image.
- the vertical axis represents the brightness value of the image
- the horizontal axis represents the position.
- a small structural element 1002 is used so that the naturalness of the image is not lost.
- a large structural element 1001 is used for a pattern that does not contain many low-frequency components so that a high sharpening effect can be obtained.
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Abstract
Description
本発明は、医用診断装置に関するものであり、被試験体を撮像して取得された撮像画像に対してノイズ除去処理と信号成分強調処理を順次に行った後それらを合成することにより画質を改善し、この画質が改善された画像を処理して医用診断を行う装置である。
図1(a)は、本発明に係る医用診断装置における処理の流れを示すフロー図である。
本発明に係る医用診断装置においては、先ず被検査体を撮像し(S11)、撮像して取得した被検査体の画像に対して画質改善処理を施し(S12),この処理により画質が改善された画像を用いて画像処理(後処理)を行い(S13)、この画像処理により得られた情報を表示画面などに表示又は上位の情報管理システムに送信する(S14)。
システム制御部216は、送受信回路部220、画像生成部206、画像データI/O制御部208、走査変換部215等の動作を制御する。
201,201’…医用診断装置、 202…送信回路部、 203…送信センサー、 204…受信センサー、 205…受信回路部、 206,206’…画像生成部、 207,207’…画像データ記憶部、 208,208’…画像データI/O制御部、 209,209’…画像データ処理部、 210,210’…前処理部、 211,211’…ノイズ除去部、 212,212’…信号成分強調部、 213,213’…信号合成部、 214,214’…後処理部、 215,215’…走査変換部、 216,216’…システム制御部、 217,217’…画像表示部、 218,218’…入力部、 219…送受信センサー、 220…送受信回路部。
Claims (14)
- 被検体を撮像して該被検体の画像を取得する撮像手段と、
該撮像手段で取得した前記被検体の画像を処理する画像処理手段と、
該画像処理手段で処理した前記被検体の画像を表示する画像表示手段と、
前記撮像手段と前記画像処理手段と前記表示手段とを制御する制御手段と
を備えた医用診断装置であって、
前記画像処理手段は、
前記生成した前記被検体の画像のノイズを除去する画像ノイズ除去部と、
該画像ノイズ除去部でノイズを除去した画像に対して信号成分強調処理を行って信号成分強調処理画像を生成する信号成分強調処理部と、
前記被検体の画像と前記画像ノイズ除去部でノイズを除去した画像と前記信号成分強調処理部で信号成分強調処理を行った信号成分強調処理画像とを合成して合成画像を生成する画像合成部と
を有することを特徴とする医用診断装置。 - 前記画像処理手段の信号成分強調処理部は、前記ノイズを除去した画像に対してモルフォロジカルフィルタを用いた鮮鋭化処理を含む請求項1記載の医用診断装置。
- 前記鮮鋭化処理は、前記モルフォロジカルフィルタを用いて膨張画像および縮退画像を生成した後、該膨張画像および該縮退画像の組み合わせにより鮮鋭化する請求項2記載の医用診断装置。
- 前記信号成分強調処理部は、前記ノイズを除去した画像に対して鮮鋭化処理とエッジ抽出処理とを含む請求項1記載の医用診断装置。
- 前記信号成分強調処理部は、前記ノイズを除去した画像に対して鮮鋭化処理を行った画像と、前記ノイズを除去した画像に対してエッジ抽出処理を行ったエッジ画像とを合成して前記信号成分強調処理画像を生成する請求項1記載の医用診断装置。
- 前記画像合成部は、前記被検体の画像と前記画像ノイズ除去部でノイズを除去した画像と前記信号成分強調処理部で信号成分強調処理を行った信号成分強調処理画像とを、重み付き加算により前記合成画像を生成する請求項1記載の医用診断装置。
- 前記画像合成部は、ノイズ抑制度合い、信号成分強調度合いのうち少なくとも一つを、画像の自然さを表す評価値に応じて調整する請求項1記載の医用診断装置。
- 医用診断装置における画像の画質を改善する方法であって、
前記医用診断装置で取得した画像のノイズを除去してノイズ除去画像を生成し、
該生成したノイズ除去画像に対して信号成分強調処理を行って信号成分強調画像を生成し、
前記医用診断装置で取得した画像と前記ノイズ除去画像と前記信号成分強調画像とを合成して合成画像を生成することを含んで前記画像の画質を改善することを特徴とする医用診断装置の画質改善方法。 - 前記信号成分強調処理は、前記ノイズを除去した画像に対してモルフォロジカルフィルタを用いた鮮鋭化処理である請求項8記載の医用診断装置の画質改善方法。
- 前記信号成分強調処理は、前記ノイズを除去した画像に対する鮮鋭化処理とエッジ抽出処理とを含む請求項8記載の医用診断装置の画質改善方法。
- 前記信号成分強調処理は、前記ノイズを除去した画像に対して前記モルフォロジカルフィルタを用い、膨張画像および縮退画像を生成した後、該膨張画像および該縮退画像の組み合わせにより鮮鋭化する信号鮮鋭化処理を含む請求項10記載の医用診断装置の画質改善方法。
- 前記信号成分強調処理は、前記ノイズを除去した画像に対して鮮鋭化処理を行った画像と、前記ノイズを除去した画像に対してエッジ抽出処理を行ったエッジ画像とを合成して前記信号成分強調処理画像を生成する請求項10記載の医用診断装置の画質改善方法。
- 前記合成画像を、前記被検体の画像と前記ノイズ除去画像と前記信号成分強調処理画像とを、重み付き加算により生成する請求項10記載の医用診断装置の画質改善方法。
- 前記画像合成は、ノイズ抑制度合い、信号成分強調度合いのうち少なくとも一つを画像の自然さを表す評価値に応じて調整する請求項8記載の医用診断装置の画質改善方法。
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