WO2013088806A1 - 医用画像を検索する方法、装置及びコンピュータプログラム - Google Patents
医用画像を検索する方法、装置及びコンピュータプログラム Download PDFInfo
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Definitions
- the present invention relates to a method, an apparatus, and a computer program for searching for a medical image that can search for an image having a high similarity to an acquired image from a plurality of stored images.
- Patent Document 1 a cardiac magnetic signal is measured, a measured cardiac magnetic signal is compared with a cardiac magnetic signal measured in the past, and estimation of whether or not a heart disease occurs, and cardiac A cardiac magnetic measurement apparatus for estimating a disease candidate is disclosed. Further, as an example of searching by comparing images, for example, in Patent Document 2, a similarity between a diagnostic image in past interpretation report data and a new diagnostic image is calculated, and a diagnosis in past interpretation report data is also calculated. A search system that searches past diagnostic images and corresponding interpretation report data in consideration of the appearance rate of result names is disclosed.
- Patent Document 1 the determination is based on indirect information such as a cardiac magnetic signal and cannot be distinguished from the case where a similar signal is generated due to another disease.
- Patent Document 2 the similarity between images is calculated by the Euclidean distance between the feature portions of the two images. However, it is necessary to determine which portion of the captured image is the feature portion, and the doctor's interpretation. There was a problem that there was a possibility that a difference in judgment might occur due to superiority or inferiority of technology.
- the present invention has been made in view of such circumstances, and a method for searching a medical image that can search for an existing image corresponding to a similar case with high accuracy using a newly acquired X-ray image,
- An object is to provide an apparatus and a computer program.
- the method according to the first invention may be executed by a device for searching for a medical image that searches for a similar image to a newly captured image from medical images based on past cases.
- the keywords included in the interpretation information are extracted, and based on the extracted keywords, similar interpretation information is detected from the stored keywords.
- the method according to the second aspect of the present invention calculates a two-dimensional Gabor wavelet characteristic as the wavelet characteristic in the first aspect.
- the method according to the third invention is the method according to the first or second invention, wherein M (M is a natural number of 2 or more) wavelet features are calculated for each image and binarized to calculate an M-dimensional bit string. And calculating the frequency distribution vector for all images, and calculating the spatial distance as an angle formed between the calculated frequency distribution vectors.
- an apparatus is an apparatus for searching for a medical image that searches for a similar image to a newly captured image from medical images based on past cases.
- a feature calculating unit that calculates wavelet features of a plurality of images that have been captured and stored in the past, a keyword extracting unit that extracts keywords included in the interpretation information for each stored image, and Information storage means for storing the calculated wavelet feature and the extracted keyword in association with the image, image acquisition means for acquiring a newly captured image, wavelet feature calculation means for calculating the wavelet feature of the acquired image, Extract keywords included in the interpretation information corresponding to the acquired image, and from the stored keywords based on the extracted keywords Interpretation information retrieval means for retrieving similar interpretation information, an image corresponding to the retrieved interpretation information, a spatial distance calculation means for calculating a spatial distance based on wavelet features between the acquired images, and the calculated spatial distance Output means for outputting images shorter than a predetermined value as search results in the order of short spatial distance.
- the feature calculation means and the wavelet feature calculation means calculate a two-dimensional Gabor wavelet feature as the wavelet feature.
- an M-dimensional bit string is obtained by calculating M (M is a natural number of 2 or more) wavelet features for each image and binarizing each of the wavelet features.
- M is a natural number of 2 or more
- a frequency distribution vector calculating means for calculating frequency distribution vectors for all images, and the spatial distance calculating means calculates the spatial distance as an angle formed between the calculated frequency distribution vectors.
- a computer program is an apparatus for searching for a medical image that searches for a similar image to a newly captured image from medical images based on past cases.
- a computer program that can be executed, the device being included in feature calculation means for calculating wavelet features of a plurality of images that have been captured and stored in the past, and interpretation information for each stored image Keyword extraction means for extracting keywords, information storage means for storing the calculated wavelet features and extracted keywords in association with stored images, image acquisition means for acquiring newly captured images, and wavelets of acquired images Wavelet feature calculation means for calculating features, keywords included in interpretation information corresponding to the acquired image Based on the extracted and extracted keywords, the interpretation information retrieval means for retrieving similar interpretation information from the stored keywords, the spatial distance based on the wavelet feature between the acquired image and the image corresponding to the retrieved interpretation information And an output means for outputting an image having a calculated spatial distance shorter than a predetermined value as a search result in order of increasing spatial distance.
- the computer program according to the eighth invention causes the feature calculating means and the wavelet feature calculating means to function as means for calculating a two-dimensional Gabor wavelet feature as the wavelet feature.
- the computer program according to a ninth aspect is the computer program according to the seventh or eighth aspect, wherein the device calculates M (M is a natural number of 2 or more) wavelet features for each image, and binarizes each.
- M is a natural number of 2 or more
- the spatial distance calculation means calculates the spatial distance as an angle formed between the calculated frequency distribution vectors. Function as a means to
- a similar image can be searched from images stored as past cases based on the wavelet feature indicating the characteristics of the acquired medical image.
- the present invention is implemented as a computer program that can be partially executed by a computer. be able to. Therefore, the present invention is a hardware embodiment of a medical image search device for searching for a medical image that searches for a similar image to a newly captured image from medical images based on past cases, as software. Or an embodiment of a combination of software and hardware.
- the computer program can be recorded on any computer-readable recording medium such as a hard disk, DVD, CD, optical storage device, magnetic storage device or the like.
- a similar image can be searched from images stored as past cases based on the wavelet feature indicating the characteristic of the acquired medical image. Even a doctor can search for an image corresponding to the most similar case, and can select an appropriate medical practice.
- FIG. 1 is a block diagram schematically showing a configuration of a medical image search apparatus according to an embodiment of the present invention.
- the medical image search apparatus 1 includes at least a CPU (Central Processing Unit) 11, a memory 12, a storage device 13, an I / O interface 14, a video interface 15, a portable disk drive 16, and a communication interface 17. And an internal bus 18 for connecting the hardware described above.
- CPU Central Processing Unit
- the CPU 11 is connected to the hardware units as described above of the medical image search apparatus 1 via the internal bus 18, controls the operation of the hardware units described above, and stores the computer program 100 stored in the storage device 13. Various software functions are executed according to the above.
- the memory 12 is composed of a volatile memory such as SRAM or SDRAM, and a load module is expanded when the computer program 100 is executed, and stores temporary data generated when the computer program 100 is executed.
- the storage device 13 includes a built-in fixed storage device (hard disk), a ROM, and the like.
- the computer program 100 stored in the storage device 13 is downloaded by the portable disk drive 16 from a portable recording medium 90 such as a DVD or CD-ROM in which information such as programs and data is recorded, and from the storage device 13 at the time of execution.
- the program is expanded into the memory 12 and executed.
- a computer program downloaded from an external computer connected via the communication interface 17 may be used.
- the storage device 13 includes a medical image storage unit 131, an interpretation information storage unit 132, a visual word storage unit 133, and a frequency distribution information storage unit 134.
- the medical image storage unit 131 stores past image data obtained by X-ray imaging in association with identification information for identifying interpretation information.
- the interpretation information storage unit 132 stores the results of a doctor interpreting and diagnosing past medical images. For example, a doctor's diagnosis result such as “a nodule shadow is observed in the upper lobe of the left lung field. Suspected squamous cell carcinoma. Instructing detailed examination by HR-CT” is stored as text data in association with identification information.
- the visual word storage unit 133 stores a Gabor wavelet feature group described later as a visual word.
- the frequency distribution information storage unit 134 stores a frequency distribution vector of values obtained by binarizing the calculated wavelet features and converting them into an M-dimensional bit string.
- the communication interface 17 is connected to an internal bus 18 and can transmit / receive data to / from an external computer or the like by connecting to an external network such as the Internet, a LAN, or a WAN.
- the I / O interface 14 is connected to input devices such as a keyboard 21 and a mouse 22 and receives data input.
- the video interface 15 is connected to a display device 23 such as a CRT display or a liquid crystal display, and displays a detection result on the display device 23.
- FIG. 2 is a functional block diagram of the medical image search apparatus 1 according to the embodiment of the present invention.
- a feature calculation unit 201 of the medical image search apparatus 1 calculates wavelet features of a plurality of images that have been captured and stored in the past.
- a Gabor wavelet feature is calculated as the wavelet feature.
- FIG. 3 is an explanatory diagram of the coordinate setting in the image of the medical image search apparatus 1 according to the embodiment of the present invention.
- an image composed of m pixels in the x direction and n pixels in the y direction is defined as s (x, y) with the upper left corner of the image as the origin.
- Any i (i is a natural number) represents the th coordinate of the pixel P i P i (x i, y i) and.
- the matrix A is a 3 ⁇ 3 affine transformation matrix.
- the affine transformation that moves the entire image in the x direction by tx and the ty in the y direction can be expressed by (Equation 2)
- the affine transformation that rotates the entire image by the rotation angle ⁇ can be expressed by (Equation 3).
- the two-dimensional Gabor wavelet function is defined as shown in (Formula 4) with respect to the coordinate values (x dots, y dots) after rotating affine transformation.
- the two-dimensional Gabor wavelet function is composed of a real part and an imaginary part.
- FIG. 4 is an illustration of a two-dimensional Gabor wavelet function.
- FIG. 4A shows an example of the real part of the two-dimensional Gabor wavelet function
- FIG. 4B shows an example of the imaginary part of the two-dimensional Gabor wavelet function.
- u 0 indicates the frequency of the wave shape
- ⁇ indicates the width of the hat-like width.
- r has shown the direction mentioned later.
- the window function g sigma shown in (Equation 4) is a two-dimensional Gaussian function can be expressed by (Equation 5).
- the Gabor wavelet feature for the acquired image s (x, y) can be calculated by (Equation 6).
- the lattice point having the maximum absolute value of the Gabor wavelet feature and the Gabor wavelet feature near the lattice point are invariable even when the image is subjected to affine transformation such as enlargement / reduction or rotation. Therefore, it is suitable as a feature amount of an image.
- a j and a ⁇ j indicate parameters indicating the degree of dilation (enlargement / reduction), and x 0 and y 0 indicate parallel movement. Further, r indicates a direction, and in this embodiment, Gabor wavelet features are calculated for each of the eight directions.
- FIG. 5 is a schematic diagram showing the direction of the two-dimensional Gabor wavelet function of the medical image search apparatus 1 according to the embodiment of the present invention.
- Gabor wavelet characteristics are calculated in the directions (1) to (8), that is, in eight directions rotated by 22.5 degrees from a predetermined direction.
- the Gabor wavelet feature for example, it is possible to calculate a wavelet feature amount that absorbs variation in the shape of a human organ, and therefore, a similar image can be searched with high accuracy.
- the scale is a value for distinguishing the size to be enlarged / reduced, and indicates that the scale is enlarged from 1 to 5, for example.
- Gabor wavelet features having an absolute value equal to or greater than a predetermined threshold are extracted, and Gabor wavelet features having a maximum value are selected from them.
- the absolute value of the Gabor wavelet feature is a maximum value
- the absolute value of the integral value in (Equation 6) is a maximum value, and changes the average luminance of the image, or changes the scale of the image. Even if an operation such as rotating an image is performed, the feature amount remains unchanged.
- FIG. 6 is a view showing an example of the data structure of the visual word stored in the visual word storage unit 133 of the storage device 13 of the medical image search device 1 according to the embodiment of the present invention.
- the calculated 24 Gabor wavelet features are listed and stored for each identification number 1, 2, 3,. That is, the first ‘1’ is an identification number, and the numerical values described after ‘1:’ to ‘24: ’across the blank indicate 24 calculated Gabor wavelet features.
- the example of FIG. 6 shows a visual word when three maximum values exist in one image. Therefore, in FIG. 6, visual words are stored for three identification numbers “1”, “2”, and “3”, but if the number of local maximum values is one, only the identification number “1” is stored. Needless to say.
- the keyword extracting unit 202 stores the image interpretation stored in the image interpretation information storage unit 132 of the storage device 13 corresponding to the past image stored in the medical image storage unit 131 of the storage device 13. Extract keywords included in the information. For example, when the interpretation information storage unit 132 of the storage device 13 stores “a nodular shadow is found in the upper lobe of the left lung field. Suspected squamous cell carcinoma. Is used for parsing and segmented into “part”, “symptom”, “disease name”, “treatment”, etc., and keywords are extracted.
- FIG. 7 is an exemplary diagram of keyword extraction of the medical image search apparatus 1 according to the embodiment of the present invention.
- the nodal shadow is observed in the upper lobe of the left lung field.
- the suspected squamous cell carcinoma is extracted from the keyword “nodule shadow”
- "disease name” is “suspected squamous cell carcinoma”
- “treatment” is "detailed examination by HR-CT”.
- the information storage unit 203 associates the wavelet feature calculated by the above-described method and the extracted keyword with the past image stored in the medical image storage unit 131 of the storage device 13 and the visual word storage unit 133 of the storage device 13.
- the visual word storage unit 133 of the storage device 13 Remember as a visual word.
- the image acquisition unit 204 acquires a newly captured image. At the same time, it is preferable to obtain corresponding interpretation information. This is because the images to be searched for similar images can be narrowed down.
- the wavelet feature calculation unit 205 calculates the wavelet feature of the acquired image and stores it in the visual word storage unit 133 as a visual word in the same manner as described above.
- the interpretation information search unit 206 extracts keywords included in the interpretation information of the acquired image, and searches for similar interpretation information from the keywords stored in the interpretation information storage unit 132 of the storage device 13 based on the extracted keywords. To do. Thereby, it is possible to effectively narrow down images to be searched for similar images.
- the frequency distribution vector calculation unit 209 generates a histogram indicating the frequency distribution of the converted 24-dimensional bit string values. Histograms are similarly generated not only for newly acquired images but also for all images stored in the medical image storage unit 131 or images corresponding to interpretation information retrieved by the interpretation information retrieval unit 206. To do.
- FIG. 8 is an exemplary diagram of a histogram according to the embodiment of the present invention.
- the horizontal axis takes the value of 2 24, obtains the frequency distribution of the respective values. Then, by using the frequency distribution for each image as the frequency distribution vector, it is possible to effectively narrow down images to be searched for similar images.
- Information about the generated histogram is stored in the frequency distribution information storage unit 134 of the storage device 13.
- the spatial distance calculation unit 207 calculates the spatial distance between the newly acquired image and the image stored in the medical image storage unit 131 as an angle formed between the calculated frequency distribution vectors. Specifically, when the frequency distribution vector of the newly acquired image is V1 and the frequency distribution vector of the image stored in the medical image storage unit 131 is V2, the angle ⁇ formed by the two vectors according to (Expression 7) Is calculated as cos ⁇ .
- ⁇ V1, V2> represents the inner product of the vector V1 and the vector V2, and the denominator represents the product of the norm (length) of the vector V1 and the norm of the vector V2.
- the result output unit (output unit) 208 outputs images whose calculated spatial distances are shorter than a predetermined value as search results in the order of shorter spatial distances.
- the shorter the spatial distance the higher the degree of similarity to the newly acquired image, and it is possible to select an appropriate medical practice by referring to similar past images. Is possible.
- FIG. 9 is an exemplary view of a search result display screen of the medical image search apparatus 1 according to the embodiment of the present invention.
- a past image determined to be most similar to the acquired image is displayed, and wavelet features larger than a predetermined value among the wavelet features are displayed as a feature vector superimposed on the image. is doing.
- the length of the arrow indicates the size of the feature amount, and the direction indicates the direction with the largest feature amount among the eight directions.
- the scale may be distinguished by the color, line type, or the like.
- FIG. 10 is a flowchart showing a processing procedure of the CPU 11 of the medical image search apparatus 1 according to the embodiment of the present invention.
- the CPU 11 of the medical image search apparatus 1 calculates wavelet features of a plurality of images that have been captured and stored in the past (step S1001).
- a Gabor wavelet feature is calculated as the wavelet feature.
- the CPU 11 extracts a keyword included in the interpretation information for each image of the stored past image (step S1002), and extracts the wavelet feature and extraction calculated by the method described above in association with the stored past image.
- the keyword is included in the interpretation information for each image of the stored past image.
- the CPU 11 acquires a newly captured image in association with interpretation information (step S1003), calculates the wavelet feature of the acquired image using the method described above (step S1004), and stores the visual word as a visual word. Stored in the unit 133.
- the CPU 11 extracts keywords included in the interpretation information corresponding to the acquired image (step S1005), and searches for similar interpretation information from the stored keywords based on the extracted keywords (step S1006). Thereby, it is possible to effectively narrow down images to be searched for similar images.
- the CPU11 calculates the spatial distance based on the wavelet feature between the acquired images for each of the plurality of images corresponding to the searched interpretation information (step S1007).
- the CPU 11 selects one image from a plurality of images corresponding to the searched interpretation information (step S1008), and determines whether or not the spatial distance calculated for the selected image is shorter than a predetermined value (step S1009).
- step S1009 the CPU 11 determines that the image is shorter than the predetermined value (step S1009: YES)
- the CPU 11 determines that the images are similar, and outputs the search results in the order of short spatial distance (step S1010). For example, an image is displayed and output on the display device 23.
- step S1009 NO
- the CPU 11 determines that the values are not similar and skips step S1010.
- the CPU 11 determines whether or not all images have been selected (step S1011), and if the CPU 11 determines that there is an image that has not yet been selected (step S1011: NO), the CPU 11 selects the next image. (Step S1012), the process returns to Step S1009, and the above-described process is repeated. If the CPU 11 determines that all images have been selected (step S1011: YES), the CPU 11 ends the process.
- a similar image can be searched from images stored as past cases based on the wavelet feature indicating the characteristics of the acquired medical image. Even a shallow doctor can search for an image corresponding to the most similar case and can select an appropriate medical practice.
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Abstract
Description
11 CPU
12 メモリ
13 記憶装置
14 I/Oインタフェース
15 ビデオインタフェース
16 可搬型ディスクドライブ
17 通信インタフェース
18 内部バス
90 可搬型記録媒体
100 コンピュータプログラム
131 医用画像記憶部
132 読影情報記憶部
133 ビジュアルワード記憶部
134 度数分布情報記憶部
Claims (9)
- 過去の症例に基づく医用画像の中から、新たに撮像した画像に類似する画像を検索する、医用画像を検索する装置で実行することが可能な方法であって、
過去に撮像して記憶してある複数の画像のウェーブレット特徴を算出するステップと、
記憶してある画像ごとの読影情報に含まれるキーワードを抽出するステップと、
記憶してある画像に対応付けて、算出したウェーブレット特徴及び抽出したキーワードを記憶するステップと、
新たに撮像した画像を取得するステップと、
取得した画像のウェーブレット特徴を算出するステップと、
取得した画像に対応する読影情報に含まれるキーワードを抽出し、抽出したキーワードに基づいて、記憶してあるキーワードから類似する読影情報を検索するステップと、
検索した読影情報に対応する画像と、取得した画像との間のウェーブレット特徴に基づく空間距離を算出するステップと、
算出した空間距離が所定値より短い画像を、前記空間距離が短い順に検索結果として出力するステップと
を含む方法。 - 前記ウェーブレット特徴として、2次元のガボールウェーブレット特徴を算出する請求項1に記載の方法。
- 画像ごとにM(Mは2以上の自然数)個の前記ウェーブレット特徴を算出し、それぞれ二値化することによりM次元のビット列に換算し、すべての画像について度数分布ベクトルを算出するステップを含み、
算出した度数分布ベクトル間のなす角度として前記空間距離を算出する請求項1又は2に記載の方法。 - 過去の症例に基づく医用画像の中から、新たに撮像した画像に類似する画像を検索する、医用画像を検索する装置であって、
過去に撮像して記憶してある複数の画像のウェーブレット特徴を算出する特徴算出手段と、
記憶してある画像ごとの読影情報に含まれるキーワードを抽出するキーワード抽出手段と、
記憶してある画像に対応付けて、算出したウェーブレット特徴及び抽出したキーワードを記憶する情報記憶手段と、
新たに撮像した画像を取得する画像取得手段と、
取得した画像のウェーブレット特徴を算出するウェーブレット特徴算出手段と、
取得した画像に対応する読影情報に含まれるキーワードを抽出し、抽出したキーワードに基づいて、記憶してあるキーワードから類似する読影情報を検索する読影情報検索手段と、
検索した読影情報に対応する画像と、取得した画像との間のウェーブレット特徴に基づく空間距離を算出する空間距離算出手段と、
算出した空間距離が所定値より短い画像を、前記空間距離が短い順に検索結果として出力する出力手段と
を備える装置。 - 前記特徴算出手段及び前記ウェーブレット特徴算出手段は、前記ウェーブレット特徴として、2次元のガボールウェーブレット特徴を算出する請求項4に記載の装置。
- 画像ごとにM(Mは2以上の自然数)個の前記ウェーブレット特徴を算出し、それぞれ二値化することによりM次元のビット列に換算し、すべての画像について度数分布ベクトルを算出する度数分布ベクトル算出手段を備え、
前記空間距離算出手段は、算出した度数分布ベクトル間のなす角度として前記空間距離を算出する請求項4又は5に記載の装置。 - 過去の症例に基づく医用画像の中から、新たに撮像した画像に類似する画像を検索する、医用画像を検索する装置で実行することが可能なコンピュータプログラムであって、
前記装置を、
過去に撮像して記憶してある複数の画像のウェーブレット特徴を算出する特徴算出手段、
記憶してある画像ごとの読影情報に含まれるキーワードを抽出するキーワード抽出手段、
記憶してある画像に対応付けて、算出したウェーブレット特徴及び抽出したキーワードを記憶する情報記憶手段、
新たに撮像した画像を取得する画像取得手段、
取得した画像のウェーブレット特徴を算出するウェーブレット特徴算出手段、
取得した画像に対応する読影情報に含まれるキーワードを抽出し、抽出したキーワードに基づいて、記憶してあるキーワードから類似する読影情報を検索する読影情報検索手段、
検索した読影情報に対応する画像と、取得した画像との間のウェーブレット特徴に基づく空間距離を算出する空間距離算出手段、及び
算出した空間距離が所定値より短い画像を、前記空間距離が短い順に検索結果として出力する出力手段
として機能させるコンピュータプログラム。 - 前記特徴算出手段及び前記ウェーブレット特徴算出手段を、前記ウェーブレット特徴として、2次元のガボールウェーブレット特徴を算出する手段として機能させる請求項7に記載のコンピュータプログラム。
- 前記装置を、画像ごとにM(Mは2以上の自然数)個の前記ウェーブレット特徴を算出し、それぞれ二値化することによりM次元のビット列に換算し、すべての画像について度数分布ベクトルを算出する度数分布ベクトル算出手段として機能させ、
前記空間距離算出手段を、算出した度数分布ベクトル間のなす角度として前記空間距離を算出する手段として機能させる請求項7又は8に記載のコンピュータプログラム。
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