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Image processing device, image processing method, and image processing program

An image processing device and an image-in-image technology, which are applied in image data processing, image data processing, image enhancement, etc., can solve problems such as inability to accurately distinguish fine structures, inability to calculate feature quantities, poor resolution, etc.

Active Publication Date: 2015-02-18
OLYMPUS CORP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Therefore, as in the prior art, even if the feature quantity based on the spatial frequency is calculated for the entire image in which the foreground part and the foreground part are mixed, due to the influence of the resolution difference, it is impossible to calculate an appropriate feature quantity, and there is a possibility that it cannot be accurately The problem of distinguishing whether the fine structure is normal or abnormal

Method used

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  • Image processing device, image processing method, and image processing program
  • Image processing device, image processing method, and image processing program
  • Image processing device, image processing method, and image processing program

Examples

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no. 1 Embodiment approach

[0053] figure 1 It is a block diagram showing the configuration of the image processing device according to the first embodiment of the present invention. The image processing device 1 of the first embodiment is, for example, a device for imaging the inside of a living body's lumen with an endoscope or a capsule endoscope (hereinafter, they are collectively referred to simply as an endoscope). On the other hand, the acquired intraluminal image (hereinafter, may be simply referred to as image) is subjected to image processing for identifying abnormalities in the microstructure of the mucosal surface. The intraluminal image usually has a color with predetermined (for example, 256 gradation) pixel levels (pixel values) for R (red), G (green), and B (blue) wavelength components (color components) at each pixel position. image.

[0054] Such as figure 1 As shown, the image processing device 1 has a control unit 10 for controlling the overall operation of the image processing dev...

Deformed example 1-1

[0093] Next, Modification 1-1 of the first embodiment will be described.

[0094] Figure 8 It is a block diagram showing the configuration of the computing unit included in the image processing device according to Modification 1-1. Such as Figure 8 As shown, the calculating unit 100 - 1 of the modification 1-1 includes an imaging distance estimating unit 110 , an inspection region setting unit 140 , and an abnormal structure identifying unit 150 . In addition, the configuration and operation of the imaging distance estimation unit 110 are the same as those of the first embodiment. In addition, the overall structure and operation of the image processing device other than the computing unit 100-1 are also the same as those of the first embodiment.

[0095] The inspection region setting unit 140 has a candidate region setting unit 141 and a region specifying unit 142 . Among them, the candidate area setting unit 141 has a representative imaging distance acquisition unit 141...

Deformed example 1-2

[0112] Next, Modification 1-2 of the first embodiment will be described.

[0113] Figure 12 It is a block diagram showing the configuration of the computing unit included in the image processing device of Modification 1-2. Such as Figure 12 As shown, the computing unit 100 - 2 of Modification 1-2 includes an imaging distance estimating unit 110 , an inspection region setting unit 160 , and an abnormal structure identifying unit 170 . In addition, the configuration and operation of the imaging distance estimation unit 110 are the same as those of the first embodiment. In addition, the overall configuration and operation of the image processing device other than the calculation unit 100-2 are also the same as those of the first embodiment.

[0114] The inspection region setting unit 160 has a candidate region setting unit 161 and a region specifying unit 142 . The candidate region setting unit 161 has a representative imaging distance gradient calculation unit 161a that ca...

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Abstract

Provided are an image processing device and other devices capable of accurately identifying an abnormality of the microscopic structure of a subject even when the difference in resolution occurs in the microscopic structure of the subject due to the difference in image capturing distance. The image processing device (1) comprises: an image capturing distance estimation unit (110) for estimating an image capturing distance to a subject to be image-captured in an image; an inspection region setting unit (120) for setting an inspection region to be within said image so that an indicator becomes within a predetermined range, the indicator indicating the broadening of the distribution of the image capturing distance of the subject to be image-captured in the inspection region; and an abnormal structure identifying unit (130) for identifying whether the microscopic structure of the subject to be image-captured in the inspection region is abnormal or not, by using a texture feature amount by which an abnormality of the microscopic structure of the subject to be image-captured in the inspection region can be identified, said abnormality being specified according to the inspection region.

Description

technical field [0001] The present invention relates to an image processing device, an image processing method, and an image processing program for discriminating an abnormal region from an image obtained by imaging the inside of a lumen of a living body. Background technique [0002] As image processing performed on an image obtained by imaging the lumen of a living body (hereinafter referred to as an endoscopic image or an intraluminal image or simply an image) by a medical observation device such as an endoscope or a capsule endoscope, for example, Patent Document 1 discloses a technique for detecting an abnormal part in an image based on a fine structure of a mucosal surface or a blood vessel progression. In this technique, after extracting an image composed of a G (green) component containing a large amount of information on the fine structure of the mucosa and blood vessel images from the endoscopic image, the pixel value pattern of the surface of the mucosa is calcula...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): A61B1/00A61B1/04G06T1/00
CPCA61B1/0676A61B1/00009G06T2207/10068G06T2207/30101G06T2207/10024G06T7/0012G06T2207/30028A61B1/000094G06T7/40
Inventor 神田大和北村诚河野隆志弘田昌士上山都士也
Owner OLYMPUS CORP
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