Abstract: Provided are an endoscopic diagnosis support method, an endoscopic diagnosis support apparatus, and an endoscopic diagnosis support program, all of which are capable of extracting an image picking up a bleeding region easily and accurately from among a large number of endoscopic images picked up by an endoscope observation apparatus by calculating a tone from a color signal of each of plural image zones obtained by dividing the endoscopic image; and discerning an image zone including a bleeding region by judging a difference among each of the plural image zones based on a tone of the calculated each image zone in the endoscopic diagnosis support apparatus for supporting an endoscopic diagnosis performed based on an endoscopic image picked up by an endoscope observation apparatus.

Abstract: A medical image processing apparatus of the present invention includes: a three-dimensional model estimating section for estimating a three-dimensional model of an object based on a two-dimensional image of an image of the object which is inputted from a medical image pickup apparatus; an image dividing section for dividing the two-dimensional image into a plurality of regions each of which includes at least one or more pixels; a feature value calculation section for calculating a feature value according to a grayscale of each pixel in one region for each of the plurality of regions; and a lesion detection reference setting section for setting lesion detection reference for detecting a locally protruding lesion in the regions of the three-dimensional model which correspond to each of the plurality of regions, based on the feature value according to the grayscale.

Abstract: A medical image processing apparatus which performs image processing on a medical input image, includes: a pixel extraction portion for extracting an inappropriate pixel satisfying a predetermined condition in the input image, a replacing pixel information calculation portion for calculating replacing information with which pixel information of the inappropriate pixel is to be replaced, based on pixel information of a predetermined region including the extracted inappropriate pixel or adjacent to the extracted inappropriate pixel and a replaced image generation portion for replacing the pixel information of the inappropriate pixel in the input image with the replacing information and generating a replaced image.

Abstract: An image processing device includes; a lesion candidate region detecting section that detects a lesion candidate region based on at least one color signal in a medical image including a plurality of color signals; an incidental region detecting section that detects an incidental region that arises because of incidental attributes accompanying a lesion from the medical image; and a detection standard changing section that changes a detection standard when detecting a lesion from the lesion candidate region in accordance with a detection result of the incidental region.

Abstract: A CPU executes a gray value gradient calculation process to, for example, an R signal in step S10, executes an isotropic change feature value calculation process based on a gray value gradient calculated in step S11, and further executes a possible polyp detection process for generating a possible polyp image at a location where a polyp exists based on an isotropic change feature value calculated in step S12. This improves the detection of an existing location of an intraluminal abnormal tissue.

Abstract: A CPU implements a possible polyp detection process of step S4 to execute processing for each label value of a thinned image and superimpose a processing result on a possible polyp image, thereby generating a possible polyp labeling image in which a possible polyp edge is labeled. The possible polyp labeling image, in which the possible polyp image is superimposed on an original image, is displayed on a display device so that a possible polyp location on the image can be easily checked, thereby improving the detection accuracy of an intraluminal abnormal tissue.

Abstract: A hemorrhage edge candidate area extraction section extracts a candidate area for the outline part of a hemorrhage area, based on an image signal of a medical image constituted by multiple color signals obtained by capturing an image of a living body. A feature quantity calculation section calculates a feature quantity of the hemorrhage area based on calculation of the amount of change in the image signal in a small area including the candidate area, among multiple small areas obtained by dividing the medical image. A hemorrhage edge determination section determines whether or not the candidate areas are the outline part of the hemorrhage area based on the feature quantity.

Abstract: An image processing apparatus includes: a surface model generation section for performing processing for generating a three-dimensional surface model from a two-dimensional medical image; and an area reliability calculation section for dividing the surface model into multiple areas and calculating the reliability of data in each of the multiple areas.

Abstract: A medical image processing apparatus of the present invention has a three-dimensional model estimating section for estimating, based on an inputted two-dimensional image of an image of a living tissue within a body cavity, a three-dimensional model of the living tissue, a shape feature value calculating section for calculating shape feature values of respective voxels included in the three-dimensional model of the living tissue, a three-dimensional shape extracting section for extracting a first voxel group whose three-dimensional model has been estimated as a predetermined shape, in the respective voxels included in the three-dimensional model of the living tissue, based on the shape feature values, and a protruding shape detecting section for detecting the first voxel group as a voxel group configuring a protruding shape in the three-dimensional model of the living tissue.

Abstract: Main parts of an endoscope system of the present invention include a medical observation apparatus, a medical image processing apparatus, and a monitor. A CPU of the medical image processing apparatus is constituted by function units including a three-dimensional model estimating unit, a detection target area setting unit, a shape feature value calculating unit, a three-dimensional shape detecting unit, a threshold determining unit, and a polyp determining unit. Such a configuration enables to execute a process appropriately adapted to an observation state of a targeted two-dimensional image and to improve the detection accuracy in the detection of a lesion with locally elevated shape as compared to the past.

Abstract: A medical image processing device of the present invention has an image dividing unit which divides an image into a plurality of regions, a feature value calculating unit which calculates a color tone feature value which is a feature value based on a color tone of the image in each of the plurality of regions, a first color tone reference value calculating unit which calculates a color tone reference value based on the color tone feature value which each of the plurality of regions has, a lesion detection reference calculating unit which properly calculates a lesion detection reference for detecting a lesion finding in accordance with the color tone reference value, and an image region detecting unit which detects a region in which an image of the lesion finding is picked up among the respective plurality of regions, based on the lesion detection reference and the color tone feature value which each of the plurality of regions has.

Abstract: A medical image processing method for image processing of a medical image picking up an image of a living mucous comprises a boundary information detecting step for detecting boundary information corresponding to a boundary portion of a living mucous from the medical image and a mucous feature detecting step for detecting presence of a living mucous with a different feature on the basis of the boundary information detected at the boundary information detecting step.

Abstract: A medical image processing apparatus of the present invention includes an edge extracting section that extracts edges of an inputted two-dimensional image, a three-dimensional-model estimating section that estimates a three-dimensional model on the basis of the two-dimensional image, a voxel extracting section that extracts, on the basis of positions of respective voxels, where the edges are present, a predetermined voxel group to be set as a calculation object of a shape feature value, a shape-feature-value calculating section that calculates the shape feature value for at least a part of voxels among the predetermined voxel group, a three-dimensional-shape extracting section that extracts a voxel group, a three-dimensional model of which is estimated as a predetermined shape, on the basis of the shape feature value, and a tuberal-shape detecting section that detects the voxel group as a voxel group forming a tuberal shape in the three-dimensional model of the living tissue.

Abstract: There is provided a medical image processing apparatus including an image-extracting section extracting a frame image from in vivo motion picture data picked up by an in vivo image pickup device or a plurality of consecutively picked-up still image data, and an image analysis section analyzing the frame image extracted by the image-extracting section to output an image analysis result. The image analysis section includes a first biological-feature detection section detecting a first biological feature, a second biological-feature detection section detecting, based on a detection result obtained by the first biological feature detection section, a second biological feature in a frame image picked up temporally before or after the image used for detection by the first biological feature detection section; and a condition determination section making a determination for a biological condition based on a detection result obtained by the second biological feature detection section to output the determination.

Abstract: A signal processing circuit of an external device includes a CPU and a memory which are not shown. A program for estimating at least one of the position and orientation of a capsule endoscope on the basis of strength signals received through respective antennas is installed in the signal processing circuit. A single-core coil to generate a magnetic field is arranged in the capsule endoscope. The generated magnetic field is detected by a plurality of coils arranged outside a body, whereby a distance that the capsule endoscope has traveled can be obtained with accuracy. This arrangement controls image-capture timing to reliably capture images necessary for a diagnosis and prevent unnecessary image capture.

Abstract: A signal processing circuit of an external device includes a CPU and a memory which are not shown. A program for estimating at least one of the position and orientation of a capsule endoscope on the basis of strength signals received through respective antennas is installed in the signal processing circuit. A single-core coil to generate a magnetic field is arranged in the capsule endoscope. The generated magnetic field is detected by a plurality of coils arranged outside a body, whereby a distance that the capsule endoscope has traveled can be obtained with accuracy. This arrangement controls image-capture timing to reliably capture images necessary for a diagnosis and prevent unnecessary image capture.

Abstract: A signal processing circuit of an external device includes a CPU and a memory which are not shown. A program for estimating at least one of the position and orientation of a capsule endoscope on the basis of strength signals received through respective antennas is installed in the signal processing circuit. A single-core coil to generate a magnetic field is arranged in the capsule endoscope. The generated magnetic field is detected by a plurality of coils arranged outside a body, whereby a distance that the capsule endoscope has traveled can be obtained with accuracy. This arrangement controls image-capture timing to reliably capture images necessary for a diagnosis and prevent unnecessary image capture.

Abstract: There is provided a medical image processing apparatus including an image-extracting section extracting a frame image from in vivo motion picture data picked up by an in vivo image pickup device or a plurality of consecutively picked-up still image data, and an image analysis section analyzing the frame image extracted by the image-extracting section to output an image analysis result. The image analysis section includes a first biological-feature detection section detecting a first biological feature, a second biological-feature detection section detecting, based on a detection result obtained by the first biological feature detection section, a second biological feature in a frame image picked up temporally before or after the image used for detection by the first biological feature detection section; and a condition determination section making a determination for a biological condition based on a detection result obtained by the second biological feature detection section to output the determination.

Abstract: A signal processing circuit of an external device includes a CPU and a memory which are not shown. A program for estimating at least one of the position and orientation of a capsule endoscope on the basis of strength signals received through respective antennas is installed in the signal processing circuit. A single-core coil to generate a magnetic field is arranged in the capsule endoscope. The generated magnetic field is detected by a plurality of coils arranged outside a body, whereby a distance that the capsule endoscope has traveled can be obtained with accuracy. This arrangement controls image-capture timing to reliably capture images necessary for a diagnosis and prevent unnecessary image capture.

Abstract: A hemorrhage edge candidate area extraction section extracts a candidate area for the outline part of a hemorrhage area, based on an image signal of a medical image constituted by multiple color signals obtained by capturing an image of a living body. A feature quantity calculation section calculates a feature quantity of the hemorrhage area based on calculation of the amount of change in the image signal in a small area including the candidate area, among multiple small areas obtained by dividing the medical image. A hemorrhage edge determination section determines whether or not the candidate areas are the outline part of the hemorrhage area based on the feature quantity.