Abstract: Provided are a display processing apparatus, method, and program for displaying a region of a detection target object in an image in a manner intelligible to a user even if the contour or boundary of the detection target object is unclear. A transmitting/receiving unit (100) and an image generation unit (102), which function as an image acquisition unit, perform an image acquisition process for sequentially acquiring ultrasound images. A region extraction unit (106) extracts a rectangular region including an organ, which is a detection target object, from an acquired ultrasound image. A curve generation unit (108) generates, in the extracted rectangular region, a curve corresponding to the organ in the rectangular region. An image combining unit (109) combines the ultrasound image and the generated curve corresponding to the organ. A display control unit (110) causes a monitor (18) to display the ultrasound image combined with the curve.

Abstract: There are provided an ultrasound diagnostic apparatus and a control method of the ultrasound diagnostic apparatus which allow a user to accurately perform a diagnosis for a lesion part.

Abstract: An ultrasound diagnostic apparatus 1 includes an image acquisition unit 17 that acquires an ultrasound image of a subject a bladder extraction unit 18 that extracts a bladder from the ultrasound image; a prostate extraction unit 19 that extracts a prostate or cervix from the ultrasound image from which the bladder is extracted; a region-of-interest setting unit 20 that sets a region of interest at a depth position in the ultrasound image based on a position of the extracted prostate or cervix in a case where the prostate or cervix is extracted and that sets a region of interest at a depth position in the ultrasound image based on a position of the extracted bladder in a case where the prostate or cervix is not extracted; and an image quality adjustment unit 21 that adjusts the transmission/reception condition according to the depth position of the region of interest.

Abstract: An ultrasound diagnostic apparatus 1 includes a bladder pattern storage unit 22, a reference pattern setting unit 21, a bladder extraction unit 18 that extracts a bladder region from an ultrasound image, a bladder extraction success/failure determination unit 19 that determines whether the bladder region represents a bladder having the reference pattern, and an image quality adjustment unit 20 that adjusts the image quality of the ultrasound image in a case where determination is made that the bladder region does not represent the bladder having the reference pattern, in which in a case where the determination is made that the bladder region does not represent the bladder having the reference pattern even in an ultrasound image of which the image quality is adjusted, the bladder extraction success/failure determination unit 19 determines whether the bladder region represents the bladder having the abnormal bladder pattern.

Abstract: A training data creation apparatus, method, and program that can create training data for training a region extractor with the expected performance in a situation in which a plurality of ground-truth region masks have been assigned to a single image, a machine learning apparatus and method, a learning model, and an image processing apparatus are provided. A training data creation apparatus includes a first processor, in which a training sample acquisition unit of first processor acquires a single image and a plurality of first ground-truth region masks for the single image from a database as a single training sample. A ground-truth region mask combination unit generates a single second ground-truth region mask from the first ground-truth region masks included in the training sample. An output unit outputs, as training data, the pair of the single image included in the training sample and the combined second ground-truth region mask.

Abstract: There are provided an image processing device, an image processing method, and a program that can efficiently obtain learning data allowing effective machine learning to be expected. An image processing device includes a processor and a plurality of recognizers, and the processor acquires a video acquired by a medical apparatus, causes the plurality of recognizers to perform processing for recognizing a lesion in image frames forming the video to acquire a recognition result of each of the plurality of recognizers, and determines whether or not to use the image frame as learning data to be used for machine learning on the basis of the recognition result of each of the plurality of recognizers.

Abstract: There are provided an image processing device, an image processing method, and a program that can accurately select normal images suitable for learning without visually selecting learning data by a human. An image processing device includes a processor, and the processor acquires an examination video picked up by an endoscope apparatus, acquires instructional information of the endoscope apparatus in the pickup of the examination video, specifies a learning frame section from a plurality of frames forming the examination video on the basis of the instructional information, and outputs a frame group of the learning frame section as first learning data.

Abstract: There are provided an image evaluation apparatus, an image evaluation method, and an image evaluation program capable of highly evaluating an image having an impression of a user's preference. A plurality of images included in a first image group are input to an image evaluation apparatus (step 21). A plurality of representative image candidates are displayed (step 22), and the user selects a desired representative image from the representative image candidates (step 23). The difference between the impression value of the representative image and the impression value of the input image is calculated (step 24), and the image quality of the input image is determined (step 25). An image evaluation value is calculated so as to become higher as the difference between the impression values becomes smaller and the image quality becomes higher (step 26).

Abstract: An ultrasound diagnostic apparatus 1 includes an ultrasound probe 2; an image acquisition unit 17 that acquires an ultrasound image of a subject by performing transmission and reception of an ultrasound beam to and from the ultrasound probe 2 in accordance with a predetermined transmission/reception condition; a display unit 16 that displays the ultrasound image acquired by the image acquisition unit 17; a constipation evaluation unit 18 that performs constipation evaluation based on the ultrasound image acquired by the image acquisition unit 17; and a urine volume measurement availability determination unit 21 that determines whether or not urine volume measurement is available, from the ultrasound image acquired by the image acquisition unit 17 in accordance with the transmission/reception condition which is used to perform the constipation evaluation by the constipation evaluation unit 18.

Abstract: An ultrasound diagnostic apparatus 1 includes a bladder pattern storage unit 22, a reference pattern setting unit 21, a bladder extraction unit 18 that extracts a bladder region from an ultrasound image, a bladder extraction success/failure determination unit 19 that determines whether the bladder region represents a bladder having the reference pattern, and an image quality adjustment unit 20 that adjusts the image quality of the ultrasound image in a case where determination is made that the bladder region does not represent the bladder having the reference pattern, in which in a case where the determination is made that the bladder region does not represent the bladder having the reference pattern even in an ultrasound image of which the image quality is adjusted, the bladder extraction success/failure determination unit 19 determines whether the bladder region represents the bladder having the abnormal bladder pattern.

Abstract: An ultrasound diagnostic apparatus 1 includes an image acquisition unit 17 that acquires an ultrasound image of a subject a bladder extraction unit 18 that extracts a bladder from the ultrasound image; a prostate extraction unit 19 that extracts a prostate or cervix from the ultrasound image from which the bladder is extracted; a region-of-interest setting unit 20 that sets a region of interest at a depth position in the ultrasound image based on a position of the extracted prostate or cervix in a case where the prostate or cervix is extracted and that sets a region of interest at a depth position in the ultrasound image based on a position of the extracted bladder in a case where the prostate or cervix is not extracted; and an image quality adjustment unit 21 that adjusts the transmission/reception condition according to the depth position of the region of interest.

Abstract: There are provided an image evaluation apparatus, an image evaluation method, and an image evaluation program capable of highly evaluating an image having an impression of a user's preference. A plurality of images included in a first image group are input to an image evaluation apparatus (step 21). A plurality of representative image candidates are displayed (step 22), and the user selects a desired representative image from the representative image candidates (step 23). The difference between the impression value of the representative image and the impression value of the input image is calculated (step 24), and the image quality of the input image is determined (step 25). An image evaluation value is calculated so as to become higher as the difference between the impression values becomes smaller and the image quality becomes higher (step 26).

Abstract: There are provided an image extraction system, an image extraction method, and an image extraction program for extracting images valuable to a user and a recording medium storing the program. An image set including three or more images is classified into a plurality of clusters, and an annotation indicating a subject or a scene of each image is acquired from a plurality of images included in each cluster. Image co-occurrence probabilities in a plurality of images are calculated from the acquired annotations, and an image with an image co-occurrence probability equal to or less than a threshold value is extracted.

Abstract: There are provided an image extraction system, an image extraction method, and an image extraction program for extracting images valuable to a user and a recording medium storing the program. An image set including three or more images is classified into a plurality of clusters, and an annotation indicating a subject or a scene of each image is acquired from a plurality of images included in each cluster. Image co-occurrence probabilities in a plurality of images are calculated from the acquired annotations, and an image with an image co-occurrence probability equal to or less than a threshold value is extracted.