Konica Minolta, Inc.

Konica Minolta Medical and Graphic, Inc.

Icad, Inc.

Satoshi Kasai

Akinori Tsunomori

Hitoshi Futamura

Koichi Fujiwara

Sho Noji

Shinsuke Katsuhara

Hiroaki Matsumoto

David S Harding

Jeffrey C Wehnes

James H Pike

Tsuyoshi Kobayashi

Muhammad Sabir

Sridharan Kamalakanan

An information processing device includes: a plurality of identifiers that discriminates whether abnormal data that is information indicating an abnormal value is included in treatment data and detects the abnormal data; and a hardware processor that: customizes evaluation data used when evaluating discrimination accuracy of the plurality of identifiers; calculates the discrimination accuracy of each of the plurality of identifiers using the evaluation data customized by the hardware processor; and selects one identifier out of the plurality of identifiers as an identifier used for discrimination based on a calculation result by the hardware processor.

Information processing device and information processing method

A dynamic image processing apparatus includes a hardware processor. The hardware processor extracts (i) a region of interest and/or (ii) a frame image of interest from a series of frame images obtained by dynamic imaging of a subject. Further, the hardware processor stores, of the series of the frame images, only (i) the extracted region of interest, (ii) the extracted frame image of interest or (iii) the extracted region of interest in the extracted frame image of interest in a storage.

Dynamic image processing apparatus

Lung segmentation and bone suppression techniques are helpful pre-processing steps prior to radiographic analyzes of the human thorax, as may occur during cancer screenings and other medical examinations. Autonomous lung segmentation may remove spurious boundary pixels from a radiographic image, as well as identify and refine lung boundaries. Thereafter, autonomous bone suppression may identify clavicle, posterior rib, and anterior rib bones using various image processing techniques, including warping and edge detection. The identified clavicle, posterior rib, and anterior rib bones may then be suppressed from the radiographic image to yield a segmented, bone suppressed radiographic image.

Lung segmentation and bone suppression techniques for radiographic images

A dynamic analysis apparatus may include a setting section which sets a target region in a lung region of a chest dynamic image; a conversion section which calculates a representative value of a pixel signal value in the target region, and converts the pixel signal value; an extraction section which extracts a pulmonary blood flow signal from the image; and a calculation section which calculates a change in the pulmonary blood flow signal, and calculates a feature amount regarding pulmonary blood flow. The setting section may determine a size of the target region based on a size of a body part other than a lung blood vessel, a movement amount of a body part other than the lung blood vessel or subject information of the chest dynamic image, the subject information regarding a subject of the radiation imaging, and the setting section may set the target region.

Dynamic analysis apparatus and dynamic analysis system

A dynamic analysis system includes a comparing unit and a display unit. The comparing unit extracts a lung field from each of dynamic images obtained by imaging a chest part containing a left lung and a right lung of a subject, specifies a corresponding point in a left part and a corresponding point in a right part of the lung field, and compares characteristic amounts at the respective corresponding points with each other. The display unit displays a result of the comparison made by the comparing unit together with the dynamic images or one of the dynamic images, or displays the result on the dynamic images or the one of the dynamic images.

Dynamic analysis system

A medical image processing apparatus includes: an abnormal shadow candidate detecting section for detecting an abnormal shadow candidate from a medical image in which a subject image is generated, with a judging logic which performs judgment with training data; a training data storing section for storing the training data used at a detection of the abnormal shadow candidate, so as to make the training data updatable; a displaying section for displaying the medical image and a detection result; an area designating section for designating an area to be registered as the training data on the medical image displayed on the displaying section; a data controlling section for having an image of the designated area stored in the training data storing section; and a logic correcting section for correcting the judging logic of the abnormal shadow candidate detecting section, based on the training data stored in the training data storing section.

Medical image processing apparatus and medical image processing system

A medical image processing apparatus includes: an abnormal shadow candidate detecting section for detecting a plurality of types of abnormal shadow candidates in a medical image; and a correcting section for correcting a detection result of one type of abnormal shadow candidate by the abnormal shadow candidate detecting section based on a detection result of another type of abnormal shadow candidate.

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Hachioji, Japan

Satoshi Kasai