Canon Medical Systems Corporation

Microsoft Technology Licensing, LLC

Yijin Wang

Hong-Jiang Zhang

Lin Li

Dong Zhang

Yu Guo

Naoki Yamashita

Xieping Xu

Qingyu Yan

Bing Lan

Yongjun Ma

Qichen Zhu

Chen Wu

A radiation exposure dose management apparatus according to an embodiment is a radiation exposure dose management apparatus that manages a radiation dose received by a subject and includes processing circuitry configured: to obtain image data of the subject; to segment the image data in accordance with organs of the subject; to generate a voxel radiation dose distribution map indicating a radiation exposure dose of each of the voxels on the basis of a specific radiation exposure dose model and the image data; and to calculate a radiation exposure dose of each of the organs on the basis of the segmented image data and the radiation exposure dose of each of the voxels within the generated voxel radiation dose distribution map.

Radiation exposure dose management apparatus, radiation exposure dose management method, and storage medium

An imaging planning apparatus according to one embodiment includes processing circuitry. The processing circuitry obtains a first value of a first index that is related to an X-ray dose and a second value of a second index that is related to an image quality, based on an X-ray imaging condition of a subject set in a predetermined examination. The processing circuitry displays an association chart indicating an association between the first index and the second index on a display unit, displays an acceptable range of the first index and the second index, the acceptable range being based on information related to a diagnostic reference level corresponding to the predetermined examination, in a manner distinguished from a range other than the acceptable range in the association chart, and also displays a mark at a position corresponding to the first value and the second value in the association chart.

Imaging planning apparatus and imaging planning method

An algorithm identifies a salient video frame from a video sequence for use as a video thumbnail. The identification of a video thumbnail is based on a frame goodness measure. The algorithm calculates a color histogram of a frame, and then calculates the entropy and standard deviation of the color histogram. The frame goodness measure is a weighted combination of the entropy and the standard deviation. A video frame having the highest value of frame goodness measure for a video sequence is determined as the video thumbnail for a video sequence.

Generating visually representative video thumbnails

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Beijing, China

Yijin Wang