Tencent America LLC

Shihyao Lin

Wei Fan

Yusheng Xie

Hui Tang

Lianyi Han

Chao Huang

Zhimin Huo

Kun Wang

Zhen Qian

Xiaozhong Chen

There is included an apparatus and system including image segmentation code, configured to cause at least one hardware processor to segment an image of a person's hand from an input image, and classification code configured to cause the at least one processor to classify the segmented image of the person's hand according to at least one predefined pose.

System and method for automatic recognition for hand activity defined in unified Parkinson disease rating scale

A method and apparatus include receiving a three dimensional (3D) non-contrast computed tomography (NCCT) image of a head including a hematoma. A plurality of two dimensional (2D) images of the head including the hematoma are generated using the 3D NCCT image of the head including the hematoma. A plurality of 2D hematoma images are generated using a first 2D convolutional neural network (CNN) based on the plurality of 2D images. A 3D region of interest (ROI) that encompasses the hematoma is identified based on the plurality of 2D hematoma images. A plurality of 2D images that correspond to the ROI are generated. A hematoma expansion (HE) prediction score is determined using a second CNN based on the plurality of 2D images that correspond to the ROI. The HE prediction score is provided.

Two and a half dimensional convolutional neural network for predicting hematoma expansion in non-contrast head computerized tomography images

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Shihyao Lin