Tencent America LLC

Lianyi Han

Wei Fan

Hui Tang

Yusheng Xie

Shih-Yao Lin

Chao Huang

Kun Wang

Zhimin Huo

Min Tu

Tao Yang

Zhen Qian

Shangqing Zhang

Qian Zhen

Yaliang Li

Nan Du

Xiaozhong Chen

Xu Wang

Zeyu You

Shihyao Lin

Yufan Xue

A method, computer program, and computer system are provided for image segmentation. Image data, such as biological image data, is received. One or more objects associated with the received image data is detected. One or more regions of interest are determined within the receive image data corresponding to one or more segments based on the detected objects.

System and method for instance segmentation in pathological images using object-guided framework

A method, computer program, and computer system is provided for query matching of sentences based on co-attention scores. Two or more query inputs to a neural network are received. A correlation factor between the two or more query input is identified based on attention weights. A feature vector is generated based on the attention weights. A probability value corresponding to the two or more query inputs is determined based on the generated feature vector.

Efficient and compact text matching system for sentence pairs

A method and user device for determining a unified Parkinson's disease rating scale (UPDRS) value associated with a user of the user device include obtaining video data associated with a movement of a body part of the user. The UPDRS value is determined using a model and the video data associated with the movement of the body part of the user. The UPDRS value is provided to permit an evaluation of the user based on the UPDRS value.

User device based Parkinson's disease detection

Systems and methods for obtaining hand images are provided. A method, performed by at least one processor that implements at least one network, includes obtaining a single source image, a three-dimensional (3D) hand pose of a first hand in the single source image, and a 3D target hand pose; and generating an image of a second hand, that has an appearance of the first hand and a pose of the 3D target hand pose, based on the single source image, the 3D hand pose, and the 3D target hand pose.

Synthesizing 3D hand pose based on multi-modal guided generative networks

A method and device for generating a three dimensional (3D) bounding box of a region of interest (ROI) of a patient include receiving a two dimensional (2D) maximum intensity projection (MIP) image that is an axial view of the patient and a 2D MIP image that is a sagittal view of the patient. A first 2D bounding box of the ROI of the patient and a second 2D bounding box of the ROI of the patient are detected using the 2D MIP images. A 3D MIP image of the patient is received, and the 3D bounding box of the ROI of the patient is generated using the 3D MIP image, the first 2D bounding box, and the second 2D bounding box. The 3D MIP image including the 3D bounding box is provided.

System and method for identifying target regions prior to organs at risk segmentation

A method and user device for providing a unified Parkinson's disease rating scale (UPDRS) value by a user device includes generating, by a sensor of the user device, sensor data based on a user of the user device manipulating the user device. The UPDRS value is determined based on the sensor data and a deep neural network (DNN) model. The UPDRS value is provided to permit an evaluation of the user based on the UPDRS value.

User device based parkinson disease detection

A method, computer program, and computer system is provided for text error identification and correction. A text input having a phonetic component and a glyphic component is received. Information corresponding to the phonetic component and the glyphic component is coded as a fixed-length sequence. One or more candidate replacement words corresponding to the fixed-length sequence are identified. At least a portion of the text input is replaced with a candidate replacement word from among the one or more candidate replacement words.

Framework for chinese text error identification and correction

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

There is included an apparatus and system including video capture code configured to control a camera of a mobile phone to capture a video of at least a portion of skin, extraction code configured to extract at least one photoplethysmogram (PPG) signal from the video, determination code configured to determine a peripheral oxygen saturation (SpO2) value based on the PPG signal with respect to a blood flow at the portion of skin, and display code configured to control a display of the mobile phone to display the SpO2 value.

SpO2 miniprogram: AI SpO2 measurement app

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

There is included an apparatus and system including an intra-heartbeat (HB) extraction code configured to extract intra-HB features from electrocardiography (ECG) signals, and an inter-HB extraction code configured to extract inter-HB features from the ECG signals, and at least one attention mechanism code configured to control at least one of the intra-HB extraction code and inter-HB extraction code based on at least one attention mechanism.

Explainable artificial intelligence framework for electrocardiography analysis

A method and apparatus include receiving a first sentence including a first set of words, and a second sentence including a second set of words. A first set of vectors corresponding to the first set of words of the first sentence, and a second set of vectors corresponding to the second set of words of the second sentence are generated using a word embedding model. A similarity matrix based on the first set of vectors and the second set of vectors is generated. An alignment score associated with the first set of vectors and the second set of vectors is determined using the similarity matrix. The alignment score is transmitted to permit information retrieval based on a similarity between the first sentence and the second sentence.

Proximity information retrieval boost method for medical knowledge question answering systems

A method, computer program, and computer system is provided for estimating three-dimensional hand poses in images. Data corresponding to two hand images is receive, and an optical flow value corresponding to a change in a hand gesture in the received hand image data is calculate. A heat map is generated based on the calculated optical flow, and a hand mesh map is estimated based on the generated heat map. A hand pose present within the hand images is determined based on the estimated hand mesh map.

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Palo Alto, CA, United States of America

Lianyi Han