most citedUnifying Neural Learning and Symbolic Reasoning for Spinal Medical Report Generation

5 citations · 12 across the 3 of their papers we have counts for

collaborators

5 papers

cs.CV20203 cited

Deep Complementary Joint Model for Complex Scene Registration and Few-shot Segmentation on Medical Images

Yuting He, Tiantian Li, Guanyu Yang +6

Deep learning-based medical image registration and segmentation joint models utilize the complementarity (augmentation data or weakly supervised data from registration, region cons…

physics.med-ph20204 cited

Dual-energy CT imaging from single-energy CT data with material decomposition convolutional neural network

Tianling Lyu, Zhan Wu, Yikun Zhang +3

Dual-energy computed tomography (DECT) is of great significance for clinical practice due to its huge potential to provide material-specific information. However, DECT scanners are…

cs.CV20205 cited

Unifying Neural Learning and Symbolic Reasoning for Spinal Medical Report Generation

Zhongyi Han, Benzheng Wei, Yilong Yin +1

Automated medical report generation in spine radiology, i.e., given spinal medical images and directly create radiologist-level diagnosis reports to support clinical decision makin…

eess.IV2019

Recurrent Aggregation Learning for Multi-View Echocardiographic Sequences Segmentation

Ming Li, Weiwei Zhang, Guang Yang +5

Multi-view echocardiographic sequences segmentation is crucial for clinical diagnosis. However, this task is challenging due to limited labeled data, huge noise, and large gaps acr…

eess.IV2019

Direct Quantification for Coronary Artery Stenosis Using Multiview Learning

Dong Zhang, Guang Yang, Shu Zhao +3

The quantification of the coronary artery stenosis is of significant clinical importance in coronary artery disease diagnosis and intervention treatment. It aims to quantify the mo…