290 citations · 386 across the 10 of their papers we have counts for
10 papers
A Transformer-based representation-learning model with unified processing of multimodal input for clinical diagnostics
Hong-Yu Zhou, Yizhou Yu, Chengdi Wang +7
During the diagnostic process, clinicians leverage multimodal information, such as chief complaints, medical images, and laboratory-test results. Deep-learning models for aiding di…
UNet-2022: Exploring Dynamics in Non-isomorphic Architecture
Jiansen Guo, Hong-Yu Zhou, Liansheng Wang +1
Recent medical image segmentation models are mostly hybrid, which integrate self-attention and convolution layers into the non-isomorphic architecture. However, one potential drawb…
Diagnose Like a Radiologist: Hybrid Neuro-Probabilistic Reasoning for Attribute-Based Medical Image Diagnosis
Gangming Zhao, Quanlong Feng, Chaoqi Chen +2
During clinical practice, radiologists often use attributes, e.g. morphological and appearance characteristics of a lesion, to aid disease diagnosis. Effectively modeling attribute…
Computer-aided Tuberculosis Diagnosis with Attribute Reasoning Assistance
Chengwei Pan, Gangming Zhao, Junjie Fang +6
Although deep learning algorithms have been intensively developed for computer-aided tuberculosis diagnosis (CTD), they mainly depend on carefully annotated datasets, leading to mu…
Domain Invariant Model with Graph Convolutional Network for Mammogram Classification
Churan Wang, Jing Li, Xinwei Sun +3
Due to its safety-critical property, the image-based diagnosis is desired to achieve robustness on out-of-distribution (OOD) samples. A natural way towards this goal is capturing o…
Harmonizing Pathological and Normal Pixels for Pseudo-healthy Synthesis
Yunlong Zhang, Xin Lin, Yihong Zhuang +6
Synthesizing a subject-specific pathology-free image from a pathological image is valuable for algorithm development and clinical practice. In recent years, several approaches base…
Cross-Modality Deep Feature Learning for Brain Tumor Segmentation
Dingwen Zhang, Guohai Huang, Qiang Zhang +3
Recent advances in machine learning and prevalence of digital medical images have opened up an opportunity to address the challenging brain tumor segmentation (BTS) task by using d…
Symmetry-Enhanced Attention Network for Acute Ischemic Infarct Segmentation with Non-Contrast CT Images
Kongming Liang, Kai Han, Xiuli Li +4
Quantitative estimation of the acute ischemic infarct is crucial to improve neurological outcomes of the patients with stroke symptoms. Since the density of lesions is subtle and c…
Identification of Pediatric Respiratory Diseases Using Fine-grained Diagnosis System
Gang Yu, Zhongzhi Yu, Yemin Shi +7
Respiratory diseases, including asthma, bronchitis, pneumonia, and upper respiratory tract infection (RTI), are among the most common diseases in clinics. The similarities among th…
EdgeStereo: An Effective Multi-Task Learning Network for Stereo Matching and Edge Detection
Xiao Song, Xu Zhao, Liangji Fang +1
Recently, leveraging on the development of end-to-end convolutional neural networks (CNNs), deep stereo matching networks have achieved remarkable performance far exceeding traditi…