1.1k citations · 2k across the 46 of their papers we have counts for
9 papers · 1 filter
CT Film Recovery via Disentangling Geometric Deformation and Illumination Variation: Simulated Datasets and Deep Models
Quan Quan, Qiyuan Wang, Liu Li +2
While medical images such as computed tomography (CT) are stored in DICOM format in hospital PACS, it is still quite routine in many countries to print a film as a transferable med…
A Hierarchical Feature Constraint to Camouflage Medical Adversarial Attacks
Qingsong Yao, Zecheng He, Yi Lin +3
Deep neural networks (DNNs) for medical images are extremely vulnerable to adversarial examples (AEs), which poses security concerns on clinical decision making. Luckily, medical A…
Aggregative Self-Supervised Feature Learning from a Limited Sample
Jiuwen Zhu, Yuexiang Li, S. Kevin Zhou
Self-supervised learning (SSL) is an efficient approach that addresses the issue of limited training data and annotation shortage. The key part in SSL is its proxy task that define…
Limited View Tomographic Reconstruction Using a Deep Recurrent Framework with Residual Dense Spatial-Channel Attention Network and Sinogram Consistency
Bo Zhou, S. Kevin Zhou, James S. Duncan +1
Limited view tomographic reconstruction aims to reconstruct a tomographic image from a limited number of sinogram or projection views arising from sparse view or limited angle acqu…
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
S. Kevin Zhou, Hayit Greenspan, Christos Davatzikos +6
Since its renaissance, deep learning has been widely used in various medical imaging tasks and has achieved remarkable success in many medical imaging applications, thereby propell…
Embedding Task Knowledge into 3D Neural Networks via Self-supervised Learning
Jiuwen Zhu, Yuexiang Li, Yifan Hu +1
Deep learning highly relies on the amount of annotated data. However, annotating medical images is extremely laborious and expensive. To this end, self-supervised learning (SSL), a…
First image then video: A two-stage network for spatiotemporal video denoising
Ce Wang, S. Kevin Zhou, Zhiwei Cheng
Video denoising is to remove noise from noise-corrupted data, thus recovering true signals via spatiotemporal processing. Existing approaches for spatiotemporal video denoising ten…
DuDoRNet: Learning a Dual-Domain Recurrent Network for Fast MRI Reconstruction with Deep T1 Prior
Bo Zhou, S. Kevin Zhou
MRI with multiple protocols is commonly used for diagnosis, but it suffers from a long acquisition time, which yields the image quality vulnerable to say motion artifacts. To accel…
ADSegNet: Anatomy-aware artifact disentanglement and segmentation network for unpaired segmentation, artifact reduction, and modality translation
Yuanyuan Lyu, Haofu Liao, Heqin Zhu +1
Spinal surgery planning necessitates automatic segmentation of vertebrae in cone-beam computed tomography (CBCT), an intraoperative imaging modality that is widely used in interven…