5 citations · 15 across the 5 of their papers we have counts for
9 papers · 1 filter
Affine Medical Image Registration with Coarse-to-Fine Vision Transformer
Tony C. W. Mok, Albert C. S. Chung
Affine registration is indispensable in a comprehensive medical image registration pipeline. However, only a few studies focus on fast and robust affine registration algorithms. Mo…
Conditional Deformable Image Registration with Convolutional Neural Network
Tony C. W. Mok, Albert C. S. Chung
Recent deep learning-based methods have shown promising results and runtime advantages in deformable image registration. However, analyzing the effects of hyperparameters and searc…
Fast Symmetric Diffeomorphic Image Registration with Convolutional Neural Networks
Tony C. W. Mok, Albert C. S. Chung
Diffeomorphic deformable image registration is crucial in many medical image studies, as it offers unique, special properties including topology preservation and invertibility of t…
CELNet: Evidence Localization for Pathology Images using Weakly Supervised Learning
Yongxiang Huang, Albert C. S. Chung
Despite deep convolutional neural networks boost the performance of image classification and segmentation in digital pathology analysis, they are usually weak in interpretability f…
A Fine-Grain Error Map Prediction and Segmentation Quality Assessment Framework for Whole-Heart Segmentation
Rongzhao Zhang, Albert C. S. Chung
When introducing advanced image computing algorithms, e.g., whole-heart segmentation, into clinical practice, a common suspicion is how reliable the automatically computed results…
A Unified Mammogram Analysis Method via Hybrid Deep Supervision
Rongzhao Zhang, Han Zhang, Albert C. S. Chung
Automatic mammogram classification and mass segmentation play a critical role in a computer-aided mammogram screening system. In this work, we present a unified mammogram analysis…