104 citations · 261 across the 17 of their papers we have counts for
18 papers
Robust Image Registration with Absent Correspondences in Pre-operative and Follow-up Brain MRI Scans of Diffuse Glioma Patients
Tony C. W. Mok, Albert C. S. Chung
Registration of pre-operative and follow-up brain MRI scans is challenging due to the large variation of tissue appearance and missing correspondences in tumour recurrence regions…
InstantGroup: Instant Template Generation for Scalable Group of Brain MRI Registration
Ziyi He, Albert C. S. Chung
Template generation is a critical step in groupwise image registration, which involves aligning a group of subjects into a common space. While existing methods can generate high-qu…
Unsupervised Deformable Image Registration with Absent Correspondences in Pre-operative and Post-Recurrence Brain Tumor MRI Scans
Tony C. W. Mok, Albert C. S. Chung
Registration of pre-operative and post-recurrence brain images is often needed to evaluate the effectiveness of brain gliomas treatment. While recent deep learning-based deformable…
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…
Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning
Alessa Hering, Lasse Hansen, Tony C. W. Mok +50
Image registration is a fundamental medical image analysis task, and a wide variety of approaches have been proposed. However, only a few studies have comprehensively compared medi…
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…
Edge-variational Graph Convolutional Networks for Uncertainty-aware Disease Prediction
Yongxiang Huang, Albert C. S. Chung
There is a rising need for computational models that can complementarily leverage data of different modalities while investigating associations between subjects for population-base…
Large Deformation Diffeomorphic Image Registration with Laplacian Pyramid Networks
Tony C. W. Mok, Albert C. S. Chung
Deep learning-based methods have recently demonstrated promising results in deformable image registration for a wide range of medical image analysis tasks. However, existing deep l…
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…
3D Deep Affine-Invariant Shape Learning for Brain MR Image Segmentation
Zhou He, Siqi Bao, Albert Chung
Recent advancements in medical image segmentation techniques have achieved compelling results. However, most of the widely used approaches do not take into account any prior knowle…
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…
Improving High Resolution Histology Image Classification with Deep Spatial Fusion Network
Yongxiang Huang, Albert Chi-shing Chung
Histology imaging is an essential diagnosis method to finalize the grade and stage of cancer of different tissues, especially for breast cancer diagnosis. Specialists often disagre…
Deep supervision with additional labels for retinal vessel segmentation task
Yishuo Zhang, Albert C. S. Chung
Automatic analysis of retinal blood images is of vital importance in diagnosis tasks of retinopathy. Segmenting vessels accurately is a fundamental step in analysing retinal images…
Learning Data Augmentation for Brain Tumor Segmentation with Coarse-to-Fine Generative Adversarial Networks
Tony C. W Mok, Albert C. S Chung
There is a common belief that the successful training of deep neural networks requires many annotated training samples, which are often expensive and difficult to obtain especially…
3D Randomized Connection Network with Graph-based Label Inference
Siqi Bao, Pei Wang, Tony C. W. Mok +1
In this paper, a novel 3D deep learning network is proposed for brain MR image segmentation with randomized connection, which can decrease the dependency between layers and increas…
Feature Sensitive Label Fusion with Random Walker for Atlas-based Image Segmentation
Siqi Bao, Albert C. S. Chung
In this paper, a novel label fusion method is proposed for brain magnetic resonance image segmentation. This label fusion method is formulated on a graph, which embraces both label…