6 citations · 9 across the 6 of their papers we have counts for
6 papers
AdaCBM: An Adaptive Concept Bottleneck Model for Explainable and Accurate Diagnosis
Townim F. Chowdhury, Vu Minh Hieu Phan, Kewen Liao +5
The integration of vision-language models such as CLIP and Concept Bottleneck Models (CBMs) offers a promising approach to explaining deep neural network (DNN) decisions using conc…
PairAug: What Can Augmented Image-Text Pairs Do for Radiology?
Yutong Xie, Qi Chen, Sinuo Wang +7
Current vision-language pre-training (VLP) methodologies predominantly depend on paired image-text datasets, a resource that is challenging to acquire in radiology due to privacy c…
CAPE: CAM as a Probabilistic Ensemble for Enhanced DNN Interpretation
Townim Faisal Chowdhury, Kewen Liao, Vu Minh Hieu Phan +7
Deep Neural Networks (DNNs) are widely used for visual classification tasks, but their complex computation process and black-box nature hinder decision transparency and interpretab…
Decomposing Disease Descriptions for Enhanced Pathology Detection: A Multi-Aspect Vision-Language Pre-training Framework
Vu Minh Hieu Phan, Yutong Xie, Yuankai Qi +7
Medical vision language pre-training (VLP) has emerged as a frontier of research, enabling zero-shot pathological recognition by comparing the query image with the textual descript…
BHSD: A 3D Multi-Class Brain Hemorrhage Segmentation Dataset
Biao Wu, Yutong Xie, Zeyu Zhang +6
Intracranial hemorrhage (ICH) is a pathological condition characterized by bleeding inside the skull or brain, which can be attributed to various factors. Identifying, localizing a…
Structure-Preserving Synthesis: MaskGAN for Unpaired MR-CT Translation
Minh Hieu Phan, Zhibin Liao, Johan W. Verjans +1
Medical image synthesis is a challenging task due to the scarcity of paired data. Several methods have applied CycleGAN to leverage unpaired data, but they often generate inaccurat…