Publications (5)
EVO-LRP: Evolutionary Optimization of LRP for Interpretable Model Explanations
Emerald Zhang, Julian Weaver, Samantha R Santacruz +1
Explainable AI (XAI) methods help identify which image regions influence a model's prediction, but often face a trade-off between detail and interpretability. Layer-wise Relevance…
PathMoE: Interpretable Multimodal Interaction Experts for Pediatric Brain Tumor Classification
Jian Yu, Joakim Nguyen, Jinrui Fang +10
Accurate classification of pediatric central nervous system tumors remains challenging due to histological complexity and limited training data. While pathology foundation models h…
ConceptMoE: Concept-Guided Multimodal Mixture of Experts for Interpretable Computational Pathology
Xuan Wang, Zhongling Xu, Gopi Kannedhara +13
Healthcare models are transitioning from unimodal prediction toward multimodal reasoning over heterogeneous diagnostic inputs. In computational pathology, for complex tumor subtype…
Implementation and evaluation of various demons deformable image registration algorithms on GPU
Xuejun Gu, Hubert Pan, Yun Liang +7
Online adaptive radiation therapy (ART) promises the ability to deliver an optimal treatment in response to daily patient anatomic variation. A major technical barrier for the clin…
Deriving ventilation imaging from 4DCT by deep convolutional neural network
Yuncheng Zhong, Yevgeniy Vinogradskiy, Liyuan Chen +6
Purpose: Functional imaging is emerging as an important tool for lung cancer treatment planning and evaluation. Compared with traditional methods such as nuclear medicine ventilati…