activity
20242026
collaborators

7 papers

cs.AI2026

IMACT-CXR: An Interactive Multi-Agent Conversational Tutoring System for Chest X-Ray Interpretation

Tuan-Anh Le, Anh Mai Vu, David Yang +2

IMACT-CXR is an interactive multi-agent conversational tutor that helps trainees interpret chest X-rays by unifying spatial annotation, gaze analysis, knowledge retrieval, and imag…

cs.CV2025

Contrastive Integrated Gradients: A Feature Attribution-Based Method for Explaining Whole Slide Image Classification

Anh Mai Vu, Tuan L. Vo, Ngoc Lam Quang Bui +7

Interpretability is essential in Whole Slide Image (WSI) analysis for computational pathology, where understanding model predictions helps build trust in AI-assisted diagnostics. W…

cs.CV2025

Beyond the First Read: AI-Assisted Perceptual Error Detection in Chest Radiography Accounting for Interobserver Variability

Adhrith Vutukuri, Akash Awasthi, David Yang +2

Chest radiography is widely used in diagnostic imaging. However, perceptual errors -- especially overlooked but visible abnormalities -- remain common and clinically significant. C…

cs.CV2024

GazeSearch: Radiology Findings Search Benchmark

Trong Thang Pham, Tien-Phat Nguyen, Yuki Ikebe +5

Medical eye-tracking data is an important information source for understanding how radiologists visually interpret medical images. This information not only improves the accuracy o…

eess.IV2024

Multimodal Learning and Cognitive Processes in Radiology: MedGaze for Chest X-ray Scanpath Prediction

Akash Awasthi, Ngan Le, Zhigang Deng +3

Predicting human gaze behavior within computer vision is integral for developing interactive systems that can anticipate user attention, address fundamental questions in cognitive…

eess.IV2024

Enhancing Radiological Diagnosis: A Collaborative Approach Integrating AI and Human Expertise for Visual Miss Correction

Akash Awasthi, Ngan Le, Zhigang Deng +2

Human-AI collaboration to identify and correct perceptual errors in chest radiographs has not been previously explored. This study aimed to develop a collaborative AI system, CoRaX…