2 citations · 3 across the 5 of their papers we have counts for
5 papers
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…
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…
FG-CXR: A Radiologist-Aligned Gaze Dataset for Enhancing Interpretability in Chest X-Ray Report Generation
Trong Thang Pham, Ngoc-Vuong Ho, Nhat-Tan Bui +8
Developing an interpretable system for generating reports in chest X-ray (CXR) analysis is becoming increasingly crucial in Computer-aided Diagnosis (CAD) systems, enabling radiolo…
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…
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…