4 papers
CheXtriev: Anatomy-Centered Representation for Case-Based Retrieval of Chest Radiographs
Naren Akash, Arihanth Tadanki, Jayanthi Sivaswamy
We present CheXtriev, a graph-based, anatomy-aware framework for chest radiograph retrieval. Unlike prior methods focussed on global features, our method leverages graph transforme…
Do Medical Vision Models Reason About Anatomy? Probing the Spatial Inductive Biases of Learned Visual Representations
Naren Akash, Neeraja Ramanan
Interpreting a CT scan means comparing structures on either side, judging how far apart organs sit, and knowing where each one belongs. Medical vision encoders are evaluated on dia…
MeDxAgent: Multi-Agent Consultation for Interactive Medical Diagnosis
Akshat Sanghvi, Naren Akash, Raza Imam +2
Large language models (LLMs) are increasingly used for health-related decision support. Yet most evaluations treat diagnosis as a single-shot task with complete information provide…
The MICCAI Hackathon on reproducibility, diversity, and selection of papers at the MICCAI conference
Fabian Balsiger, Alain Jungo, Naren Akash R J +12
The MICCAI conference has encountered tremendous growth over the last years in terms of the size of the community, as well as the number of contributions and their technical succes…