6 citations · 14 across the 11 of their papers we have counts for
5 papers · 1 filter
From Embeddings to Accuracy: Comparing Foundation Models for Radiographic Classification
Xue Li, Jameson Merkow, Noel C. F. Codella +11
Foundation models provide robust embeddings for diverse tasks, including medical imaging. We evaluate embeddings from seven general and medical-specific foundation models (e.g., De…
WaveFormer: A 3D Transformer with Wavelet-Driven Feature Representation for Efficient Medical Image Segmentation
Md Mahfuz Al Hasan, Mahdi Zaman, Abdul Jawad +9
Transformer-based architectures have advanced medical image analysis by effectively modeling long-range dependencies, yet they often struggle in 3D settings due to substantial memo…
Multi-Modal Mamba Modeling for Survival Prediction (M4Survive): Adapting Joint Foundation Model Representations
Ho Hin Lee, Alberto Santamaria-Pang, Jameson Merkov +2
Accurate survival prediction in oncology requires integrating diverse imaging modalities to capture the complex interplay of tumor biology. Traditional single-modality approaches o…
3D-MIR: A Benchmark and Empirical Study on 3D Medical Image Retrieval in Radiology
Asma Ben Abacha, Alberto Santamaria-Pang, Ho Hin Lee +9
The increasing use of medical imaging in healthcare settings presents a significant challenge due to the increasing workload for radiologists, yet it also offers opportunity for en…
Region-based Contrastive Pretraining for Medical Image Retrieval with Anatomic Query
Ho Hin Lee, Alberto Santamaria-Pang, Jameson Merkow +4
We introduce a novel Region-based contrastive pretraining for Medical Image Retrieval (RegionMIR) that demonstrates the feasibility of medical image retrieval with similar anatomic…