6 citations · 14 across the 11 of their papers we have counts for
11 papers
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…
OPTIC: Optimizing Patient-Provider Triaging & Improving Communications in Clinical Operations using GPT-4 Data Labeling and Model Distillation
Alberto Santamaria-Pang, Frank Tuan, Ross Campbell +11
The COVID-19 pandemic has accelerated the adoption of telemedicine and patient messaging through electronic medical portals (patient medical advice requests, or PMARs). While these…
MedImageInsight: An Open-Source Embedding Model for General Domain Medical Imaging
Noel C. F. Codella, Ying Jin, Shrey Jain +28
In this work, we present MedImageInsight, an open-source medical imaging embedding model. MedImageInsight is trained on medical images with associated text and labels across a dive…
Scalable Drift Monitoring in Medical Imaging AI
Jameson Merkow, Felix J. Dorfner, Xiyu Yang +6
The integration of artificial intelligence (AI) into medical imaging has advanced clinical diagnostics but poses challenges in managing model drift and ensuring long-term reliabili…
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…
Deep Labeling of fMRI Brain Networks
Ammar Ahmed Pallikonda Latheef, Sejal Ghate, Zhipeng Hui +4
Resting State Networks (RSNs) of the brain extracted from Resting State functional Magnetic Resonance Imaging (RS-fMRI) are used in the pre-surgical planning to guide the neurosurg…
Deep Labeling of fMRI Brain Networks Using Cloud Based Processing
Sejal Ghate, Alberto Santamaria-Pang, Ivan Tarapov +2
Resting state fMRI is an imaging modality which reveals brain activity localization through signal changes, in what is known as Resting State Networks (RSNs). This technique is gai…
CheXstray: Real-time Multi-Modal Data Concordance for Drift Detection in Medical Imaging AI
Arjun Soin, Jameson Merkow, Jin Long +6
Clinical Artificial lntelligence (AI) applications are rapidly expanding worldwide, and have the potential to impact to all areas of medical practice. Medical imaging applications…