Search Results for author:
Found 5 papers, 2 papers with code
3D-MIR: A Benchmark and Empirical Study on 3D Medical Image Retrieval in Radiology
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 enhancing healthcare outcomes if effectively leveraged.
Region-based Contrastive Pretraining for Medical Image Retrieval with Anatomic Query
We introduce a novel Region-based contrastive pretraining for Medical Image Retrieval (RegionMIR) that demonstrates the feasibility of medical image retrieval with similar anatomical regions.
Deep Labeling of fMRI Brain Networks
We prove the generalizability of our method by showing that the MLP performs at 100% accuracy in the holdout dataset and 98. 3% accuracy in three other sites' fMRI acquisitions.
Deep Labeling of fMRI Brain Networks Using Cloud Based Processing
We propose an end-to-end reproducible pipeline which incorporates image processing of rs-fMRI in a cloud-based workflow while using deep learning to automate the classification of RSNs.
CheXstray: Real-time Multi-Modal Data Concordance for Drift Detection in Medical Imaging AI
We use the CheXpert and PadChest public datasets to build and test a medical imaging AI drift monitoring workflow to track data and model drift without contemporaneous ground truth.
