6 citations · 11 across the 8 of their papers we have counts for
3 papers · 1 filter
DinoAtten3D: Slice-Level Attention Aggregation of DinoV2 for 3D Brain MRI Anomaly Classification
Fazle Rafsani, Jay Shah, Catherine D. Chong +2
Anomaly detection and classification in medical imaging are critical for early diagnosis but remain challenging due to limited annotated data, class imbalance, and the high cost of…
Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR Images
Md Mahfuzur Rahman Siddiquee, Jay Shah, Teresa Wu +5
Harnessing the power of deep neural networks in the medical imaging domain is challenging due to the difficulties in acquiring large annotated datasets, especially for rare disease…
HealthyGAN: Learning from Unannotated Medical Images to Detect Anomalies Associated with Human Disease
Md Mahfuzur Rahman Siddiquee, Jay Shah, Teresa Wu +3
Automated anomaly detection from medical images, such as MRIs and X-rays, can significantly reduce human effort in disease diagnosis. Owing to the complexity of modeling anomalies…