1 citations · 1 across the 4 of their papers we have counts for
4 papers
AUCp: Pseudo-AUC for Inference Model Selection with Unlabeled Validation Data in Abnormality Detection
Md Mahfuzur Rahman Siddiquee, Fazle Rafsani, Jay Shah +4
Abnormality detection is a crucial yet challenging task in medical image analysis. Distinguishing abnormalities from normal data by learning to reconstruct normal-only data allevia…
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…
Efficient Feature Extraction and Classification Architecture for MRI-Based Brain Tumor Detection and Localization
Plabon Paul, Md. Nazmul Islam, Fazle Rafsani +2
Uncontrolled cell division in the brain is what gives rise to brain tumors. If the tumor size increases by more than half, there is little hope for the patient's recovery. This emp…
AnoFPDM: Anomaly Segmentation with Forward Process of Diffusion Models for Brain MRI
Yiming Che, Fazle Rafsani, Jay Shah +2
Weakly-supervised diffusion models (DMs) in anomaly segmentation, leveraging image-level labels, have attracted significant attention for their superior performance compared to uns…