most citedRR-CP: Reliable-Region-Based Conformal Prediction for Trustworthy Medical Image Classification

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eess.IV2024

Towards Ground-truth-free Evaluation of Any Segmentation in Medical Images

Ahjol Senbi, Tianyu Huang, Fei Lyu +8

We explore the feasibility and potential of building a ground-truth-free evaluation model to assess the quality of segmentations generated by the Segment Anything Model (SAM) and i…

eess.IV2023

SQA-SAM: Segmentation Quality Assessment for Medical Images Utilizing the Segment Anything Model

Yizhe Zhang, Shuo Wang, Tao Zhou +2

Segmentation quality assessment (SQA) plays a critical role in the deployment of a medical image based AI system. Users need to be informed/alerted whenever an AI system generates…