An AI-generated radiology report can resemble a physician's report while omitting an abnormality, adding an unsupported finding, or reversing its presence. Measuring these factual differences is essential for evaluating report generators. We study Jev, a System One decision model, as a simple, low-cost judge of agreeme...
Jia-Ju Huang, Hao Yang, Xin-Yu Ma et al.· 0 citations
Comprehensive magnetic resonance imaging (MRI) analysis in oncology involves multiple interrelated tasks including volumetric segmentation, grading, staging, and malignancy detection. However, most existing deep learning models are task-specific or sequence-specific, lacking the generalizability required for heterogene...
TRIAGE, Tracer-aware Refinement via Interactive Anatomy-Guided sEgmentation, a 3D STU-Net initialized through masked autoencoding pre-training with an asynchronous masking strategy, aiming to learn transferable anatomical and cross-modal representations before task-specific fine-tuning.
Xing-Long Liang, Chun-Fang Lu, Tian-Yu Zhang et al.· 0 citations
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