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Št. zadetkov: 2
Uncertainty quantification for deep learning-based metastatic lesion segmentation on whole body PET/CT
Brayden Schott, Victor Santoro Fernandes, Žan Klaneček, Scott Perlman, Robert Jeraj
Izvirni znanstveni članek
Oznake: medicinska fizika;medicinsko slikanje;tumorji;globoko učenje;medical physics;medical imaging;tumors;deep learning;
Objective. Deep learning models are increasingly being implemented for automated medical image analysis to inform patient care. Most models, however, lack uncertainty information, without which the reliability of model outputs cannot be ensured. Several uncertainty quantification (UQ) methods exist ...
Leto: 2025 Vir: Fakulteta za matematiko in fiziko (UL FMF)
Uncertainty quantification via localized gradients for deep learning-based medical image assessments
Brayden Schott, Dmitry Pinchuk, Victor Santoro Fernandes, Žan Klaneček, Luciano Rivetti, Alison Deatsch, Scott Perlman, Yixuan Li, Robert Jeraj
Izvirni znanstveni članek
Oznake: medicinska fizika;medicinsko slikanje;tumorji;globoko učenje;medical physics;medical imaging;tumors;deep learning;
Objective. Deep learning models that aid in medical image assessment tasks must be both accurate and reliable to be deployed within clinical settings. While deep learning models have been shown to be highly accurate across a variety of tasks, measures that indicate the reliability of these models ar ...
Leto: 2024 Vir: Fakulteta za matematiko in fiziko (UL FMF)
Št. zadetkov: 2
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