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A task-specific deep-learning-based denoising approach for myocardial perfusion SPECT.

, , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 12467 of SPIE Proceedings, SPIE, (2023)

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Reliability of PET/CT shape and heterogeneity features in functional and morphological components of Non-Small Cell Lung Cancer tumors: a repeatability analysis in a prospective multi-center cohort., , , , , , and . CoRR, (2016)A task-specific deep-learning-based denoising approach for myocardial perfusion SPECT., , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 12467 of SPIE Proceedings, SPIE, (2023)An estimation-based method to segment PET images., , , , , , , , , and . CoRR, (2020)Need for objective task-based evaluation of AI-based segmentation methods for quantitative PET., , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 12467 of SPIE Proceedings, SPIE, (2023)DEMIST: A deep-learning-based task-specific denoising approach for myocardial perfusion SPECT., , , , , and . CoRR, (2023)rPOP: Robust PET-only processing of community acquired heterogeneous amyloid-PET data., , , , , , , , , and 2 other author(s). NeuroImage, (2022)Observer study-based evaluation of a stochastic and physics-based method to generate oncological PET images., , , , , , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 11599 of SPIE Proceedings, SPIE, (2021)No-gold-standard evaluation of quantitative imaging methods in the presence of correlated noise., , , , and . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, volume 12035 of SPIE Proceedings, SPIE, (2022)Need for Objective Task-based Evaluation of Deep Learning-Based Denoising Methods: A Study in the Context of Myocardial Perfusion SPECT., , , , , , , and . CoRR, (2023)