5 citations · 14 across the 7 of their papers we have counts for
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physics.med-ph2022★ 4 cited
Semi-supervised learning towards automated segmentation of PET images with limited annotations: Application to lymphoma patients
Fereshteh Yousefirizi, Isaac Shiri, Joo Hyun O +9
The time-consuming task of manual segmentation challenges routine systematic quantification of disease burden. Convolutional neural networks (CNNs) hold significant promise to reli…
physics.med-ph2022
Convolutional neural network with a hybrid loss function for fully automated segmentation of lymphoma lesions in FDG PET images
Fereshteh Yousefirizi, Natalia Dubljevic, Shadab Ahamed +9
Segmentation of lymphoma lesions is challenging due to their varied sizes and locations in whole-body PET scans. This work presents a fully-automated segmentation technique using a…