Joint Lymphoma Lesion Segmentation and Prognosis Prediction From Baseline FDG-PET Images via Multitask Convolutional Neural Networks

Joint Lymphoma Lesion Segmentation and Prognosis Prediction From Baseline FDG-PET Images via Multitask Convolutional Neural Networks

<italic>Objective:</italic> Lymphoma lesion segmentation and prognosis prediction from baseline FDG-PET images are valuable for tailoring and adapting a treatment plan for patients with Diffuse Large B-cell Lymphoma (DLBCL). However, the tasks are challenging due to the fact that DLBCL i...

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Bibliographic Details
Main Authors: Peng Liu, Miao Zhang, Xiaoru Gao, Biao Li, Guoyan Zheng
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Diffuse large b-cell lymphoma (DLBCL)
prognostic model
multi-task learning
PET images
Online Access:https://ieeexplore.ieee.org/document/9847204/

Internet

https://ieeexplore.ieee.org/document/9847204/

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