Simultaneous cosegmentation of tumors in PET‐CT images using deep fully convolutional networks

PURPOSE: To investigate the use and efficiency of 3‐D deep learning, fully convolutional networks (DFCN) for simultaneous tumor cosegmentation on dual‐modality nonsmall cell lung cancer (NSCLC) and positron emission tomography (PET)‐computed tomography (CT) images. METHODS: We used DFCN cosegmentati...

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Bibliographic Details
Published in:Med Phys
Main Authors: Zhong, Zisha, Kim, Yusung, Plichta, Kristin, Allen, Bryan G., Zhou, Leixin, Buatti, John, Wu, Xiaodong
Format: Artigo
Language:Inglês
Published: John Wiley and Sons Inc. 2019
Subjects:
QUANTITATIVE IMAGING AND IMAGE PROCESSING
Online Access:https://ncbi.nlm.nih.gov/pmc/articles/PMC6527327/
https://ncbi.nlm.nih.gov/pubmed/30537103
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1002/mp.13331
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