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Description
In this study, we explore whether the streamlined PocketNet architecture can perform comparably to the more robust nnU-Net framework for the auto-segmentation of pelvic structures and tumor volumes in the CT scans of cervical cancer patients.
Publication Date
8-2024
Recommended Citation
Chacko, Sarah M.; Sjogreen, Carlos PhD; Parameshwaran, Jaganathan A. MD; Court, Laurence E. PhD; and Netherton, Tucker J. PhD, DMP, "Auto-segmentation of structures in cervical cancer treatment planning using a deep learning framework" (2024). Students Summer in Oncology at Anderson Research (SOAR). 5.
https://openworks.mdanderson.org/soar24/5
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