Region-specific deep learning models for accurate segmentation of rectal structures on post-chemoradiation T2w MRI: a multi-institutional, multi-reader study

INTRODUCTION: For locally advanced rectal cancers, in vivo radiological evaluation of tumor extent and regression after neoadjuvant therapy involves implicit visual identification of rectal structures on magnetic resonance imaging (MRI). Additionally, newer image-based, computational approaches (e.g...

Descripción completa

Detalles Bibliográficos
Autores principales: DeSilvio, Thomas, Antunes, Jacob T., Bera, Kaustav, Chirra, Prathyush, Le, Hoa, Liska, David, Stein, Sharon L., Marderstein, Eric, Hall, William, Paspulati, Rajmohan, Gollamudi, Jayakrishna, Purysko, Andrei S., Viswanath, Satish E.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Medicine
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10213753/
https://www.ncbi.nlm.nih.gov/pubmed/37250635
http://dx.doi.org/10.3389/fmed.2023.1149056

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10213753/
https://www.ncbi.nlm.nih.gov/pubmed/37250635
http://dx.doi.org/10.3389/fmed.2023.1149056

Ejemplares similares