Effects of interobserver and interdisciplinary segmentation variabilities on CT-based radiomics for pancreatic cancer

Abstract Radiomics is a method to mine large numbers of quantitative imaging features and develop predictive models. It has shown exciting promise for improved cancer decision support from early detection to personalized precision treatment, and therefore offers a desirable new direction for pancrea...

Description complète

Enregistré dans:
Détails bibliographiques
Auteurs principaux: Jeffrey Wong, Michael Baine, Sarah Wisnoskie, Nathan Bennion, Dechun Zheng, Lei Yu, Vipin Dalal, Michael A. Hollingsworth, Chi Lin, Dandan Zheng
Format: article
Langue:EN
Publié: Nature Portfolio 2021
Sujets:
R
Q
Accès en ligne:https://doaj.org/article/bcdb7caa7f194e2184b552cfd4028e59
Tags: Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!