An Automated Segmentation Pipeline for Intratumoural Regions in Animal Xenografts Using Machine Learning and Saturation Transfer MRI.
Adenocarcinoma
/ pathology
Algorithms
Animals
Apoptosis
Automation
Cell Proliferation
Female
Humans
Image Processing, Computer-Assisted
/ methods
Machine Learning
Magnetic Resonance Imaging
/ methods
Male
Mice
Mice, Nude
Prostatic Neoplasms
/ pathology
Tumor Cells, Cultured
Xenograft Model Antitumor Assays
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
15 05 2020
15 05 2020
Historique:
received:
27
01
2020
accepted:
24
04
2020
entrez:
17
5
2020
pubmed:
18
5
2020
medline:
1
12
2020
Statut:
epublish
Résumé
Saturation transfer MRI can be useful in the characterization of different tumour types. It is sensitive to tumour metabolism, microstructure, and microenvironment. This study aimed to use saturation transfer to differentiate between intratumoural regions, demarcate tumour boundaries, and reduce data acquisition times by identifying the imaging scheme with the most impact on segmentation accuracy. Saturation transfer-weighted images were acquired over a wide range of saturation amplitudes and frequency offsets along with T
Identifiants
pubmed: 32415137
doi: 10.1038/s41598-020-64912-6
pii: 10.1038/s41598-020-64912-6
pmc: PMC7228927
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
8063Références
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