Published July 2019
| Version v1
Journal article
Automatic Segmentation of the Prostate on CT Images Using Deep Neural Networks (DNN)
Creators
- 1. Department of Radiation Oncology, Josephine Ford Cancer Institute, Henry Ford Health System, Detroit (United States)
Description
Recent advances in deep neural networks (DNNs) have unlocked opportunities for their application for automatic image segmentation. We have evaluated a DNN-based algorithm for automatic segmentation of the prostate gland on a large cohort of patient images.
Additional details
Identifiers
- DOI
- 10.1016/j.ijrobp.2019.03.017;
- PII
- S0360301619303761;
Publishing Information
- Journal Title
- International Journal of Radiation Oncology, Biology and Physics
- Journal Volume
- 104
- Journal Issue
- 4
- Journal Page Range
- p. 924-932
- ISSN
- 0360-3016
- CODEN
- IOBPD3
INIS
- Country of Publication
- United States
- Country of Input or Organization
- International Atomic Energy Agency (IAEA)
- INIS RN
- 55060838
- Subject category
- S62: RADIOLOGY AND NUCLEAR MEDICINE;
- Descriptors DEI
- ALGORITHMS; COMPUTERIZED TOMOGRAPHY; IMAGES; NEURAL NETWORKS; PATIENTS; PROSTATE
- Descriptors DEC
- BODY; DIAGNOSTIC TECHNIQUES; GLANDS; MALE GENITALS; MATHEMATICAL LOGIC; ORGANS; TOMOGRAPHY
Optional Information
- Copyright
- Copyright (c) 2019 Elsevier Inc. All rights reserved.