ARPM‐net: A novel CNN‐based adversarial method with Markov random field enhancement for prostate and organs at risk segmentation in pelvic CT images-Reference-Cited by-同舟云学术

ARPM‐net: A novel CNN‐based adversarial method with Markov random field enhancement for prostate and organs at risk segmentation in pelvic CT images

Published:2020-11-24 Issue:1 Volume:48 Page:227-237
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Zhang Zhuangzhuang¹,Zhao Tianyu²,Gay Hiram²,Zhang Weixiong³,Sun Baozhou²

Affiliation:

1. Department of Computer Science and Engineering Washington University One Brookings Drive, Campus Box 1045 St. Louis MO63130USA

2. Department of Radiation Oncology Washington University School of Medicine 4921 Parkview Place, Campus Box 8224 St. Louis MO63110USA

3. Department of Computer Science and Engineering Department of Genetics Washington University One Brookings Drive, Campus Box 1045 St. Louis MO63130USA

Funder

Varian Medical Systems

Publisher

Wiley

Subject

General Medicine

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mp.14580

Reference33 articles.

1. A novel MRI segmentation method using CNN ‐based correction network for MRI ‐guided adaptive radiotherapy

2. The Impact of Gross Tumor Volume (GTV) and Clinical Target Volume (CTV) Definition on the Total Accuracy in Radiotherapy

3. The probability of correct target dosage: dose-population histograms for deriving treatment margins in radiotherapy

4. Fully automated organ segmentation in male pelvic CT images

5. Segmentation of pelvic structures for planning CT using a geometrical shape model tuned by a multi-scale edge detector

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