A random walk-based segmentation framework for 3D ultrasound images of the prostate-Reference-Cited by-同舟云学术

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A random walk-based segmentation framework for 3D ultrasound images of the prostate

Published:2017-07-18 Issue:10 Volume:44 Page:5128-5142
ISSN:0094-2405
Container-title:Medical Physics
language:en
Short-container-title:Med. Phys.

Author:

Ma Ling¹,Guo Rongrong¹,Tian Zhiqiang¹,Fei Baowei¹²³⁴

Affiliation:

1. Department of Radiology and Imaging Sciences; Emory University School of Medicine; Atlanta GA 30329 USA

2. The Wallace H. Coulter Department of Biomedical Engineering; Emory University and Georgia Institute of Technology; Atlanta GA 30329 USA

3. Winship Cancer Institute of Emory University; Atlanta GA 30329 USA

4. Department of Mathematics and Computer Science; Emory College of Emory University; Atlanta GA 30329 USA

Funder

National Institutes of Health

Georgia Research Alliance Distinguished Scientists Award

Publisher

Wiley

Subject

General Medicine

Reference48 articles.

1. Cancer statistics, 2016;Siegel;CA Cancer J Clin,2015

2. Intra-and inter-observer variability and reliability of prostate volume measurement via two-dimensional and three-dimensional ultrasound imaging;Tong;Ultrasound Med Biol,1998

3. A survey of prostate segmentation methodologies in ultrasound, magnetic resonance and computed tomography images;Ghose;Comput Methods Programs Biomed,2012

4. Prostate boundary segmentation from ultrasound images using 2D active shape models: optimisation and extension to 3D;Hodge;Comput Methods Programs Biomed,2006

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A multi-center study of ultrasound images using a fully automated segmentation architecture;Pattern Recognition;2024-01

2. H-ProMed: Ultrasound image segmentation based on the evolutionary neural network and an improved principal curve;Pattern Recognition;2022-11

3. Deep Attentive Features for Prostate Segmentation in 3D Transrectal Ultrasound;IEEE Transactions on Medical Imaging;2019-12

4. Automatic prostate segmentation using multiobjective active appearance modelin MR images;TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES;2019-11-26

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