Automatic magnetic resonance prostate segmentation by deep learning with holistically nested networks-Reference-Cited by-同舟云学术

Automatic magnetic resonance prostate segmentation by deep learning with holistically nested networks

Published:2017-08-21 Issue:04 Volume:4 Page:1
ISSN:2329-4302
Container-title:Journal of Medical Imaging
language:
Short-container-title:J. Med. Imag

Author:

Cheng Ruida¹,Roth Holger R.²,Lay Nathan²,Lu Le²,Turkbey Baris³,Gandler William¹,McCreedy Evan S.¹,Pohida Tom⁴,Pinto Peter A.⁵,Choyke Peter³,McAuliffe Matthew J.¹,Summers Ronald M.²

Affiliation:

1. Imaging Sciences Laboratory, Center of Information Technology, NIH, Bethesda, Maryland

2. Imaging Biomarkers and CAD Laboratory, Clinical Center, NIH, Bethesda, Maryland

3. Molecular Imaging Program, NCI, Bethesda, Maryland

4. Computational Bioscience and Engineering Laboratory, Center of Information Technology, NIH, Bethesda

5. Center of Cancer Research, Urologic Oncology Branch, Bethesda, Maryland

Publisher

SPIE-Intl Soc Optical Eng

Subject

Radiology Nuclear Medicine and imaging

Reference28 articles.

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3. Prostate Cancer Imaging. Computer-Aided Diagnosis, Prognosis, and Intervention

4. Multifeature Landmark-Free Active Appearance Models: Application to Prostate MRI Segmentation

5. A new prostate segmentation approach using multispectral magnetic resonance imaging and a statistical pattern classifier

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