Convolutional neural network initialized active contour model with adaptive ellipse fitting for nuclear segmentation on breast histopathological images-Reference-Cited by-同舟云学术

Convolutional neural network initialized active contour model with adaptive ellipse fitting for nuclear segmentation on breast histopathological images

Published:2019-02-08 Issue:01 Volume:6 Page:1
ISSN:2329-4302
Container-title:Journal of Medical Imaging
language:
Short-container-title:J. Med. Imag.

Author:

Xu Jun¹,Gong Lei¹,Wang Guanhao¹,Lu Cheng²,Gilmore Hannah³,Zhang Shaoting⁴,Madabhushi Anant²

Affiliation:

1. Nanjing University of Information Science and Technology, Jiangsu Key Laboratory of Big Data Analysi

2. Case Western Reserve University, Department of Biomedical Engineering, Cleveland, Ohio

3. University Hospitals Case Medical Center, Case Western Reserve University, Institute for Pathology,

4. University of North Carolina at Charlotte, Department of Computer Science, Charlotte, North Carolina

Publisher

SPIE-Intl Soc Optical Eng

Subject

Radiology, Nuclear Medicine and imaging

Reference69 articles.

1. Systematic Analysis of Breast Cancer Morphology Uncovers Stromal Features Associated with Survival

2. Expectation–Maximization-Driven Geodesic Active Contour With Overlap Resolution (EMaGACOR): Application to Lymphocyte Segmentation on Breast Cancer Histopathology

3. Automatic image segmentation of nuclear stained breast tissue sections using color active contour model and an improved watershed method

4. An Update of the Gleason Grading System

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