Automated skin thickening extraction in post radiotherapy mammograms via feedforward neural networks using histogram based segmentation and continuous hidden Markov model generated features

Authors

L. Barinov, Rutgers Cancer Institute of New Jersey
L. Paster, Rutgers Robert Wood Johnson Medical School
N. Yue, Rutgers Cancer Institute of New Jersey
Z. Xiao, Rutgers Cancer Institute of New Jersey
Q. Huang, Rutgers Cancer Institute of New Jersey
S. Goyal, Rutgers Cancer Institute of New Jersey

Document Type

Conference Proceeding

Publication Date

2-11-2016

Journal

2015 IEEE Signal Processing in Medicine and Biology Symposium - Proceedings

DOI

10.1109/SPMB.2015.7405459

Abstract

© 2015 IEEE. The purpose of this study is to establish an automated technique that accurately and effectively characterizes skin thickening in mammograms after breast conserving surgery and radiation therapy (BCS+RT).

APA Citation

Barinov, L., Paster, L., Yue, N., Xiao, Z., Huang, Q., & Goyal, S. (2016). Automated skin thickening extraction in post radiotherapy mammograms via feedforward neural networks using histogram based segmentation and continuous hidden Markov model generated features. 2015 IEEE Signal Processing in Medicine and Biology Symposium - Proceedings, (). http://dx.doi.org/10.1109/SPMB.2015.7405459