A Heuristic Framework for Image Filtering and Segmentation: Application to Blood Vessel ImmunohistochemistryReport as inadecuate




A Heuristic Framework for Image Filtering and Segmentation: Application to Blood Vessel Immunohistochemistry - Download this document for free, or read online. Document in PDF available to download.

Analytical Cellular Pathology - Volume 2015 2015, Article ID 589158, 10 pages -

Research Article

Institute of Biomedical Engineering, College of Medicine and College of Engineering, National Taiwan University, No. 1, Section 1, Jen-Ai Road, Taipei 100, Taiwan

Department of Radiology, National Taiwan University College of Medicine and Department of Medical Imaging, National Taiwan University Hospital, No. 7, Chung-Shan South Road, Taipei 100, Taiwan

Department of Internal Medicine, National Taiwan University College of Medicine, No. 7, Chung-Shan South Road, Taipei 100, Taiwan

Received 28 April 2015; Revised 2 September 2015; Accepted 10 September 2015

Academic Editor: Giovanni Tuccari

Copyright © 2015 Chi-Hsuan Tsou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The blood vessel density in a cancerous tissue sample may represent increased levels of tumor growth. However, identifying blood vessels in the histological tissue image is difficult and time-consuming and depends heavily on the observer’s experience. To overcome this drawback, computer-aided image analysis frameworks have been investigated in order to boost object identification in histological images. We present a novel algorithm to automatically abstract the salient regions in blood vessel images. Experimental results show that the proposed framework is capable of deriving vessel boundaries that are comparable to those demarcated manually, even for vessel regions with weak contrast between the object boundaries and background clutter.





Author: Chi-Hsuan Tsou, Yi-Chien Lu, Ang Yuan, Yeun-Chung Chang, and Chung-Ming Chen

Source: https://www.hindawi.com/



DOWNLOAD PDF




Related documents