A neural network approach to segment brain blood vessels in digital subtraction angiography.

Journal: Computer methods and programs in biomedicine
Published Date: Nov 2, 2019

Abstract

BACKGROUND AND OBJECTIVE: Cerebrovascular diseases (CVDs) affect a large number of patients and often have devastating outcomes. The hallmarks of CVDs are the abnormalities formed on brain blood vessels, including protrusions, narrows, widening, and bifurcation of the blood vessels. CVDs are often diagnosed by digital subtraction angiography (DSA) yet the interpretation of DSA is challenging as one must carefully examine each brain blood vessel. The objective of this work is to develop a computerized analysis approach for automated segmentation of brain blood vessels.

Authors

  • Min Zhang
    Department of Infectious Disease, The Second Xiangya Hospital of Central South University, Changsha, China.
  • Chen Zhang
    Department of Dermatology, Affiliated Jinling Hospital, Medical School of Nanjing University, Nanjing, China.
  • Xian Wu
    Beijing University of Posts and Telecommunications, Beijing 100876, China.
  • Xinhua Cao
    Department of Radiology, Boston Children's Hospital, Boston, MA, USA.
  • Geoffrey S Young
    Departments of Radiology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 02115, USA.
  • Huai Chen
    Department of Radiology, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong 510120, China.
  • Xiaoyin Xu
    Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA. Electronic address: xxu@bwh.harvard.edu.

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