Automated delineation of calcified vessels in mammography by tracking with uncertainty and graphical linking techniques

Jie Zhi Cheng, Chung Ming Chen, Elodia B. Cole, Etta D. Pisano, Dinggang Shen

Research output: Contribution to journalArticle

26 Citations (Scopus)

Abstract

As a potential biomarker for women's cardiovascular and chronic kidney diseases, breast arterial calcification (BAC) in mammography has become an emerging research topic in recent years. To provide more objective measurement for vascular structures with calcium depositions in mammography, a new computerized method is introduced in this paper to delineate the calcified vessels. Specifically, we leverage two underlying cues, namely calcification and vesselness, into a multiple seeded tracking with uncertainty scheme. This new vessel-tracking scheme generates plenty of sampling paths to describe the complicated topology of the vascular structures with calcium depositions. A compiling and linking process is further carried out to organize the sampling paths together to be the vessel segments that likely belong to the same vessel tract. The proposed method has been evaluated on 63 mammograms, by comparison with manual delineations from two experts using various assessment metrics. The experiment results confirm the efficacy and stability of the proposed method, and also indicate that the proposed method can be potentially used as a convenient BAC measurement tool in replacement of the trivial and tedious manual delineation tasks.

Original languageEnglish
Article number6290397
Pages (from-to)2143-2155
Number of pages13
JournalIEEE Transactions on Medical Imaging
Volume31
Issue number11
DOIs
Publication statusPublished - 2012 Dec 1
Externally publishedYes

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Keywords

  • Breast arterial calcification (BAC)
  • curve linking
  • mammography
  • uncertainty
  • vessel tracking

ASJC Scopus subject areas

  • Software
  • Radiological and Ultrasound Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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