A fully automated system for retinal vessel tortuosity diagnosis using scale dependent vessel tracing and grading

Qin Li, Jia You, Jinghua Wang, Allan Wong

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

3 Citations (Scopus)

Abstract

A fully automated system for retinal vessel tortuosity system diagnosis is proposed in this paper. Our diagnosis system includes: (1) automated retinal vessel segmentation and tracing; (2) computerized tortuosity grading. In recent years, many works have been done on computerized diagnosis of retinal vessel tortuosity. But there are few researchers working on a fully automated system. The major difficulties in producing a fully automated system includes: (1) automated tracing of vessels to identify each individual branch; (2) global tortuosity grading of a retinal vessel image. In this paper, we propose a scheme to trace and grade retinal vessels using scale (variant widths and lengths of vessel segments) dependent techniques. The experimental results show that our system is useful in clinical applications.
Original languageEnglish
Title of host publicationProceedings of the 23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010
Pages221-225
Number of pages5
DOIs
Publication statusPublished - 1 Dec 2010
Event23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010 - Perth, Australia
Duration: 12 Oct 201015 Oct 2010

Conference

Conference23rd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2010
CountryAustralia
CityPerth
Period12/10/1015/10/10

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Computer Science Applications

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