Automatic and semi-automatic approaches for arteriolar-to-venular computation in retinal photographs

Ana Maria Mendonça, Beatriz Remeseiro, Behdad Dashtbozorg, Aurélio Campilho

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

2 Citations (Scopus)


The Arteriolar-to-Venular Ratio (AVR) is a popular dimensionless measure which allows the assessment of patients’ condition for the early diagnosis of different diseases, including hypertension and diabetic retinopathy. This paper presents two new approaches for AVR computation in retinal photographs which include a sequence of automated processing steps: vessel segmentation, caliber measurement, optic disc segmentation, artery/vein classification, region of interest delineation, and AVR calculation. Both approaches have been tested on the INSPIRE-AVR dataset, and compared with a ground-truth provided by two medical specialists. The obtained results demonstrate the reliability of the fully automatic approach which provides AVR ratios very similar to at least one of the observers. Furthermore, the semi-automatic approach, which includes the manual modification of the artery/vein classification if needed, allows to significantly reduce the error to a level below the human error.
Original languageEnglish
Title of host publicationMedical Imaging 2017 Computer-Aided Diagnosis, 13-16 February 2017, Orlando, Florida
EditorsNicholas A. Petrick, Samuel G. Armato
Number of pages7
ISBN (Electronic)9781510607149
ISBN (Print)9781510607132
Publication statusPublished - 1 Mar 2017
Event2017 SPIE Medical Imaging: Image Processing - Renaissance Orlando at Sea World/Orlando, Orlando, United States
Duration: 11 Feb 201716 Feb 2017

Publication series

NameProceedings of SPIE
PublisherSociety of Photo-Optical Instrumentation Engineers
ISSN (Print)1605-7422
ISSN (Electronic)2410-9045
NameProgress in Biomedical optics and Imaging
PublisherSociety of Photo-Optical Instrumentation Engineers


Conference2017 SPIE Medical Imaging
CountryUnited States


  • Arteriolar-to-Venular Ratio
  • Artery/Vein classification
  • Retinal images
  • Vessel Segmentation


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