Automating measurement of renal interstitial fibrosis: Effect of colour spaces on quantification

Wei Keat Tey, Ye Chow Kuang, Joon Joon Khoo, Melanie Po-Leen Ooi, Serge Demidenko

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

2 Citations (Scopus)


The progression of chronic renal diseases is primarily measured by the extent of interstitial fibrosis and glomerulosclerosis in renal biopsies. The traditional method of interstitial fibrosis quantification uses visual evaluation, which presents high inter- and intra-observer variability. In this paper, we investigate automated quantification methods based on various colour spaces in renal biopsy images. The system identifies and extracts structures in the renal biopsy image based on the colour information presented by the image following a set of knowledge-based rules on the different structures in a microscopic renal biopsy image. The quantification results indicate that a hybrid method which incorporates different colour spaces to segment tissue structures achieves higher accuracy compared to thresholding or clustering methods. It reduces the error of single colour space methods by half, achieving a mean error of 6 percentage points.

Original languageEnglish
Title of host publication2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings (I2MTC 2016)
Subtitle of host publicationTaipei, Taiwan, 23-26 May 2016
EditorsAlessandra Flammini, Subhas Mukhopadhyay, Shervin Shirmohammadi
PublisherIEEE, Institute of Electrical and Electronics Engineers
Number of pages6
ISBN (Electronic)9781467392204
ISBN (Print)9781467392211
Publication statusPublished - 22 Jul 2016
EventIEEE International Instrumentation and Measurement Technology Conference 2016 - Taipei, Taiwan
Duration: 23 May 201626 May 2016
Conference number: 33rd (Proceedings)


ConferenceIEEE International Instrumentation and Measurement Technology Conference 2016
Abbreviated titleI2MTC 2016
Internet address


  • Medical image analysis
  • Renal fibrosis
  • Segmentation

Cite this