Progression analysis and stage discovery in continuous physiological processes using image computing

Lior Shamir, Salim Rahimi, Nikita Orlov, Luigi Ferrucci, Ilya G. Goldberg

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


We propose an image computing-based method for quantitative analysis of continuous physiological processes that can be sensed by medical imaging and demonstrate its application to the analysis of morphological alterations of the bone structure, which correlate with the progression of osteoarthritis (OA). The purpose of the analysis is to quantitatively estimate OA progression in a fashion that can assist in understanding the pathophysiology of the disease. Ultimately, the texture analysis will be able to provide an alternative OA scoring method, which can potentially reflect the progression of the disease in a more direct fashion compared to the existing clinically utilized classification schemes based on radiology. This method can be useful not just for studying the nature of OA, but also for developing and testing the effect of drugs and treatments. While in this paper we demonstrate the application of the method to osteoarthritis, its generality makes it suitable for the analysis of other progressive clinical conditions that can be diagnosed and prognosed by using medical imaging.

Original languageEnglish (US)
Article number107036
JournalEurasip Journal on Bioinformatics and Systems Biology
StatePublished - 2010
Externally publishedYes

ASJC Scopus subject areas

  • Medicine(all)
  • Computer Science(all)
  • Signal Processing
  • Statistics and Probability
  • General


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