Automated classification of dementia subtypes from post-mortem cortex images

David Cornforth, Herbert Jelinek

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

5 Scopus citations

Abstract

We apply automated classification techniques to determine whether dementia is associated with changes in the physical structure of small blood vessels in the brain. A successful predictive model would imply such an association. The use of measures derived from fractal analysis, and the use of machine learning classification algorithms, allow exploration of highly complex relationships. Results suggest that although physiological differences are difficult to detect, and vary between different areas of brain tissue, there is evidence for such an association. If such changes can be detected from images of post mortem tissue, this implies that investigation of the medical significance of these changes could provide greater understanding of this class of diseases.

Original languageBritish English
Title of host publicationAI 2005
Subtitle of host publicationAdvances in Artificial Intelligence - 18th Australian Joint Conference on Artificial Intelligence, Proceedings
Pages1285-1288
Number of pages4
DOIs
StatePublished - 2005
Event18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence - Sydney, Australia
Duration: 5 Dec 20059 Dec 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3809 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th Australian Joint Conference on Artificial Intelligence, AI 2005: Advances in Artificial Intelligence
Country/TerritoryAustralia
CitySydney
Period5/12/059/12/05

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