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On bloodvessel branching analysis for the detection of Alzheimer's disease

On bloodvessel branching analysis for the detection of Alzheimer's disease
On bloodvessel branching analysis for the detection of Alzheimer's disease
Alzheimer’s Disease (AD) is increasingly prevalent in modern society and methods for its diagnosis are only just starting to emerge. Given images of brain tissue, we show how Alzheimer’s disease can be detected from the branching structures of blood vessels. This is achieved by a new approach which counts the branching points and derives measures which are suited to the analysis of small branching structures. The measures are formulated to be rotation, scale and position invariant and are deployed in tandem with more standard measures. Analysis on a database comprised of brain tissue samples from subjects who are normal, with Alzheimer’s and age matched normal has shown capability to classify correctly images of brain tissue from subjects afflicted with Alzheimer’s disease.
Sahrim, Musab
9f93c355-4ebe-4ada-91a9-6eed03aa288e
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Carare, Roxana O.
0478c197-b0c1-4206-acae-54e88c8f21fa
Sahrim, Musab
9f93c355-4ebe-4ada-91a9-6eed03aa288e
Nixon, Mark S.
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Carare, Roxana O.
0478c197-b0c1-4206-acae-54e88c8f21fa

Sahrim, Musab, Nixon, Mark S. and Carare, Roxana O. (2014) On bloodvessel branching analysis for the detection of Alzheimer's disease. 18th Annual Conference in Medical Image Understanding and Analysis 2014, United Kingdom. 09 - 11 Jul 2014. 6 pp .

Record type: Conference or Workshop Item (Poster)

Abstract

Alzheimer’s Disease (AD) is increasingly prevalent in modern society and methods for its diagnosis are only just starting to emerge. Given images of brain tissue, we show how Alzheimer’s disease can be detected from the branching structures of blood vessels. This is achieved by a new approach which counts the branching points and derives measures which are suited to the analysis of small branching structures. The measures are formulated to be rotation, scale and position invariant and are deployed in tandem with more standard measures. Analysis on a database comprised of brain tissue samples from subjects who are normal, with Alzheimer’s and age matched normal has shown capability to classify correctly images of brain tissue from subjects afflicted with Alzheimer’s disease.

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Published date: July 2014
Venue - Dates: 18th Annual Conference in Medical Image Understanding and Analysis 2014, United Kingdom, 2014-07-09 - 2014-07-11
Organisations: Vision, Learning and Control

Identifiers

Local EPrints ID: 367020
URI: http://eprints.soton.ac.uk/id/eprint/367020
PURE UUID: e4debf4f-d521-454f-afa4-e10e0165eb3a
ORCID for Mark S. Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 24 Jul 2014 16:20
Last modified: 06 Jun 2018 13:18

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Contributors

Author: Musab Sahrim
Author: Mark S. Nixon ORCID iD

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