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Blood vessel feature description for detection of Alzheimers disease

Blood vessel feature description for detection of Alzheimers disease
Blood vessel feature description for detection of Alzheimers disease
We describe how image analysis can be used to detect the presence of Alzheimer’s disease. The data are images of brain tissue collected from subjects with and without Alzheimer’s disease. The analysis concentrates on the shape and structure of the blood vessels which are known to be affected by amyloid beta, whose drainage is affected by Alzheimer’s disease. The structure is analysed by a new approach which measures the influence of the blood vessels’ branching structures. Their density and tortuosity are analysed in conjunction with a boundary description derived using Fourier descriptors. These measures form a feature vector which is derived from the images of brain tissue, and the discrimination capability shows that it is possible to detect the presence of Alzheimer’s disease using these measures and in an automated way. These measures also show that shape information is influenced by the vessels’ branching
structure, as known to be consistent with Alzheimer’s disease evolution.
alzheimer's disease, medical image analysis, segmentation, shape description
317-322
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) Blood vessel feature description for detection of Alzheimers disease. 13th International Conference on Control, Automation, Robotics and Vision (ICARV), Singapore. 10 - 12 Dec 2014. pp. 317-322 .

Record type: Conference or Workshop Item (Other)

Abstract

We describe how image analysis can be used to detect the presence of Alzheimer’s disease. The data are images of brain tissue collected from subjects with and without Alzheimer’s disease. The analysis concentrates on the shape and structure of the blood vessels which are known to be affected by amyloid beta, whose drainage is affected by Alzheimer’s disease. The structure is analysed by a new approach which measures the influence of the blood vessels’ branching structures. Their density and tortuosity are analysed in conjunction with a boundary description derived using Fourier descriptors. These measures form a feature vector which is derived from the images of brain tissue, and the discrimination capability shows that it is possible to detect the presence of Alzheimer’s disease using these measures and in an automated way. These measures also show that shape information is influenced by the vessels’ branching
structure, as known to be consistent with Alzheimer’s disease evolution.

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Accepted/In Press date: 30 July 2014
Published date: December 2014
Venue - Dates: 13th International Conference on Control, Automation, Robotics and Vision (ICARV), Singapore, 2014-12-10 - 2014-12-12
Keywords: alzheimer's disease, medical image analysis, segmentation, shape description
Organisations: Vision, Learning and Control, Clinical & Experimental Sciences

Identifiers

Local EPrints ID: 374996
URI: https://eprints.soton.ac.uk/id/eprint/374996
PURE UUID: af7f71bf-4d44-434f-a274-accd13e6de18
ORCID for Mark S. Nixon: ORCID iD orcid.org/0000-0002-9174-5934

Catalogue record

Date deposited: 09 Mar 2015 13:15
Last modified: 06 Jun 2018 13:18

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