Automated Segmentation and Clinical Information on Dementia Diagnosis

A. Conci, A. Plastino, A. S. Souza, C. S. Kubrusly, D. M. Saade, F. L. Seixas

Abstract

This work intends to predict the clinical dementia rating (CDR) based on human brain volumetric segmentation measures from magnetic resonance (MR) images. These brain measures were extracted using an automated image segmentation method based on morphometry study and considering brain anatomical atlas. The prediction was achieved by Bayesian classifier. The classifier training was performed on 371 individuals from Open Access Series of Imaging Studies (OASIS) dataset. MR images and clinical information (including the Clinical Dementia Rating score) of each case are available on OASIS dataset. Experimentation results were assessed using true-positive rate. The final purpose of this work is to design a computer-aided diagnostic system that could be able to detect precociously neurodegenerative disorders, allowing early therapeutic interventions.

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Paper Citation


in Harvard Style

Conci A., Plastino A., Souza A., Kubrusly C., Saade D. and Seixas F. (2009). Automated Segmentation and Clinical Information on Dementia Diagnosis . In Proceedings of the 1st International Workshop on Medical Image Analysis and Description for Diagnosis Systems - Volume 1: Workshop MIAD, (BIOSTEC 2009) ISBN 978-989-8111-77-7, pages 33-42. DOI: 10.5220/0001811200330042


in Bibtex Style

@conference{workshop miad09,
author={A. Conci and A. Plastino and A. S. Souza and C. S. Kubrusly and D. M. Saade and F. L. Seixas},
title={Automated Segmentation and Clinical Information on Dementia Diagnosis},
booktitle={Proceedings of the 1st International Workshop on Medical Image Analysis and Description for Diagnosis Systems - Volume 1: Workshop MIAD, (BIOSTEC 2009)},
year={2009},
pages={33-42},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001811200330042},
isbn={978-989-8111-77-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 1st International Workshop on Medical Image Analysis and Description for Diagnosis Systems - Volume 1: Workshop MIAD, (BIOSTEC 2009)
TI - Automated Segmentation and Clinical Information on Dementia Diagnosis
SN - 978-989-8111-77-7
AU - Conci A.
AU - Plastino A.
AU - Souza A.
AU - Kubrusly C.
AU - Saade D.
AU - Seixas F.
PY - 2009
SP - 33
EP - 42
DO - 10.5220/0001811200330042