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A Genetic Algorithm Optimized Artificial Neural Network for the Segmentation of MR Images in Frontotemporal Dementia

  • R. Sheela Kumari
  • Tinu Varghese
  • C. Kesavadas
  • N. Albert Singh
  • P. S. Mathuranath
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8298)

Abstract

Frontotemporal Dementia (FTD) is an early onset dementia with atrophy in frontal and temporal regions. The differential diagnosis of FTD remains challenging because of the overlapping behavioral symptoms in patients, which have considerable overlap with Alzheimer’s disease (AD). Neuroimaging analysis especially Magnetic Resonance Image Imaging (MRI) has opened up a new window to identify, and track disease process and progression. In this paper, we introduce a genetic algorithm (GA) tuned Artificial Neural Network (ANN) to measure the structural changes over a period of 1year. GA is a heuristic optimization method based on the Darwin’s principle of natural evolution. The longitudinal atrophy patterns obtained from the proposed approach could serve as a predictor of impending behavioral changes in FTD subjects. The performance of our computerized scheme is evaluated and compared with the ground truth information. Using the proposed approach, we have achieved an average classification accuracy of 95.5 %, 96.5% and 98% for GM, WM and CSF respectively.

Keywords

Frontotemporal Dementia (FTD) Alzheimer’s disease (AD) Magnetic Resonance Imaging (MRI) Genetic algorithm (GA) Artificial Neural Network (ANN) 

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Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • R. Sheela Kumari
    • 1
  • Tinu Varghese
    • 2
  • C. Kesavadas
    • 3
  • N. Albert Singh
    • 2
  • P. S. Mathuranath
    • 4
  1. 1.Sree Chitra Tirunal Institute for Medical Science and Technology TrivandrumIndia
  2. 2.Noorul Islam UniversityIndia
  3. 3.Department of RadiologySree Chitra Tirunal Institute for Medical Science and TechnologyTrivandrumIndia
  4. 4.Department of NeurologyNational Institute of Mental Health and NeurosciencesBangloreIndia

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