Longitudinal Evaluation of Structural Changes in Frontotemporal Dementia Using Artificial Neural Networks

  • R. Sheela Kumari
  • Tinu Varghese
  • C. Kesavadas
  • N. Albert Singh
  • P. S. Mathuranath
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 247)


Automatic Segmentation of Magnetic Resonance (MR) Images plays an important role in medical image processing. Segmentation is the process of extracting the brain tissue components such as grey matter (GM), white matter (WM) and cerebrospinal fluids (CSF). The volumetric analysis of the segmented tissues helps in determining the amount of GM loss in specific disease pathology. Among the various segmentation techniques, fuzzy c means (FCM) is the most widely used one. The performance of traditional FCM is considerably reduces in noisy MR images. However, in the clinical analysis accurate segmentation of MR image is very important and crucial for the early diagnosis and prognosis. This paper put forward an Artificial Neural Network based segmentation to map the longitudinal structural changes overtime in Frontotemporal dementia (FTD) subjects that could be a better cue to impending behavioural changes. Our proposed approach has achieved an average classification accuracy of 96.7%, 96.4% and 97.96% for GM, WM and CSF respectively.


Magnetic Resonance (MRI) fuzzy C means (FCM) Artificial Neural Network (ANN) Frontotemporal Dementia (FTD) 


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Copyright information

© Springer International Publishing Switzerland 2014

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 TechnologyTrivandrumIndia
  2. 2.Noorul Islam UniversityThuckalayIndia
  3. 3.Department of NeurologySree Chitra Tirunal Institute for Medical Science and TechnologyTrivandrumIndia
  4. 4.Department of NeurologyNational Institute of Medical Sciences and Mental Health and NeurosciencesBangloreIndia

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