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Identification of Fronto-Temporal Dementia Using Neural Network

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International Conference on Intelligent Computing and Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 846))

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Abstract

Fronto-Temporal Dementia (FTD) affects the behavior, cognition, and memory retention capacity of the affected people. This study focuses on preprocessing the acquired MRI images and transforming RGB to grayscale image, detection of edge by applying Sobel algorithm, segmenting the image, extraction of features, and feeding to the classifier for classification.

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References

  1. N. Sandhya and Dr. S. Nagarajan, Frontotemporal Dementia—A Supervised Learning Approach, Springer ERCICA 2015 Vol 3, https://doi.org/10.1007/978-981-10-0287-8.

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Correspondence to N. Sandhya .

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Sandhya, N., Nagarajan, S. (2019). Identification of Fronto-Temporal Dementia Using Neural Network. In: Bhaskar, M., Dash, S., Das, S., Panigrahi, B. (eds) International Conference on Intelligent Computing and Applications. Advances in Intelligent Systems and Computing, vol 846. Springer, Singapore. https://doi.org/10.1007/978-981-13-2182-5_6

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