Segmentation Using Adaptive Fuzzy Clustering Based Atom Search Optimization of Magnetic Resonance Images for Early Detection of Alzheimer’s Disease
- DOI
- 10.2991/978-94-6463-136-4_82How to use a DOI?
- Keywords
- Alzheimer’s disease; pre-processing; DT; NLMSMJ; MGM dataset; MRI
- Abstract
Alzheimer’s Disease is a neurodegenerative condition affecting middle-aged to older peo-ple characterized by marked loss of memory, cerebral damage and helplessness. Early and correct detection can help doctors to plan the medication for the sufferer. As we know this disease is progressive and degenerative, the speed of the disease can slows down by ap-propriate treatment it also helps to protect against brain tissue damage. This work presents the practical methodology, pre-processing and segmentation steps which helps in the early detection of Alzheimer’s disease. The effective pre-processing of an image is done with the help of skull stripping as the first step, then normalized linear smoothing and median joint(NLSMJ) Filtering and segmentation is carried out with Adaptive Fuzzy Based Atom Searched Optimization. The presented technique is used on Local neuro-imaging MRI da-taset collected from MGM hospital.
- Copyright
- © 2023 The Author(s)
- Open Access
- Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
Cite this article
TY - CONF AU - Nirupama P. Ansingkar AU - Rita B. Patil AU - Rajmohan A. Pardeshi AU - Prapti D. Deshmukh PY - 2023 DA - 2023/05/01 TI - Segmentation Using Adaptive Fuzzy Clustering Based Atom Search Optimization of Magnetic Resonance Images for Early Detection of Alzheimer’s Disease BT - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022) PB - Atlantis Press SP - 931 EP - 942 SN - 2352-538X UR - https://doi.org/10.2991/978-94-6463-136-4_82 DO - 10.2991/978-94-6463-136-4_82 ID - Ansingkar2023 ER -