MRI brain tumor detection using optimal possibilistic fuzzy C-means clustering algorithm and adaptive k-nearest neighbor classifier-Reference-Cited by-同舟云学术

MRI brain tumor detection using optimal possibilistic fuzzy C-means clustering algorithm and adaptive k-nearest neighbor classifier

Published:2020-09-01 Issue:2 Volume:12 Page:2867-2880
ISSN:1868-5137
Container-title:Journal of Ambient Intelligence and Humanized Computing
language:en
Short-container-title:J Ambient Intell Human Comput

Author:

Kumar D. Maruthi,Satyanarayana D.,Prasad M. N. Giri

Publisher

Springer Science and Business Media LLC

Subject

General Computer Science

Link

https://link.springer.com/content/pdf/10.1007/s12652-020-02444-7.pdf

Reference34 articles.

1. Alagarsamy S, Kamatchi K, Govindaraj V, Zhang YD, Thiyagarajan A (2019) Multi-channeled MR brain image segmentation: a new automated approach combining BAT and clustering technique for better identification of heterogeneous tumors. Biocybern Biomed Eng 39(4):1005–1035

2. Amin J, Sharif M, Yasmin M, Fernandes SL (2017) A distinctive approach in brain tumor detection and classification using MRI. Pattern Recogn Lett. https://doi.org/10.1016/j.patrec.2017.10.036

3. Bahadure NB, Ray AK, Thethi HP (2017) Image analysis for MRI based brain tumor detection and feature extraction using biologically inspired BWT and SVM. Int J Biomed Imaging 2017:9749108. https://doi.org/10.1155/2017/9749108

4. Binsy T, Madhu N (2012) Comparative analysis of fuzzy clustering algorithms in data mining. Int J Adv Res Comput Sci Electron Eng 1(7):221

5. Chanchlani A, Chaudhari M, Shewale B, Jha A (2017) Tumor detection in brain MRI using clustering and segmentation algorithm. Imp J Interdiscip Res 3(5):2395–4396

Cited by 50 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Advancements in brain tumor identification: Integrating synthetic GANs with federated-CNNs in medical imaging analysis;Alexandria Engineering Journal;2024-10

2. A Unified Pipeline for Simultaneous Brain Tumor Classification and Segmentation Using Fine-Tuned CNN and Residual UNet Architecture;Life;2024-09-10

3. Brain tumor classification for combining the advantages of multilayer dense net‐based feature extraction and hyper‐parameters tuned attentive dual residual generative adversarial network classifier using wild horse optimization;NMR in Biomedicine;2024-08-28

4. A novel brain tumor segmentation and classification model using deep neural network over MRI-flair images;Multimedia Tools and Applications;2024-07-04

5. Dual path parallel hierarchical diagnosis model for intracranial tumors based on multi-feature entropy weight;Computers in Biology and Medicine;2024-05