Identifying Tumor by Segmentation of Brain Images Using Combinatory Approach of Convolutional Neural Network and Biogeography Algorithm
Author:
Publisher
Springer Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-16-2248-9_8
Reference15 articles.
1. Chandra SK, Bajpai MK (2020) Fractional Crank-Nicolson finite difference method for benign brain tumor detection and segmentation. Biomed Signal Process Control 60. https://doi.org/10.1016/j.bspc.2020.102002
2. Filho PPR, da Silva Barros AC, Almeida JS, Rodrigues JPC, de Albuquerque VHC (2019) A new effective and powerful medical image segmentation algorithm based on optimum path snakes. Appl Soft Comput J 76:649–670
3. Brain tumor: introduction Cancer.Net. [online] https://www.cancer.net/cancer-types/brain-tumor/introduction. Accessed: 25/02/2019
4. Brain Tumors-Classifications, Symptoms, Diagnosis and Treatments. [Online]. Available: https://www.aans.org/Patients/Neurosurgical-Conditions-and-Treatments/Brain-Tumors
5. Deepa AR, Sam Emmanuel WR (2018) An efficient detection of brain tumor using fused feature adaptive firefly backpropagation neural network. Multim Tools Appl 1–16
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