Brain Image Classification Using the Hybrid CNN Architecture

2021 ◽  
pp. 329-336
Author(s):  
Pranati Satapathy ◽  
Sateesh Kumar Pradhan ◽  
Sarbeswara Hota ◽  
Rashmi Ranjan Mahakud
Keyword(s):  
Image Classification ◽  
Brain Image

scholarly journals Inception Architecture for Brain Image Classification

2021 ◽  
Vol 1964 (7) ◽  
pp. 072022
Author(s):  
R Tamilarasi ◽  
S Gopinathan
Keyword(s):  
Image Classification ◽  
Brain Image

scholarly journals Online Brain Image Repositories for Brain Disease Detection

2019 ◽  
Vol 9 (2S2) ◽  
pp. 864-867
Keyword(s):  
Image Analysis ◽  
Image Classification ◽  
Disease Detection ◽  
Tumor Type ◽  
File Format ◽  
Tissue Segmentation ◽  
Brain Image ◽  
Clinical Dataset ◽  
Skull Stripping ◽  
Brain Image Analysis

Brain image analysis is an emerging area of researchers to improve the diagnosis process more fast and accurate. One of the difficulties is getting the clinical dataset of patients from hospitals to test the performance of the proposed methods. Therefore, numerous online brain image repositories are available to promote the research works. It has manually segmented results to evaluate the accuracy of the developed methods. Each repository has different file format and focused on different problems like skull stripping, tumorous image classification, tumor type categorization, tissue segmentation and tumor with substructure segmentation. This paper gives detail information on famous brain datasets with their purpose.

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