Novel Approach for Brain Tumor Detection Based on Naive Bayes Classification

被引:12
作者
Kaur, Gurkarandesh [1 ]
Oberoi, Ashish [1 ]
机构
[1] RIMT Univ, Dept CSE, Mandi Gobindgarh, India
来源
DATA MANAGEMENT, ANALYTICS AND INNOVATION, ICDMAI 2019, VOL 1 | 2020年 / 1042卷
关键词
Brain tumor; Clustering; MRI; Morphological scanning; Naive Bayes NBC-BTD model;
D O I
10.1007/978-981-32-9949-8_31
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The brain tumor detection is the approach which can detect the tumor portion from the MRI image. To detect tumor from the image various techniques has been proposed in the previous times. The technique which is adapted in research work is based upon morphological scanning, clustering, and Naive Bayes classification. The morphological scanning will scan the input image and clustering will cluster similar and dissimilar patches from image then Naive Bayes classifier spot the tumor portion from magnetic resonance imaging. The advance algorithm is implemented in MATLAB and results are analyzed in terms of PSNR, MSE accuracy, and fault detection and also calculate overlapping area with dice coef. The proposed method has been tested on data set with more than 25 slide scanned images. This proposed method achieved accuracy with 86% best cell detection.
引用
收藏
页码:451 / 462
页数:12
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