MRI Brain Tumor Segmentation Using Automatic 3D Blob Method

  • B. JyothiEmail author
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 898)


Brain tumor surgery totally depends on accurate detection and segmentation of a brain tumor. For this, 3D detection is very necessary to know the actual depth of a tumor. This paper presents the segmentation and detection of brain tumors based on 3D blobs. We detect and segment the single and multiple tumors from 2 to 31,738 mm3 in volume. The proposed method uses Laplacian of Gaussian (LoG) filtering, skull removal, affine adaptation and shape pruning. The LoG finds 3D blobs and extremely sensitive to minute abnormalities per scan. The proposed approach has 90.70 and 96.40% detection rates and a typical end running time of less than 2 min. The results exhibit that it is possible to categorize normal and abnormal.


Brain tumor MRI brain asymmetry 3D independent LoG 


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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of ECEMalla Reddy College of Engineering and TechnologyHyderabadIndia

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