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Logeswari, T.
- An Improved Implementation of Brain Tumor Detection Using Segmentation Based on Self Organizing Map
Authors
1 Dept. of Computer Science, Mother Teresa Women’s University, Kodaikanal, IN
2 Department of Computer Science & Engineering, Tamilnadu College of Engineering, IN
Source
Artificial Intelligent Systems and Machine Learning, Vol 2, No 2 (2010), Pagination: 12-18Abstract
Image Segmentation is an important and challenging factor in the medical image segmentation. This paper describes segmentation method consist of two phases. The first phase, describe MRI brain image is acquired from patient’s database, In that film artifact and noise are removed after that HSOM is applied for image segmentation. The HSOM is the extension of the conventional self organizing map used to classify the image row by row. In this lowest level of weight vector, a higher value of tumor pixels, computation speed is achieved by the HSOM with vector quantization.Keywords
HSOM, Image Analysis, Segmentation,, Tumor Detection.
- Automatic Brain Tumor Detection through MRI – A Survey
Authors
1 Department of Computer Science, New Horizon College, Kasturai Nagar, Bangalore, IN
Source
Digital Image Processing, Vol 8, No 9 (2016), Pagination: 303-305Abstract
This review paper, intents to analyze and compare the diverse methods of automatic detection of brain tumor through Magnetic Resonance Image (MRI) used in different stages of Computer Aided Detection System (CAD).Tumor detection and segmentation are two key problems in research undertaken on brain diagnosis. The main techniques for detection and segmentation are clustering based, knowledge-based, Model-based, level-set evolution, or combination of them. In particular, the Preprocessing, Enhancement and Segmentation are studied and compared. Classification procedure used to obtain final results is also discussed. In Preprocessing and Enhancement stage, medical image is converted into standard format and is manipulated for noise reduction by background removal, edge sharpening, filtering process and removal of film artifacts. Segmentation determines the process of dividing an image into disjoint homogenous regions of a medical image. Classification helps to compare the system generated result with the radiologist report are studied and compared.