2010
DOI: 10.7763/ijcte.2010.v2.206
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An Enhanced Implementation of Brain Tumor Detection Using Segmentation Based on Soft Computing

Abstract: Abstract-Image Segmentation is an important and challenging factor in the medical image segmentation. This paper describes segmentation method consisting of two phases. In the first phase, the MRI brain image is acquired from patients database, In that film artifact and noise are removed. After that Hierarchical Self Organizing Map (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 vec… Show more

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Cited by 38 publications
(44 citation statements)
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References 22 publications
(12 reference statements)
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“…M E Jain explained a wrapper based technique for image segmentation [6]. Various techniques using fuzzy logic have also been proposed like by P.Vasuda, S.Satheesh [7] but the drawback was more computation time required, T. Logeswari, M. Karnan [8]. Ming niwu,chia-chen Lin and chin-chenchang, proposed an algorithm which uses a clustering technique(k-means) to detect the brain tumor in MR images [9].…”
Section: Related Workmentioning
confidence: 99%
See 1 more Smart Citation
“…M E Jain explained a wrapper based technique for image segmentation [6]. Various techniques using fuzzy logic have also been proposed like by P.Vasuda, S.Satheesh [7] but the drawback was more computation time required, T. Logeswari, M. Karnan [8]. Ming niwu,chia-chen Lin and chin-chenchang, proposed an algorithm which uses a clustering technique(k-means) to detect the brain tumor in MR images [9].…”
Section: Related Workmentioning
confidence: 99%
“…So efficient and accurate techniques are required for brain tumor detection. In India, totally 80,271 people are affected by various types of tumor (2007 estimates) [2].…”
Section: Introductionmentioning
confidence: 99%
“…Image segmentation allows in prognosis of brain sicknesses and enables in quantitative evaluation of MR Images such as measuring accurate size and area of extracted portion. Exact measurements in brain diagnosis are difficult because of different shapes and sizes of tumor [2,3]. The K-means algorithm implements a divisive clustering and was first mentioned by means of Duda and Hart .…”
Section: Introductionmentioning
confidence: 99%
“…It's been concluded in the research of the majority of the western world that number of individuals who suffering and dying from brain tumors continues to be increased to 300 a year during past few decades [1]. More than 612,000 Americans will likely be identified as having a brain tumor and also over millions of people in the united states are living with brain tumors that have yet to be detected based on Nation's Brain Tumor Foundation (NBTF) and American Brain Tumor Association (ABTA) [2] where approximately 4300 children younger than age 20 will be informed they have primary brain tumors, which 3050 will likely be under age 15.…”
Section: Introductionmentioning
confidence: 99%