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Scanned Image Segmentation and Detection Using MSER Algorithm

E. Madura, P. Sajithira, M. Sandhiya, M. Selvapriya

Abstract


Today’s modern medical imaging research faces the challenge of detecting brain tumour, skin cancer through scanned images. Normally, to produce images of soft tissue of human body, scanned images are used by experts. It is used for analysis of human organs to replace surgery. The brain tumour detection, or to find skin cancer image segmentation is required. For this purpose, the brain or skin is partitioned into two distinct regions. This is considered to be one of the most important but difficult part of the process of detecting brain tumour and skin cancer. Hence, it is highly necessary that segmentation of the scanned images must be done accurately before asking the computer to do the exact diagnosis. Earlier, a variety of algorithms were developed for segmentation of scanned images by using different tools and techniques. However, this paper presents a comprehensive review of the methods and techniques used to detect brain tumour and cancer and etc.., through scanned image segmentation. Lastly, the paper concludes with a concise discussion and provides a direction toward the upcoming trend of more advanced research studies on brain image segmentation and Tumour and Cancer detection.


Keywords


Scanned Image, Embedded Noise, Median Filter, MSER Algorithm.

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References


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