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Aim of presenting this paper is to detect the brain tumor by using thresholding and watershed algorithm. In order to find the correct size, shape, limit extraction and area of tumor Brain tumor identification can be helpful. To detect and segment brain tumor there are three stages. For detection of tumor based on segmentation there is an efficient algorithm. For detection of tumor in scanned image, firstly, enhancement process of scanned image and morphological operators are applied. Once edges are detected , operators are applied so that the boundaries can be extracted and the size of tumors can be found.
The brain is a delicate, sensitive, irreplaceable and lightweight tissue. It is a steady place for examples to enter and settle among one another. A tumor is essentially a swelling of a part of the body that becomes a wild force that governs the typical forces of its development. Brain tumor is a gathering of irregular cells that becomes either inside the mind or on the other hand around the brain. All healthy brain cells could be destroy by tumors. It can indirectly, adversely harm the healthy brain cells by swarming into different parts of the brain and causing aggravation, brain swelling and inducing pressure inside the skull.
Exact measurements in brain tumor diagnosis are very troublesome due to assorted shapes, sizes and tumor appearance. Tumors may develop unexpectedly, leading to adjacent neighboring. In addition, the organization also provides a large number of unusual structures for solid tissue. In this paper, we will use a division related to morphological activities to establish a three-dimensional segmentation process for brain tumors.
In this paper, description of Brain tumor detection and segmentation by using Watershed and thresholding algorithm has been put down.
The test results appeared in the upper region, and the canny edge detection operator showed the accuracy of the tumor and found the boundary of the tumor. The shape and size of the tumor are depicted.