Identification of Tumour from Ct Images using Contour Plot and Gui
S Priya1, R Nischal2, Mithrashree Sekar3, Harshit Yadav4
1S Priya, Assistant professor CSE (O.G), SRM Institute of technology, Ramapuram.
2R Nischal, BTECH CSE (3rd year), SRM Institute of technology, Ramapuram.
3Mithrashree Sekar, BTECH CSE (3rd year), SRM Institute of technology, Ramapuram.
4Harshit Yadav , BTECH CSE (3rd year), SRM Institute of technology, Ramapuram.
Manuscript received on November 11, 2019. | Revised Manuscript received on November 23, 2019. | Manuscript published on 30 November, 2019. | PP: 4306-4309 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8106118419/2019©BEIESP | DOI: 10.35940/ijrte.D8106.118419
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The healthcare sector in terms of medical imaging is picking up significance with people preferring automation which is eventually fast and effective in determination of the problem which can give understanding to the picture way superior than to the human eyes. Brain tumour is a condition where it ranks second in terms of cancer related deaths for men and ranks at fifth place for women over the age group of 20 to 39.Brain tumours are extremely agonizing and it ends up being significant reasons for various ailments if not cured properly. Analysis of the tumour and its type is a very significant part in its treatment. Tumours are of two types benign and malignant, Distinguishing the type of tumour place an important role in its treatment .The principal reason for the rise in the number of malignancy patients is due to numbness towards its treatment at early stages. The whole idea of this paper is to create an algorithm that could educate the patient about the tumour with the help of image processing techniques. The basic image processing techniques are used to obtain the background by the sharpening the image, reduction of noise together with morphological functions such as erosion and dilation. To obtain the tumour images we are intended to subtract the background of the image and their negatives from the various set of images. Plotting contour and c-label of the tumour and its boundary provides us with information related to the tumour that can help in a better visualization in diagnosing cases. This procedure helps in recognizing the size, shape and location of the tumour. This in turn helps the doctors as well as the patient to comprehend the complexity of tumour with colour labelling for different levels of elevation. A graphical user interface would help the medicinal staff to access the reports and also find the background and contour plot of tumour within their finger tips.
Keywords: Contour plot, Dilation, Erosion, Image processing, Noise removal, 3D Image.
Scope of the Article: 3D Printing.