Detecting Cancer in Gastrointestinal Images using MATLAB

A. Srujan, R. Srija, Suraj Sara, S. Sahithi, V. Krishna, A. M. Baradwaj
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Abstract

This paper deals with the detection of cancer from gastrointestinal images. Cancer detection is the most adequate field of implementation in bio-medical domains. At first, the several capabilities have been recognized to automate the process of identification of cancer and also upscale the accuracy rates over alternative diagnostic techniques. The methods that presently exist to diagnose cancer are not working constructively on all kinds of images, especially poor-quality images such as images with too much noise. And also, most of the available techniques have completely ignored the effective use of object segmentation in gastrointestinal images. So, to subdue the limitations of previous techniques, a new approach has been proposed in this paper. Impressive results have been generated by using the features of image processing in MATLAB with the help of images from kvasir dataset. The image processing techniques used for diagnostic test pictures might facilitate the sight of distinctive options in cancer detection.
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利用MATLAB检测胃肠道图像中的肿瘤
本文讨论了从胃肠道图像中检测癌症的方法。肿瘤检测是生物医学领域中应用最充分的领域。首先,人们已经认识到,这几种能力可以使癌症识别过程自动化,并且比其他诊断技术的准确率更高。目前现有的诊断癌症的方法并不能对所有类型的图像都有效,尤其是质量差的图像,比如噪声太大的图像。而且,现有的大多数技术完全忽略了目标分割在胃肠道图像中的有效应用。因此,为了克服以往技术的局限性,本文提出了一种新的方法。利用MATLAB中图像处理的特点,结合kvasir数据集的图像,得到了令人印象深刻的结果。用于诊断测试图片的图像处理技术可能有助于在癌症检测中看到独特的选择。
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