<p>A team of researchers from IIT Guwahati has come up with an automated Artificial Intelligence-based system to detect colorectal cancer.</p>.<p>The system has been designed by Manas Kamal Bhuyan, a professor of electronics and electrical engineering department of the institute, along with scientists from renowned research institutes around the world. </p>.<p>“We have developed an innovative automated system that can help the physician rapidly and accurately detect colorectal cancer from colonoscopy images,” said a statement quoting Bhuyan on Thursday. </p>.<p>The statement said colorectal cancer is the third most common type of cancer among men and women in India, but if detected early it can be cured. </p>.<p>The commonly used technique to detect colorectal cancer is colonoscopy, in which the specialist – physician, gastroenterologist or oncologist – visually inspects the image obtained by the camera inserted into the colon of the subject. In the current manual approach for colonoscopy examination by physicians, observation bias may sometimes lead to an erroneous diagnosis.</p>.<p>“This method is important because it prevents delays in diagnosis. Furthermore, currently, doctors waste a lot of time on manually analysing images, valuable time that can be spent on devising management and treatment strategies,” it said. </p>.<p>During the visual examination, specialists check for the presence and features of abnormal tissue growths (polyps) including shape, surface structure and contour to classify them into different categories (neoplastic and non-neoplastic). The multi-institutional team extracted the shape, texture and color components through artificial intelligence algorithms using different filters, it said. </p>.<p>The results of their work have recently been published in a prestigious journal belonging to the Nature group - Scientific Reports. The paper has been co-authored by Dr. Kangkana Bora of Cotton University, Guwahati, Dr. Kunio Kasugai of Aichi Medical University, Japan. Prof. Zhongming Zhao from the University of Texas, Health Science Centre, Houston, USA, and Dr. Saurav Mallik of Harvard University, USA have also contributed to the study, said the statement.</p>
<p>A team of researchers from IIT Guwahati has come up with an automated Artificial Intelligence-based system to detect colorectal cancer.</p>.<p>The system has been designed by Manas Kamal Bhuyan, a professor of electronics and electrical engineering department of the institute, along with scientists from renowned research institutes around the world. </p>.<p>“We have developed an innovative automated system that can help the physician rapidly and accurately detect colorectal cancer from colonoscopy images,” said a statement quoting Bhuyan on Thursday. </p>.<p>The statement said colorectal cancer is the third most common type of cancer among men and women in India, but if detected early it can be cured. </p>.<p>The commonly used technique to detect colorectal cancer is colonoscopy, in which the specialist – physician, gastroenterologist or oncologist – visually inspects the image obtained by the camera inserted into the colon of the subject. In the current manual approach for colonoscopy examination by physicians, observation bias may sometimes lead to an erroneous diagnosis.</p>.<p>“This method is important because it prevents delays in diagnosis. Furthermore, currently, doctors waste a lot of time on manually analysing images, valuable time that can be spent on devising management and treatment strategies,” it said. </p>.<p>During the visual examination, specialists check for the presence and features of abnormal tissue growths (polyps) including shape, surface structure and contour to classify them into different categories (neoplastic and non-neoplastic). The multi-institutional team extracted the shape, texture and color components through artificial intelligence algorithms using different filters, it said. </p>.<p>The results of their work have recently been published in a prestigious journal belonging to the Nature group - Scientific Reports. The paper has been co-authored by Dr. Kangkana Bora of Cotton University, Guwahati, Dr. Kunio Kasugai of Aichi Medical University, Japan. Prof. Zhongming Zhao from the University of Texas, Health Science Centre, Houston, USA, and Dr. Saurav Mallik of Harvard University, USA have also contributed to the study, said the statement.</p>
