Ulcerative Colitis Diagnosis Based on Artificial Intelligence System

مرض التهاب القولون التقرحي هو تهيج في القولون الذي يرتبط في كثير من الأحيان مع العدوى ونقص المناعة. يكون جدار القولون للشخص مصاب بالالتهاب دائمًا أكثر سماكة من المعتاد. قد يكون مرض التهاب القولون التقرحي مهدد للحياة ويؤدي إلى الموت إذا لم يتم اكتشافه مبكرًا. الاكتشاف المبكر لهذا المرض مهم للغاية لبدء العلاج المناسب. في هذا البحث، تم تقديم شبكة العصبية الاصطناعية للكشف عن مرض التهاب القولون التقرحي وفقًا لمجموعة البيانات النظرية التي تم إنشاؤها بواسطة المعايير. تم تدريب الشبكة باستخدام خوارزمية Levenberg-Marquardt. أفضل اداء للشبكة كان حيث نسبة الخطأ تساوي 1.9947×10-24   للنظام الذي عدد خلاياه العصبية = 4.Ulcerative colitis (UC) disease is irritation of the colon that is frequently related to infection and immune compromise. The wall of the colon with inflammation is always thicker than normal. UC may be life-threatening and lead to death if not detected early. Early detection of this disease is very important to initiate appropriate treatment. In this paper, the Artificial Neural Network (ANN) applied to detect the UC according to a theoretical dataset generated by the criteria of UC. The Levenberg-Marquardt (LM) algorithm has trained the single hidden layer ANN. The best behaviour is equal to 1.9947×10-24for the system which the number of neurons =4

Detection of Ulcerative Colitis Severity and Enhancement of Informative Frame Filtering Using Texture Analysis in Colonoscopy Videos

There are several types of disorders that affect our colon’s ability to function properly such as colorectal cancer, ulcerative colitis, diverticulitis, irritable bowel syndrome and colonic polyps. Automatic detection of these diseases would inform the endoscopist of possible sub-optimal inspection during the colonoscopy procedure as well as save time during post-procedure evaluation. But existing systems only detects few of those disorders like colonic polyps. In this dissertation, we address the automatic detection of another important disorder called ulcerative colitis. We propose a novel texture feature extraction technique to detect the severity of ulcerative colitis in block, image, and video levels. We also enhance the current informative frame filtering methods by detecting water and bubble frames using our proposed technique. Our feature extraction algorithm based on accumulation of pixel value difference provides better accuracy at faster speed than the existing methods making it highly suitable for real-time systems. We also propose a hybrid approach in which our feature method is combined with existing feature method(s) to provide even better accuracy. We extend the block and image level detection method to video level severity score calculation and shot segmentation. Also, the proposed novel feature extraction method can detect water and bubble frames in colonoscopy videos with very high accuracy in significantly less processing time even when clustering is used to reduce the training size by 10 times

Pacific Symposium on Biocomputing 2023

The Pacific Symposium on Biocomputing (PSB) 2023 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2023 will be held on January 3-7, 2023 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference.PSB 2023 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology.The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputing's 'hot topics.' In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field