SEI: Collaborative Research: Endoscopic Multimedia Information System (EMIS)

视频技术的进步正在被纳入今天的医疗实践。例如，各种类型的内窥镜用于结肠镜检查、上消化道内窥镜检查、肠镜检查、支气管镜检查和膀胱镜检查。此外，数量迅速增加的以前的开放式外科手术现在正在转变为内窥镜手术，包括胆囊切除术、供体肾的取出、结肠和胰腺肿瘤的切除、食管裂孔疝的矫正、冠状动脉旁路移植术和微创神经外科手术。尽管在医学图像分析方面有大量的知识，但内窥镜检查视频并没有被系统地捕获用于实时或术后审查和分析。它们偶尔被记录到磁性录像带（即，VHS）。还没有开发硬件和软件工具来捕获、分析和提供对这些视频上的医疗、科学或教育内容的用户友好和有效的访问。本计画旨在开发一个内视镜多媒体资讯系统（Endoscopic Multimedia Information System，EMIS），以撷取高品质的内视镜影像，并分析撷取的影像，并提供有效的内容存取。该项目将开发一种新的内窥镜视频捕获系统，该系统专为患者隐私而设计，对内窥镜手术无干扰，对特定内窥镜供应商无限制。信息帧和非信息帧自动分类的新算法。该技术不需要任何预定义的参数或阈值。新的算法用于自动内容分析突出病变，如息肉。许多突出的病变聚集在一起。一种新的区域分割技术，可以识别孤立的病变将首先开发。为了处理聚集性病变，将开发使用区域模式图来捕获相关区域重要特征的算法。该系统将直接有利于内窥镜研究，教育和培训。对研究生的研究型培训的贡献，这些研究生将有助于PI和CoPI机构的计算机科学和医学信息学研究生和本科生课程的研究型高级培训。该项目将有助于培养新一代的计算机科学家，他们具有独特的技能，是传统医学成像的补充。这项研究将增加初中和高中学生参加各种大学方案（UTA暑期科学营，科学和工程妇女方案）和国家方案的研究机会。(4)扩大代表性不足群体的参与。

ABSTRACTAdvances in video technology are being incorporated into today's healthcare practice. For example, various types of endoscopes are used for colonoscopy, upper gastrointestinal endoscopy, enteroscopy, bronchoscopy, and cystoscopy. In addition, a rapidly expanding number of formerly open surgical procedures now are being converted to endoscopic procedures including resection of gallbladders, retrieval of donor kidneys, resection of tumors of colon and pancreas, correction of hiatal hernias, coronary artery bypass grafting and minimal invasive neurosurgeries. Despite a large body of knowledge in medical image analysis, endoscopy videos are not systematically captured for real-time or post-procedure reviews and analyses. They are recorded occasionally to magnetic video-tapes (i.e., VHS). No hardware and software tools have been developed to capture, analyze, and provide user-friendly and efficient access to the medical, scientific, or educational content on such videos. This project aims to develop an Endoscopic Multimedia Information System (EMIS) to capture high quality endoscopy videos, analyze the captured videos, and provide efficient access to the content of these videos.Images of endoscopy videos significantly differ from medical still images as studiedin the literature of medical image processing. The project will develop a new capturing system for endoscopy videos designed for patient's privacy and is non-disruptive to endoscopic proceduresand non-restrictive to a particular endoscope vendor. New algorithms for automatic classification of informative and non-informative frames. The technique does not need any predefined parameters or thresholds. New algorithms for automatic content analysis for protruding lesions such aspolyps. Many protruding lesions are clustered together. A new region segmentation technique that can identify isolated lesions will be developed first. To handle clusteredlesions, algorithms using a region pattern graph that captures important characteristics of relevant regions will be developed..The proposed system will directly benefit endoscopic research, education, and training. Contributions to research-based training of graduate students who will contribute to research-based advanced training of students in graduate and undergraduate programs in computer science and medical informatics at PI and CoPI's institutions. The project will contribute to training of a new generation of computer scientists with a unique skill set supplement to traditionalmedical imaging. This research will enhance research opportunities for junior high and high school students participating in various university programs (UTA Summer Science Camp, Program for Women in Science and Engineering) and national programs. (4) Broaden the participation of under-represented groups.