Computational Geometry Algorithms for Medical Problems in Radiation Therapy and Medical Imaging

放射治疗和医学成像中医学问题的计算几何算法

• 批准号: 0515203
• 负责人: Danny Chen
• 金额: --
• 依托单位: University of Notre Dame
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-06-01 至 2010-05-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0515203&HistoricalAwards=false
• 关键词: Computational; Geometry; Algorithms; Medical; Problems

Computational Geometry Algorithms for Medical Problems in Radiation Therapy and Medical Imaging This project investigates a number of important computational geometry problems that arise in radiation therapy, medical imaging, and other applications. The target geometric problems include multileaf collimator leaf sequencing, field partitioning, shape approximation, sphere packing, and image segmentation and analysis. These problems play crucial roles in current medical research and clinical practice, especially in diagnostic imaging and radiosurgical treatment of cancers and other diseases. The project has broader impacts beyond computational geometry and computer science. It will produce efficient and effective algorithms and software for solving key problems in radiosurgery, medical imaging, and other related medical areas. New algorithmic approaches and software for computing radiosurgical plans of much better quality for cancer treatment than those used in current clinical practice will be developed. Optimal quality 3-D and 4-D medical image segmentation algorithms for various anatomical structures and their motions will be obtained. Thus, this study will help unite the powers of computer algorithms and modern medicine, and improve the quality of life for patients. Theoretically, the target problems belong to fundamental topics of computational geometry such as geometric packing, covering, shaping, partitioning, and approximation, and present significant new challenges and new problem sources to computational geometry research. To develop new geometric techniques for solving these problems, diverse ideas and methods from other theoretical areas, such as graph algorithms, combinatorial optimization, and operations research, must be utilized. Algorithm implementation, experimentation, evaluation, and software development are a crucial component of this project. The investigator's group has been working with medical researchers and practitioners, and has access to real medical data and clinical radiation treatment systems for their experimental studies. The intellectual merit of this research includes: (1) providing new algorithmic techniques for solving a set of important geometric problems confronted by current medical research and practice; (2) introducing fresh and theoretically interesting problems and algorithms to computational geometry, enriching this area, and prodding further development of geometric techniques; (3) presenting new challenging problems and new approaches to other theoretical areas such as graph algorithms, combinatorial optimization, and operations research, and bringing new applications to these areas.

放射疗法和医学成像中医学问题的计算几何算法该项目研究了许多重要的计算几何问题，这些问题在放射疗法，医学成像和其他应用中都会出现。目标几何问题包括多动物准直晶叶测序，场分配，形状近似，球形堆积以及图像分割和分析。这些问题在当前的医学研究和临床实践中起着至关重要的作用，尤其是在癌症和其他疾病的诊断成像和放射外科治疗方面。该项目超出了计算几何和计算机科学的更大影响。它将产生有效的算法和软件，以解决放射外科手术，医学成像和其他相关医疗领域的关键问题。 将开发出比当前临床实践中使用的新算法方法和用于计算癌症治疗质量更高的放射外科计划的软件。 将获得各种解剖结构及其运动的最佳质量3-D和4-D医疗图像分割算法。因此，这项研究将有助于团结计算机算法和现代医学的力量，并改善患者的生活质量。从理论上讲，目标问题属于计算几何形状的基本主题，例如几何填料，覆盖，塑造，分配和近似，并提出了重大的新挑战以及计算几何学研究的新问题来源。 为了开发用于解决这些问题的新几何技术，必须利用来自其他理论领域的各种思想和方法，例如图形算法，组合优化和操作研究。 算法实施，实验，评估和软件开发是该项目的关键组成部分。研究者小组一直在与医学研究人员和从业人员合作，并可以使用实际的医学数据和临床放射治疗系统进行实验研究。这项研究的智力优点包括：（1）提供新的算法技术来解决当前医学研究和实践面临的一组重要的几何问题； （2）将新鲜和理论上有趣的问题和算法引入计算几何形状，丰富该区域并进一步发展几何技术； （3）为其他理论领域（例如图形算法，组合优化和运营研究）提出新的具有挑战性的问题和新方法，并将新应用程序带入这些领域。