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.

用于放射治疗和医学成像中的医学问题的计算几何算法 该项目研究放射治疗、医学成像和其他应用中出现的许多重要的计算几何问题。目标几何问题包括多叶准直器叶片排序、场划分、形状近似、球体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发挥着至关重要的作用，特别是在癌症和其他疾病的诊断成像和放射外科治疗中。该项目具有计算几何和计算机科学之外更广泛的影响。它将产生高效、有效的算法和软件来解决放射外科、医学成像和其他相关医学领域的关键问题。 将开发新的算法方法和软件，用于计算放射外科计划，其癌症治疗质量比当前临床实践中使用的算法和软件要好得多。 将获得针对各种解剖结构及其运动的最佳质量 3D 和 4D 医学图像分割算法。因此，这项研究将有助于结合计算机算法和现代医学的力量，提高患者的生活质量。从理论上讲，目标问题属于几何填充、覆盖、整形、划分、逼近等计算几何的基础课题，对计算几何研究提出了重大的新挑战和新问题来源。 为了开发新的几何技术来解决这些问题，必须利用其他理论领域的不同思想和方法，例如图算法、组合优化和运筹学。 算法实现、实验、评估和软件开发是该项目的重要组成部分。研究人员的小组一直与医学研究人员和从业者合作，并能够获得真实的医学数据和临床放射治疗系统来进行实验研究。这项研究的智力价值包括：（1）为解决当前医学研究和实践面临的一系列重要几何问题提供新的算法技术； （2）将新鲜的、理论上有趣的问题和算法引入计算几何，丰富这一领域，推动几何技术的进一步发展； （3）向图算法、组合优化和运筹学等其他理论领域提出新的挑战性问题和新方法，并为这些领域带来新的应用。