Conformal Geometry for Medical Imaging

医学成像的共形几何

• 批准号: 7894775
• 负责人: ARIE E KAUFMAN
• 金额: $ 37.54万
• 依托单位: STATE UNIVERSITY NEW YORK STONY BROOK
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-15 至 2012-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7894775
• 关键词: Abbreviations; Abdomen; Abdominal Aortic Aneurysm; Algorithms; Alzheimer' s Disease; Aneurysm; Aorta; Aortic Aneurysm; Area; Atlas of Cancer Mortality in the United States; Bladder; Blood Vessels; Brain; Brain Mapping; Brain imaging; Brain scan; Calibration; Cancer Detection; Case Study; Characteristics; Cities; Classification; Clinical; Clinical Research; Colon; Colon Carcinoma; Colonic Polyps; Communication; Communities; Computational algorithm; Computed Tomographic Colonography; Computer Assisted; Cystoscopy; Data; Data Set; Data Storage and Retrieval; Databases; Detection; Diagnosis; Diagnostic Procedure; Diffuse; Disease; Disease Progression; Drug Addiction; Educational workshop; Equation; Evaluation; Fourier Analysis; Frequencies; Functional Magnetic Resonance Imaging; Genus Cola; Goals; Health; Healthcare; Human; Image; Imagery; Imaging Techniques; Investigation; Journals; Libraries; Liver; Magnetic Resonance Imaging; Malignant neoplasm of urinary bladder; Manuals; Maps; Mathematics; Measurement; Measures; Medial; Medical Imaging; Methodology; Methods; Modality; Monitor; Movement; Mucous Membrane; Operative Surgical Procedures; Organ; Patient Participation; Patients; Physics; Play; Polyps; Positron-Emission Tomography; Principal Investigator; Prize; Procedures; Process; Public Health; Publishing; Radiology Specialty; Research; Research Design; Research Personnel; Research Project Grants; Role; Scanning; Screening for cancer; Screening procedure; Shapes; Simulate; Solid; Solutions; Stretching; Structure; Surface; System; Techniques; Telemedicine; Testing; Texture; Time; Universities; Validation; Virtual Endoscopy; X-Ray Computed Tomography; addiction; base; biomedical Computer science; clinical application; computer science; field study; improved; indexing; large-scale database; novel; operation; performance site; programs; symposium; theories; tool; treatment planning; tumor; virtual; volunteer; web site

It is paramount in medical imaging to measure, compare, calibrate, register and analyze potentially deformed organ shapes with high accuracy and fidelity. However, this is extremely difficult due to the complicated shape of human organs. Different organs have different topologies and curvature distributions, and furthermore, the shape may deform due to disease progression, movement, imaging, surgery and treatment. We propose to use conformal geometry, a theoretically rigorous and practically efficient and robust method, to tack this challenge. The broad, long-term objective of this project is to develop conformal geometry as a primary tool in the vast biomedical applications of medial imaging. Conformal structure is a natural structure, ideally suited to study shape matching and deformation. A powerful tool, Ricci flow, can be used to compute conformal geometry. It has been applied recently in the proof of the Poincaré conjecture. We have developed practical computational algorithms to compute Ricci flow, obtained promising preliminary results, and plan to apply it with other conformal geometric methods in a variety of clinical case-studies for the colon and brain. The health relatedness of the project is to dramatically improve medical imaging techniques for clinical applications, thereby improving the diagnosis, procedure planning, treatment, follow-ups and clinical research. Consequently, health care will be substantially improved, as well as patients’ participation in screening programs will be noticeably increased. The specific aims of this project are to develop: (1) conformal surface flattening; (2) conformal mapping for volumetric parameterization; and (3) registration and fusion using conformal mapping. The research design and methodology will include developing and validating techniques to conformally flatten 3D organ surfaces to canonical parametric surfaces for colonic polyp detection. We will further extend flattening to implement volumetric parameterization based on Ricci flow and then apply it to brain and colon structure segmentation, and tumor evaluation. In addition, we will implement shape registration and data fusion using a common canonical parameter domain. Brain data sets will be fused between and within subjects and modalities, as well as colon supine and prone will be registered for improved cancer screening. PERFORMANCE SITE(S) (organization, city, state) Departments of Computer Science and Radiology Stony Brook University (SUNY at Stony Brook) Stony Brook, NY 11794-4400 Organization abbreviation:

在医学成像中，以高精度和保真度测量、比较、校准、记录和分析潜在变形的器官形状至关重要。然而，由于人体器官的形状复杂，这是极其困难的。不同的器官具有不同的拓扑结构和曲率分布，而且形状可能因疾病进展、运动、影像、手术和治疗而变形。我们建议使用共形几何来应对这一挑战，这是一种理论上严谨、实践上高效且稳健的方法。该项目的广泛、长期目标是开发共形几何作为医学成像广泛生物医学应用的主要工具。共形结​​构是一种自然结构，非常适合研究形状匹配和变形。 Ricci flow 是一个强大的工具，可用于计算共形几何。最近它被应用在庞加莱猜想的证明中。我们开发了实用的计算算法来计算 Ricci 流，获得了有希望的初步结果，并计划将其与其他共形几何方法一起应用于结肠和大脑的各种临床案例研究中。该项目的健康相关性是显着改善临床应用的医学成像技术，从而改善诊断、手术规划、治疗、随访和临床研究。因此，医疗保健将得到显着改善，患者对筛查计划的参与也将显着增加。该项目的具体目标是开发：（1）共形表面平坦化； (2) 体积参数化的共形映射； (3)使用共形映射进行配准和融合。研究设计和方法将包括开发和验证将 3D 器官表面保形平坦化为规范参数化表面以进行结肠息肉检测的技术。我们将进一步扩展扁平化以实现基于Ricci流的体积参数化，然后将其应用于大脑和结肠结构分割以及肿瘤评估。此外，我们将使用公共规范参数域来实现形状配准和数据融合。大脑数据集将在受试者和模式之间和内部进行融合，并且结肠仰卧和俯卧将被注册以改进癌症筛查。绩效站点（组织、城市、州） 计算机科学和放射学系 石溪大学 (SUNY at Stony Brook) Stony Brook, NY 11794-4400 组织缩写：

项目成果

LMap: Shape-Preserving Local Mappings for Biomedical Visualization.

LMap：用于生物医学可视化的形状保持局部映射。

• DOI: 10.1109/tvcg.2017.2772237
• 发表时间: 2018
• 期刊: IEEE transactions on visualization and computer graphics
• 影响因子: 5.2
• 作者: Nadeem,Saad;Gu,Xianfeng;Kaufman,ArieE
• 通讯作者: Kaufman,ArieE

Context preserving maps of tubular structures.

管状结构的上下文保留图。

• DOI: 10.1109/tvcg.2011.182
• 发表时间: 2011
• 期刊: IEEE transactions on visualization and computer graphics
• 影响因子: 5.2
• 作者: Marino,Joseph;Zeng,Wei;Gu,Xianfeng;Kaufman,Arie
• 通讯作者: Kaufman,Arie

Interactive visibility retargeting in VR using conformal visualization.

使用共形可视化在 VR 中实现交互式可见性重定向。

• DOI: 10.1109/tvcg.2011.278
• 发表时间: 2012
• 期刊: IEEE transactions on visualization and computer graphics
• 影响因子: 5.2
• 作者: Petkov,Kaloian;Papadopoulos,Charilaos;Zhang,Min;Kaufman,ArieE;Gu,XianfengDavid
• 通讯作者: Gu,XianfengDavid

Volumetric Colon Wall Unfolding Using Harmonic Differentials.

• DOI: 10.1016/j.cag.2011.03.008
• 发表时间: 2011-06-01
• 期刊: Computers & graphics
• 作者: Zeng W;Marino J;Kaufman A;Gu XD
• 通讯作者: Gu XD

Multi-voxel pattern analysis of selective representation of visual working memory in ventral temporal and occipital regions.

• DOI: 10.1016/j.neuroimage.2013.01.055
• 发表时间: 2013-06
• 期刊: NEUROIMAGE
• 影响因子: 5.7
• 作者: Han, Xufeng;Berg, Alexander C.;Oh, Hwamee;Samaras, Dimitris;Leung, Hoi-Chung
• 通讯作者: Leung, Hoi-Chung