Conformal Geometry for Medical Imaging

医学成像的共形几何

基本信息

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
项目类别：
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&apos 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

项目摘要

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，测量，比较，校准，注册和分析潜在变形的器官形状以高度准确性和忠诚度至关重要。但是，由于人体器官的复杂形状，这非常困难。不同的器官具有不同的拓扑和曲率分布，此外，由于疾病进展，运动，成像，手术和治疗，形状可能会变形。我们建议使用保形几何形状，这是一种理论上严格且实际上有效，强大的方法，以应对这一挑战。该项目的广泛长期目标是发展保形几何形状，作为媒体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。一个强大的工具，即RICCI流，可用于计算保形几何形状。它最近用于庞加莱猜想的证明。我们已经开发了实用的计算算法来计算RICCI流，并获得了有希望的初步结果，并计划将其应用于结肠和大脑的各种临床病例研究中。该项目的健康相关性是大大改善临床应用的医学成像技术，从而改善诊断，程序计划，治疗，随访和临床研究。因此，医疗保健将大大改善，并且患者参与筛查计划将显着提高。该项目的具体目的是发展：（1）保形表面扁平；（2）用于体积参数化的共形映射；（3）使用保形映射的注册和融合。研究设计和方法将包括开发和验证技术，以形成结实的3D器官表面到典型的参数表面以进行结肠息肉检测。我们将进一步扩展基于RICCI流量，然后将其应用于大脑和结肠结构分割以及肿瘤评估。此外，我们将使用通用规范参数域实施形状注册和数据融合。大脑数据集将在受试者和模态内和内部融合，以及结肠仰卧和容易发生的脑部数据集将被注册以改善癌症筛查。绩效网站（S）（州，城市，州）计算机科学和放射学斯托尼·布鲁克大学（Stony Brook University）（Stony Brook的SUNY）Stony Brook，NY 11794-4400组织缩写：

项目成果

期刊论文数量（12）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

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
影响因子：
0
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