Automatic Three Dimensional (3D) Registration for Enhanced Cancer Management

自动三维 (3D) 配准以增强癌症管理

• 批准号: 8445391
• 负责人: Charles Raymond Meyer
• 金额: $ 128.92万
• 依托单位: UNIVERSITY OF MICHIGAN AT ANN ARBOR
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-07-15 至 2015-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8445391
• 关键词: Address; Anemia; Blood Platelets; Brain; Breast; Cancer Patient; Chemotherapy-Oncologic Procedure; Clinical; Communication; Data; Development; Diffusion; Early Diagnosis; Emotional; Evaluation; Excision; Functional Magnetic Resonance Imaging; Goals; Health; Image; Language; Lesion; Leukocytes; Magnetic Resonance Imaging; Malignant Neoplasms; Malignant neoplasm of brain; Maps; Measurement; Methods; Monitor; Motion; Motor; Motor Cortex; Neoadjuvant Therapy; Noise; Operative Surgical Procedures; Patients; Program Research Project Grants; Protocols documentation; Regimen; Resolution; Risk; Sensitivity and Specificity; Techniques; Testing; Time; Tumor Suppression; Work; base; cancer therapy; chemotherapy; computerized data processing; cost; cranium; hormone therapy; improved; malignant breast neoplasm; response; tool; tumor

DESCRIPTION (provided by applicant): The overarching goal of this program project grant application is to change current clinical paradigms through the support of accurate, early detection and measurement of breast cancer response to chemotherapy (Projects 1, 3), and presurgical motor and temporal language cortex evaluation of brain function (Project 2) through the development, application and testing of robust and sophisticated registration and related signal processing tools. Project 1 investigates the efficacy of early-assessment and measurement of response to neoadjuvant chemo or hormonal therapy for patients with breast cancer obtained through the use of volumetric, diffusion and dynamic contrast enhancement MRI. The hypothesis is that nonlinear registration of interval breast exams increases the sensitivity and specificity of functional diffusion mapping (fDM) as well as the accuracy of dynamic contrast enhancement (DCE). Developing low noise, unbiased tools for assessing lesion response to therapy is currently an important topic. Project 2 extends previously completed work on registration-based fMRI motion by examining the benefits of combining our unique motion correction method with different fMRI acquisition protocols, e.g. clustered acquisition, to improve communication with the patient and response monitoring. Project 3 addresses the fundamental ambiguity problem in dynamic MRI associated with imaging in general: for any given technique either we can obtain high spatial or temporal resolution imaging data, but not both. Generalized techniques that support controlling and optimizing these tradeoffs during dynamic imaging in MRI are very important.

描述（由申请人提供）：该计划项目授予申请的总体目标是通过支持乳腺癌对化学疗法的准确，早期检测和测量（项目1、3），以及通过良好的注册和复杂的调查工具和相关的信号处理工具以及测试脑功能2评估乳腺癌对化学疗法的反应（项目1、3），以及脑部和时间语言的脑功能评估（项目2）。项目1研究了通过使用体积，扩散和动态对比度增强MRI获得的乳腺癌患者的早期评估和对新辅助化学疗法或荷尔蒙治疗的反应的疗效。假设是，间隔乳房检查的非线性注册会提高功能扩散映射（FDM）的敏感性和特异性以及动态对比度增强的准确性（DCE）。目前，开发低噪声，无偏见的工具来评估对治疗的病变反应是一个重要主题。项目2通过检查将我们独特的运动校正方法与不同的fMRI获取协议相结合的好处，例如集群采集，以改善与患者的沟通和反应监测。项目3解决了与成像相关的动态MRI中的基本歧义问题：对于任何给定的技术，我们都可以获得高空间或时间分辨率成像数据，但不能同时获得两者。在MRI中动态成像过程中支持和优化这些权衡的一般技术非常重要。

项目成果

SCALABLE FUSED LASSO SVM FOR CONNECTOME-BASED DISEASE PREDICTION.

• DOI: 10.1109/icassp.2014.6854753
• 发表时间: 2014-05
• 期刊: Proceedings of the ... IEEE International Conference on Acoustics, Speech, and Signal Processing. ICASSP (Conference)
• 作者: Watanabe T;Scott CD;Kessler D;Angstadt M;Sripada CS
• 通讯作者: Sripada CS

Dictionary-Free MRI PERK: Parameter Estimation via Regression with Kernels.

• DOI: 10.1109/tmi.2018.2817547
• 发表时间: 2018-09
• 期刊: IEEE transactions on medical imaging
• 影响因子: 10.6
• 作者: Nataraj G;Nielsen JF;Scott C;Fessler JA
• 通讯作者: Fessler JA

Regularization parameter selection for nonlinear iterative image restoration and MRI reconstruction using GCV and SURE-based methods.

使用基于 GCV 和 SURE 的方法进行非线性迭代图像恢复和 MRI 重建的正则化参数选择。

• DOI: 10.1109/tip.2012.2195015
• 发表时间: 2012-08
• 期刊: IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
• 作者: Ramani S;Liu Z;Rosen J;Nielsen JF;Fessler JA
• 通讯作者: Fessler JA

MODEL-BASED IMAGE RECONSTRUCTION FOR MRI.

• DOI: 10.1109/msp.2010.936726
• 发表时间: 2010-07-01
• 期刊: IEEE signal processing magazine
• 影响因子: 14.9
• 作者: Fessler JA

Fast parallel MR image reconstruction via B1-based, adaptive restart, iterative soft thresholding algorithms (BARISTA).

• DOI: 10.1109/tmi.2014.2363034
• 发表时间: 2015-02
• 期刊: IEEE transactions on medical imaging
• 影响因子: 10.6
• 作者: Muckley MJ;Noll DC;Fessler JA
• 通讯作者: Fessler JA