SBIR PHASE II TOPIC "Scalable Automated Brain Tumor Segmentation"

SBIR 第二阶段主题“可扩展的自动化脑肿瘤分割”

• 批准号: 8947908
• 负责人: Patricia Buendia
• 金额: $ 100万
• 依托单位: INFOTECH SOFT, INC.
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-19 至 2016-09-18
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8947908
• 关键词: Brain; Brain Neoplasms; Central Nervous System Neoplasms; Cessation of life; Clinic; Computer software; Data; Detection; Diagnosis; Disease Progression; Equipment; Goals; Image; Imagery; Individual; Knowledge; Location; Magnetic Resonance Imaging; Malignant - descriptor; Manuals; Measures; Neurosurgeon; Noise; Non-Malignant; Oncologist; Patients; Process; Production; Reporting; Semantics; Small Business Innovation Research Grant; Structure; System; Testing; Time; Treatment Effectiveness; United States; Vendor; brain tissue; burden of illness; clinical practice; graphical user interface; interoperability; radiologist; response; tool; treatment planning; tumor; user-friendly

Brain tumor segmentation in Magnetic Resonance Imaging is an important task for neurosurgeons, oncologists, and radiologists to assess disease burden and measure tumor response to treatment. Over 237,000 individuals worldwide are estimated to have been diagnosed with malignant brain and CNS with over 174,000 deaths. In the United States alone, over 66,000 new cases of primary malignant and non-malignant brain and CNS tumors are expected to be diagnosed in 2014. Detection of brain tumors with the exact location and orientation is extremely important for effective diagnosis, treatment planning, and analysis of treatment effectiveness; however, manual delineation of the tumor takes considerable time and is prone to error and wide variability. The overall goal of this proposal is to develop a scalable and automated approach for the segmentation of brain tumors. The aims of the project are: 1) Produce a clinic ready software package with user-friendly graphical user interface to manage the process of brain tumor segmentation and quantitative imaging. 2) Implement the production software module to accurately detect and classify brain tissues from multi-channel MRI data. 3) Support quantitative imaging, system interoperability, structured reporting, and knowledge integration through the use of semantics and annotation standards. 4) Demonstrate the software produces clinically validated results for accurate assessment from MRI data of the brain under varying conditions of noise, spatial inhomogeneities, localized scanner settings and vendor equipment. 5) Package, deploy, and test the SABTS tools to be used in clinical practice for the accurate detection, visualization, and assessment of disease progression in patients with brain tumors.

磁共振成像中的脑肿瘤分割是神经外科医生，肿瘤学家和 放射科医生评估疾病负担并测量肿瘤对治疗的反应。全球超过237,000个人 据估计，已被诊断出患有超过174,000人死亡的恶性大脑和中枢神经系统。在美国 单独的原发性恶性肿瘤和非恶性大脑和中枢神经系统肿瘤的新病例超过66,000例 在2014年被诊断出。检测具有确切位置和方向的脑肿瘤对 有效的诊断，治疗计划和治疗效果分析；但是，手动描述 肿瘤需要大量时间，容易出现错误和广泛的变异性。该提议的总体目标是 开发一种可扩展且自动化的方法来分割脑肿瘤。该项目的目的是：1） 与用户友好的图形用户界面生产诊所就绪软件包，以管理大脑的过程 肿瘤分割和定量成像。 2）实施生产软件模块以准确检测和 通过多通道MRI数据对脑组织进行分类。 3）支持定量成像，系统互操作性，结构化 通过使用语义和注释标准，报告以及知识集成。 4）演示 软件产生临床验证的结果，以从不同的大脑MRI数据中进行准确评估 噪声，空间不均匀性，局部扫描仪设置和供应商设备的条件。 5）包裹，部署， 并测试用于临床实践中的SABTS工具，以进行准确的检测，可视化和评估 脑肿瘤患者的疾病进展。