Continued Development and Maintenance of ITK-SNAP 3D Image Segmentation Software

ITK-SNAP 3D 图像分割软件的持续开发和维护

• 批准号: 8531010
• 负责人: Paul A. Yushkevich
• 金额: $ 46.54万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-19 至 2015-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8531010
• 关键词: Acceleration; Address; Aging; Algorithms; Area; Automation; Back; Biomedical Research; Brain Diseases; Cardiovascular Diseases; Cations; Classification; Color; Communities; Complex; Computer software; Computers; Confocal Microscopy; Data; Data Set; Defect; Dependency; Development; Diffusion; Documentation; Education and Outreach; Educational workshop; Ensure; Environment; Exhibits; Fluorescence Microscopy; Funding; Future; Generations; Goals; Image; Imagery; Imaging technology; Industry; Lesion; Libraries; Magnetic Resonance Imaging; Maintenance; Malignant Neoplasms; Manuals; Maps; Measures; Memory; Modality; Operating System; Paper; Pattern; Performance; Probability; Process; Protocols documentation; Public Health; Publications; Publishing; Quality Control; Reproducibility; Research; Research Personnel; Resolution; Resources; S-nitro-N-acetylpenicillamine; Sampling; Slice; Software Tools; Speed; Structure; Texture; Three-Dimensional Image; Three-Dimensional Imaging; Time; Training; Ultrasonography; Update; Validation; Weight; Work; base; bioimaging; design; flexibility; graphical user interface; image processing; imaging Segmentation; imaging modality; improved; innovation; interest; interoperability; meetings; multimodality; next generation; novel; open source; operation; outreach; success; tool; tumor; usability

This project seeks to continue developing and maintaining a software application ITK-SNAP, which provides functionality for user-guided automatic segmentation and manual annotation of 3D volumes generated by biomedical imaging. ITK-SNAP is a free, open-source software tool that has a large number of users in the biomedical community (estimated in the thousands) and has contributed to over 200 publications since 2006, spanning a wide range of biomedical applications and imaging modalities. Furthermore, ITK-SNAP occupies a unique place in the spectrum of open-source tools available to today's imaging researcher, with a mature user interface and functionality specifically focused on the problem of image segmentation. The broad goals of this project are to ensure the long-term availability and viability of ITK-SNAP in the face of ever increasing complexity of imaging datasets and rapidly changing software environment; and to significantly expand the class of biomedical image segmentation problems that can benefit from the automatic features of ITK-SNAP. Five specific aims are proposed to achieve these goals. Aim 1 will develop a novel software framework for semi-automatic segmentation of multimodality and multichannel imaging data. This aim will extend the existing active contour segmentation framework with a flexible toolbox for user-guided generation of object/background probability maps from image volumes. The toolbox will support texture analysis and pattern classification, as well as user-generated spatial segmentation priors. Aim 2 will boost the performance of ITK-SNAP by employing graphics card acceleration and will change the internal data structures to allow the tool to work with very large image volumes, like those produced by high-resolution multi-slice CT or confocal microscopy. Aim 3 will remove ITK-SNAP dependencies on an aging and poorly supported FLTK user interface software library, transitioning instead to the QT library, which has strong community and industry support. This aim will also make critical improvements to ITK-SNAP usability, including support for the project paradigm. In Aim 4, segmentation protocols based on new ITK-SNAP functionality will be developed to address a diverse set of biomedical image segmentation problems. These protocols will then be validated against manual segmentation using public datasets. The criterion for success is to achieve a two-fold or better reduction in segmentation time with no penalty in inter-observer or intra-observer reliability. Aim 5 is to continue supporting the ITK-SNAP user community by implementing user-requested features, correcting defects in the software, and providing thorough documentation, including video tutorials, and training and outreach efforts.

该项目旨在继续开发和维护软件应用程序ITK-SNAP，该应用程序提供 用户引导的自动细分和手动注释3D卷生成的功能 生物医学成像。 ITK-SNAP是一种免费的开源软件工具，在该工具中有大量用户 生物医学界（数千个估计），自2006年以来已为200多个出版物做出了贡献， 跨越广泛的生物医学应用和成像方式。此外，ITK-SNAP占据 与成熟的用户相关的开源工具的独特位置 界面和功能专门针对图像分割问题。这个广泛的目标 项目旨在确保面对不断增加的ITK-SNAP的长期可用性和可行性 成像数据集的复杂性和快速变化的软件环境；并显着扩大 一类生物医学图像分割问题可以从ITK-SNAP的自动特征中受益。 提出了五个具体目标来实现这些目标。 AIM 1将开发一个新颖的软件框架 多模式和多通道成像数据的半自动分割。这个目标将扩展现有的 具有灵活的工具箱的活动轮廓分割框架，用于用户引导的对象/背景 图像量的概率图。该工具箱将支持纹理分析和模式分类，如 以及用户生成的空间分段先验。 AIM 2将提高ITK-SNAP的性能 采用图形卡加速度，并将更改内部数据结构以允许该工具与 非常大的图像量，例如高分辨率多板CT或共聚焦显微镜产生的图像。目标3 将删除对衰老且支持不足的FLTK用户界面软件库的ITK-SNAP依赖关系， 过渡到具有强大社区和行业支持的QT图书馆。这个目标也将 对ITK-SNAP可用性进行了重要改进，包括对项目范式的支持。在AIM 4中， 将开发基于新的ITK-SNAP功能的细分协议，以解决一套多样化的集合 生物医学图像分割问题。这些协议将通过手动细分进行验证 使用公共数据集。成功的标准是实现分割的两倍或更好的减少 时间没有罚款或观察者内的可靠性。目标5是继续支持ITK-SNAP 用户社区通过实施用户要求的功能，纠正软件中的缺陷并提供 详尽的文档，包括视频教程以及培训和外展工作。