Multiresolution Autofocusing for Automated Microscopy

用于自动显微镜的多分辨率自动对焦

• 批准号: 6951446
• 负责人: QIANG WU
• 金额: $ 31.84万
• 依托单位: ADVANCED DIGITAL IMAGING RESEARCH, LLC
• 依托单位国家: 美国
• 财政年份: 2002
• 资助国家: 美国
• 起止时间: 2002-05-15 至 2007-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6951446
• 关键词: artificial intelligence; bioimaging /biomedical imaging; biomedical automation; clinical research; computer program /software; computer system design /evaluation; digital imaging; flow cytometry; fluorescence microscopy; fluorescent in situ hybridization; human data; image enhancement; image processing; mathematical model; artificial intelligence; bioimaging /biomedical imaging; biomedical automation; clinical research; computer program /software; computer system design /evaluation; digital imaging; flow cytometry; fluorescence microscopy; fluorescent in situ hybridization; human data; image enhancement; image processing; mathematical model

DESCRIPTION (provided by applicant): This project will further develop and refine an innovative digital auto-focus technology for automated microscopy. Auto-focusing is essential to automated microscope imaging. Currently available techniques rely on various algorithms of focus computation at a single image resolution and suffer from inherent performance limitations, which affect their success and utilization in clinical and research applications. Auto-focusing for fluorescence microscopy, for example, represents a serious challenge to existing methods for desired accuracy, reliability and speed since in this case the images have very low signal-to-noise ratio and narrow depth-of-fields while specimen exposure to fluorescent excitation must be minimized to avoid photo-bleaching and formation of undesirable substances such as free radicals and singlet oxygen. We propose a novel multi-resolution image analysis approach to microscope auto-focusing, based on the recently developed mathematical theory of wavelet transform. The new approach overcomes a number of inherent limitations of currently available techniques, and holds the promise to make the measurement of the microscope focus function and the detection of best-focus imaging position considerably more accurate, reliable, and fast. This innovative technology will significantly increase the ability and efficacy of automated microscope instruments for a wide range of clinical and research applications where a large number of specimens need to be imaged and quantitatively analyzed on a routine basis. During the Phase 1 project we investigated the feasibility of the proposed technology for fluorescence microscopy. We developed software to implement the algorithms for multi-resolution focus function measurements and for in-focus imaging position search. We evaluated the new approach in software simulation on a variety of sample image stacks of cytogenetic FISH specimens, and compared it with all current best-performing methods for microscope auto-focusing using the criteria of (1) accuracy, (2) range, (3) robustness, and (4) speed. The Phase 1 results suggest that, by using a proper wavelet-based auto-focus function, the new multi-resolution method significantly outperforms all competing methods in each of the aforementioned performance categories, and clearly exceeds the Phase 1 feasibility criteria. In the Phase 2 project, we will further develop, refine, integrate, and validate the new technology in real-time operation environment. We plan to build a prototype system with multi-resolution auto-focusing capabilities for both fluorescence and bright-field microscope imaging. We will evaluate the system extensively for a variety of applications including genetics, pathology, and cytology. We will beta test the new system and technology in routine clinical laboratory environment and optimize the technology as end user input and feedbacks are gathered. Once fully developed and qualified, this new technology will be patented and incorporated into future IRIS automated imaging cytometry instruments. It will also be made commercially available to Applied Imaging Corporation and other manufacturers of automated microscope instruments through licensing agreements and partnerships.

描述（由申请人提供）：该项目将进一步开发和完善一种用于自动显微镜的创新数字自动对焦技术。自动焦点对于自动显微镜成像至关重要。当前可用的技术依赖于单个图像分辨率的各种焦点计算算法，并且遭受了固有的性能限制，这会影响其在临床和研究应用中的成功和利用。例如，用于荧光显微镜的自动关注是对现有方法的严重挑战，因为在这种情况下，图像具有非常低的信噪比和狭窄的景点，而在荧光激发中的样本则必须最小化，以避免避免使用不可避免的诸如免费的Oxegens和Singlets的荧光照射和形成。我们根据最近开发的小波变换数学理论提出了一种新型的多分辨率图像分析方法，用于显微镜自动焦点。新方法克服了当前可用技术的许多固有局限性，并有望进行显微镜焦点函数的测量，并且检测最佳焦点成像位置更加准确，可靠和快速。这项创新技术将显着提高自动显微镜仪器在广泛的临床和研究应用中的能力和功效，在这些临床和研究应用中，需要进行大量标本进行成像和定量分析。在第1阶段项目中，我们研究了提出的技术对荧光显微镜的可行性。我们开发了用于实现多分辨率焦点功能测量和聚焦成像位置搜索的算法。我们评估了软件仿真的新方法对各种细胞遗传鱼样样品的样本图像堆栈，并将其与使用（1）精度的标准，（2）范围，（3）稳健性和（4）速度进行了比较。第1阶段的结果表明，通过使用基于小波的自动对焦功能，新的多分辨率方法在每个上述性能类别中都显着优于所有竞争方法，并且显然超过了第1阶段的可行性标准。在第二阶段项目中，我们将进一步开发，完善，整合和验证实时操作环境中的新技术。我们计划构建具有多分辨率自动关注功能的原型系统，用于荧光和明亮场显微镜成像。我们将广泛评估系统的各种应用，包括遗传学，病理学和细胞学。我们将在常规临床实验室环境中测试新系统和技术，并将技术优化作为最终用户的投入和反馈。一旦完全开发和资格，这项新技术将获得专利，并将其纳入未来的IRIS自动成像细胞仪仪器中。还将通过许可协议和合作伙伴关系和合作伙伴关系，将其用于应用成像公司和其他自动显微镜工具制造商。