SBIR-STTR Award

The goal of this project is to develop innovative digital microscope autofocusing techniques for automated cytogenetics applications. We propose a novel multi-resolution image analysis approach to focus measurement and detection, based on the recently developed mathematical theory of wavelet transform. In comparison to currently available single-resolution techniques, the proposed method overcomes their fundamental limitations and promises considerably more accurate, reliable and faster means to compute and determine in-focus image position for image acquisition. This will significantly increase the ability and efficacy of automated scanning microscope instruments for clinical and cancer cytogenetics applications. In Phase 1 we will investigate the feasibility of the proposed method based on its utilization in fluorescence microscopy. We will develop and implement the algorithm and software for multi-resolution focus function computation and in-focus position determination. We will test and evaluate the new method against the current best-performing algorithms by comparing (1) Accuracy; (2) Range; (3) Insensitivity to other parameters; and (4) Speed. If the new approach achieves superior performance, in Phase 2 the technique will be further developed and extended to bright-field microscopy applications. When fully developed, the new technology will be made available to Applied Imaging (AIC) for integration into the PowerGene cytogenetics automation products. PROPOSED COMMERCIAL APPLICATIONS: As soon as the new techniques are developed and qualified for routine application, they will be made available to AIC for incorporation into the PowerGene product line of cytogenetics automation equipment, both in new systems sold and as an upgrade to existing systems already in use in cytogenetics labs, thus commercializing the technology quickly.

Thesaurus Terms:
artificial intelligence, biomedical automation, computer program /software, computer system design /evaluation, cytogenetics, digital imaging, fluorescence microscopy, image enhancement fluorescent in situ hybridization, image processing, mathematical model bioimaging /biomedical imaging, clinical research, human data

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.

Thesaurus Terms:
artificial intelligence, biomedical automation, computer program /software, computer system design /evaluation, digital imaging, fluorescence microscopy, image enhancement flow cytometry, fluorescent in situ hybridization, image processing, mathematical model bioimaging /biomedical imaging, clinical research, human data