Reference number : GC-2017-Q4-01462, amendment number : , agreement type : G, recipient legal name : Plataniotis, Konstantinos (University of Toronto), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Collaborative Research and Development Grants - Project, program name french : Subventions de recherche et développement coopérative - projet, program purpose english : In collaboration with Huron Digital Pathology Inc., of Waterloo, Ontario, the University of Toronto (UofT)_x000D_
team aims to develop an innovative image processing framework for the custom-tailored fluorescence imaging_x000D_
workflow of Huron's next generation TissueScope. Using tools from signal & image processing, computer_x000D_
vision, and machine learning, the applicants plan to research, develop, and test new, cutting-edge fluorescence_x000D_
imaging algorithmic solutions._x000D_
Despite effective utilization of existing virtual microscopes, the goal of delivering a fully integrated, scalable,_x000D_
certified for clinical use, digital pathology framework has not yet materialized. According to early adopters of_x000D_
integrated digital pathology the main reason for the delay is the lack of progress in integrating the digital_x000D_
scanners with advanced image processing modules. The delay is attributed to hardware related issues, such as_x000D_
those pertinent to the automation of the image acquisition process, and software related issues such as the use_x000D_
of proprietary protocols in the processing pipeline which result in a diverse set of image navigation, contrast_x000D_
correction, spectral mapping and enhancement, segmentation, and information retrieval solutions._x000D_
The proposed framework will greatly decrease the time and computational complexity of the image acquisition_x000D_
and scanning process while improving accuracy and reliability, and enhancing the end-user experience., program purpose french : In collaboration with Huron Digital Pathology Inc., of Waterloo, Ontario, the University of Toronto (UofT)_x000D_
team aims to develop an innovative image processing framework for the custom-tailored fluorescence imaging_x000D_
workflow of Huron's next generation TissueScope. Using tools from signal & image processing, computer_x000D_
vision, and machine learning, the applicants plan to research, develop, and test new, cutting-edge fluorescence_x000D_
imaging algorithmic solutions._x000D_
Despite effective utilization of existing virtual microscopes, the goal of delivering a fully integrated, scalable,_x000D_
certified for clinical use, digital pathology framework has not yet materialized. According to early adopters of_x000D_
integrated digital pathology the main reason for the delay is the lack of progress in integrating the digital_x000D_
scanners with advanced image processing modules. The delay is attributed to hardware related issues, such as_x000D_
those pertinent to the automation of the image acquisition process, and software related issues such as the use_x000D_
of proprietary protocols in the processing pipeline which result in a diverse set of image navigation, contrast_x000D_
correction, spectral mapping and enhancement, segmentation, and information retrieval solutions._x000D_
The proposed framework will greatly decrease the time and computational complexity of the image acquisition_x000D_
and scanning process while improving accuracy and reliability, and enhancing the end-user experience., agreement title english : Fluorescence imaging analysis software tools for high throughput automated workflow solution in digital pathology, agreement title french : Fluorescence imaging analysis software tools for high throughput automated workflow solution in digital pathology, agreement number : CRDPJ, agreement value : 168116.0, agreement start date : 2018-01-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year (2017-2018 to 2019-2020)., additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier (2017-2018 à 2019-2020)., owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada