Abstract : Cancer research and diagnostics is an important frontier to apply the power of computers. Researchers use image processing techniques for a few years now, but diagnostics only start to explore its possibilities. Pathologists specialized in this area usually diagnose by visual inspection, typically through a microscope, or more recently on a computer screen. They examine at tissue specimen or a sample consisting of a population cells extracted from it. The latter area is the area of cytometry that researchers started to support by creating image processing algorithms. The validation of an image processing approach like that is an expensive task both financially and time-wise. This paper aims to show a semi-automatized method to simplify this task, by reducing the amount of human interaction necessary.
Luis M. Camarinha-Matos; Thais A. Baldissera; Giovanni Di Orio; Francisco Marques. 6th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Apr 2015, Costa de Caparica, Portugal. IFIP Advances in Information and Communication Technology, AICT-450, pp.231-238, 2015, Technological Innovation for Cloud-Based Engineering Systems. 〈10.1007/978-3-319-16766-4_25〉
https://hal.inria.fr/hal-01343487
Contributeur : Hal Ifip
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Viktor Jonas, Miklos Kozlovszky, Bela Molnar. Semi-Automated Quantitative Validation Tool for Medical Image Processing Algorithm Development. Luis M. Camarinha-Matos; Thais A. Baldissera; Giovanni Di Orio; Francisco Marques. 6th Doctoral Conference on Computing, Electrical and Industrial Systems (DoCEIS), Apr 2015, Costa de Caparica, Portugal. IFIP Advances in Information and Communication Technology, AICT-450, pp.231-238, 2015, Technological Innovation for Cloud-Based Engineering Systems. 〈10.1007/978-3-319-16766-4_25〉. 〈hal-01343487〉
