A method for quantitative analysis of clump thickness in cervical cytology slides |
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| Institution: | 1. Laboratory of Animal Cell Biology and Embryology, College of Veterinary Medicine, Nanjing Agricultural University, PR China;2. College of Veterinary Medicine, Yangzhou University, PR China;1. Instituto de Física de Cantabria (CSIC-UC), Avda. los Castros s/n, E-39005 Santander, Spain;2. CERN, Organisation europénne pour la recherche nucléaire, CH-1211 Genéve 23, Switzerland;3. SGIker Laser Facility, UPV/EHU, Sarriena, s/n - 48940 Leioa-Bizkaia, Spain;4. Departamento de Ingeniería Electrónica, Escuela Superior de Ingenieros Universidad de Sevilla, Spain;1. EMAT, University of Antwerp, Groenenborgerlaan 171, 2020 Antwerp, Belgium;2. Graz Centre for Electron Microscopy, Steyrergasse 17, 8010 Graz, Austria;3. Institute for Electron Microscopy and Nanoanalysis, Graz University of Technology, Steyrergasse 17, A-8010 Graz, Austria;1. College of Computer and Information Science, Fujian Agriculture and Forestry University, Fuzhou 350002, China;2. College of Physics and Information Engineering, FuZhou University, Fuzhou 350002, China;3. Fujian Province Key Laboratory of Plant Virology, Institute of Plant Virology, Fujian Agriculture and Forestry University, Fuzhou 350002, China;1. Neurologische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Munich, Germany;2. Institut für Neurogenomik, Helmholtz Zentrum München, Munich, Germany;3. Department of Neurology, Medical University Innsbruck, Innsbruck, Austria;4. Institut für Humangenetik, Helmholtz Zentrum München, Munich, Germany;5. Institute of Epidemiology II, Helmholtz Zentrum München, Munich, Germany;6. Institute of Genetic Epidemiology, Helmholtz Zentrum München, Munich, Germany;7. Institut für Humangenetik, Technische Universität München, Munich, Germany;8. Vivantes Klinikum Spandau, Berlin, Germany;9. Munich Cluster for Systems Neurology, SyNergy, Munich, Germany |
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| Abstract: | Knowledge of the spatial distribution and thickness of cytology specimens is critical to the development of digital slide acquisition techniques that minimise both scan times and image file size. In this paper, we evaluate a novel method to achieve this goal utilising an exhaustive high-resolution scan, an over-complete wavelet transform across multi-focal planes and a clump segmentation of all cellular materials on the slide. The method is demonstrated with a quantitative analysis of ten normal, but difficult to scan Pap stained, Thin-prep, cervical cytology slides. We show that with this method the top and bottom of the specimen can be estimated to an accuracy of 1 μm in 88% and 97% of the fields of view respectively. Overall, cellular material can be over 30 μm thick and the distribution of cells is skewed towards the cover-slip (top of the slide). However, the median clump thickness is 10 μm and only 31% of clumps contain more than three nuclei. Therefore, by finding a focal map of the specimen the number of 1 μm spaced focal planes that are required to be scanned to acquire 95% of the in-focus material can be reduced from 25.4 to 21.4 on average. In addition, we show that by considering the thickness of the specimen, an improved focal map can be produced which further reduces the required number of 1 μm spaced focal planes to 18.6. This has the potential to reduce scan times and raw image data by over 25%. |
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| Keywords: | Virtual microscopy Digital slide Focal depths Cytology |
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