Digital Image Analysis and Virtual Microscopy in Pathology
Digital image analysis (DIA) gives objective and consistent information of the images and helps in the diagnosis, grading, classification and various prognostic information of diseases. This chapter elucidates the principle, steps and application of DIA. The steps of DIA include image digitalization, image detection, image segmentation, image editing and feature extraction. The problems of DIA such as auto-segmentation, decision to take on individual patient, getting three-dimensional imaging data from two-dimensional data, etc. are also discussed. Presently the entire slide is available in the computer as “whole slide imaging” with the help of whole slide scanning. In this whole slide imaging, a complete digital slide is generated, and the observer can examine any part of the slide by increasing or decreasing the magnification. The chapter covers the advantages and disadvantages of virtual slide and web-based teaching.
KeywordsDigital image analysis Image digitalization Image detection Image segmentation Image editing Feature extraction Auto-segmentation Telepathology Markovian texture Grey level co-occurrence of matrix Pattern recognition Virtual slide Web-based teaching Whole slide imaging
- 13.Lezoray O, Elmoataz A, Cardot H, Gougeon G, Lecluse M, Elie H, Revenu M. Segmentation of cytological images using color and mathematical morphology. Eur Conf Stereol. 1999;18(1):1–14.Google Scholar
- 16.Turbin DA, Leung S, Cheang MC, Kennecke HA, Montgomery KD, McKinney S, Treaba DO, Boyd N, Goldstein LC, Badve S, Gown AM, van de Rijn M, Nielsen TO, Gilks CB, Huntsman DG. Automated quantitative analysis of estrogen receptor expression in breast carcinoma does not differ from expert pathologist scoring: a tissue microarray study of 3,484 cases. Breast Cancer Res Treat. 2008;110(3):417–26.CrossRefGoogle Scholar
- 19.Roerdink J, Meijster A. The watershed transform: definitions, algorithms and parallelization strategies. Fundam Inform. 2000;41:187–228.Google Scholar