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Digital Image Analysis for Early Diagnosis of Cancer: Identification of Pre-Cancerous State
Abstract
Cancer diagnoses so far are based on pathologists' criteria. Hence, they are based on qualitative assessment. Histopathological images of cancer biopsy samples are now available in digital format. Such digital images are now gaining importance. To avoid individual pathologists' qualitative assessment, digital images are processed further through use of computational algorithm. To extract characteristic features from the digital images in quantitative terms, different techniques of mathematical morphology are in use. Recently several other statistical and machine learning techniques have developed to classify histopathological images with the pathologists' criteria. Here, the authors discuss some characteristic features of image processing techniques along with the different advanced analytical methods used in oncology. Relevant background information of these techniques are also elaborated and the recent applications of different image processing techniques for the early detection of cancer are also discussed.
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