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Subtraction Method Of Mathematical Morphology And Region-based The Silicosis X-ray Image Enhancement Technology

Posted on:2007-07-04Degree:MasterType:Thesis
Country:ChinaCandidate:L W ZhengFull Text:PDF
GTID:2208360185471868Subject:Communication and Information System
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This paper focuses on the study of Mathematical Morphology and regional image subtract, and theirs applications in pneumoconiosis X-ray films enhancements. Pneumoconiosis is one of the major occupational diseases of which no cures have turned out effective so far. X-ray film examination is necessarily adopted to diagnose and discern pneumoconiosis. However, X-ray film features an excessively broad range, over -exhaustive details and poor contrast. Also, it is not obvious as to the pathological changes of early pneumoconiosis symptoms. These factors add difficulty to the early diagnoses of pneumoconiosis. With the help of digital image processing, the contrast of pneumoconiosis X-ray film can be enhanced, and such early symptoms will be emphasized with better clarity in the feedback. Thereby, we are hoping to reduce the misdiagnosis rate.Mathematical Morphology is a new method that being used in the field of image processing and pattern recognition, its theory is to analysis and recognition the image by using some shape structural element to measure and extract the correspondence form in the image. The paper used the morphology methods to process the silicosis' X-ray films, including the Binarization processing of images, Top-hat transform and four basic morphology operating, and by the inspiration of the methods of image edge detection based on multi structural element using Mathematical Morphology, the methods of using multiple-dimensioned and multi structural element to enhance the image was put forward. The paper put forward the skills of image enhancement based on the regional connectivity conception, which to determine whether a pixel and it's neighborhood pixel belong to the same region by set threshold value. By the inspiration of inverse-sharpen-mask enhancement algorithm, the pixel was simply divided into two classes, then it belongs to whether the background or the small shadow, and extend the neighborhood to a small correlation region, select the appropriate size of the region and blurring times, to blur the original image, to obtain the small shadow image by using the original image to subtract the blurring image. The results indicates that enhancement processing on silicosis' X-ray films will...
Keywords/Search Tags:Image enhancement, Mathematical Morphology, Regional connectivity, Image subtract, Pneumoconiosis(silicosis)
PDF Full Text Request
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