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Analysis on imaging features of mammography in computer radiography and investigation on gray scale transform and energy subtraction
Author(s) -
Feng Shuli
Publication year - 2003
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.1628411
Subject(s) - mammography , image quality , grayscale , artificial intelligence , computed radiography , computer vision , subtraction , medical imaging , image subtraction , detective quantum efficiency , computer science , optical transfer function , radiography , image processing , optics , physics , medicine , image (mathematics) , mathematics , radiology , binary image , arithmetic , cancer , breast cancer
In this dissertation, a novel transform method based on human visual response features for gray scale mammographic imaging in computer radiography (CR) is presented. The parameters for imaging quality on CR imaging for mammography were investigated experimentally. In addition, methods for image energy subtraction and a novel method of image registration for mammography of CR imaging are presented. Because the images are viewed and investigated by humans, the method of displaying differences in gray scale images is more convenient if the gray scale differences are displayed in a manner commensurate with human visual response principles. Through transformation of image gray scale with this method, the contrast of the image will be enhanced and the capability for humans to extract the useful information from the image will be increased. Tumors and microcalcifications are displayed in a form for humans to view more simply after transforming the image. The method is theoretically and experimentally investigated. Through measurement of the parameters of a geometrically blurred image, MTF, DQE, and ROC on CR imaging, and also comparison with the imaging quality of screen–film systems, the results indicate that CR imaging qualities in DQE and ROC are better than those of screen–film systems. In geometric blur of the image and MTF, the differences in image quality between CR and the screen–film system are very small. The results suggest that the CR system can replace the screen–film system for mammography imaging. In addition, the results show that the optimal imaging energy for CR mammography is about 24 kV. This condition indicates that the imaging energy of the CR system is lower than that of the screen–film system and, therefore, the x‐ray dose to the patient for mammography with the CR system is lower than that with the screen–film system. Based on the difference of penetrability of x ray with different wavelength, and the fact that the part of the x‐ray beam will pass through the image plate in the procedure of CR imaging, the method of subtraction of the two images which were taken in the same time with one exposure can increase the diagnostic information. Image registration for mammography with CR imaging is usually ignored because the two images are taken in one exposure time. This dissertation investigated the necessity of image registration for image energy subtraction in CR mammography imaging. A novel method for image registration that can reduce the computing time is established, based on the features of CR imaging for mammography.