Download e-book for kindle: Digital image processing for medical applications by Geoff Dougherty
By Geoff Dougherty
Snapshot processing is a hands-on self-discipline, and easy methods to research is by way of doing. this article takes its motivation from scientific purposes and makes use of actual scientific photographs and events to demonstrate and make clear innovations and to construct instinct, perception and knowing. Designed for complicated undergraduates and graduate scholars who becomes end-users of electronic photo processing, it covers the fundamentals of the key scientific imaging modalities, explaining how the photographs are produced and bought. It then offers the traditional photograph processing operations, concentrating on useful concerns and challenge fixing. Crucially, the publication explains whilst and why specific operations are performed, and functional computer-based actions convey how those operations have an effect on genuine photographs. All pictures, hyperlinks to the public-domain software program ImageJ and customized plug-ins, and chosen options can be found from www.cambridge.org/books/dougherty.
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Extra info for Digital image processing for medical applications
Open the original image prostate again, and choose Image/Type/HSB Stack and then Make Montage to see the image split into Hue, Saturation and Brightness planes. Compare this with the original image and the HSB montage. 6 Indexed color and color LUTs Open the image prostate in ImageJ, make a duplicate (Image/Duplicate…) and click on Image/Type/8 bit Color to change it from an RGB to an indexed color image. Did you notice much of a change? Compare it with the original image. With the indexed color as the current image, go to Image/Color/Edit LUT to see the 256 colors used in this image as a 16×16 LUT or palette, with the colors indexed to the pixel values of the image.
18 shows the point spread function of a two-dimensional digital imaging system, with different-sized pixel grids superimposed on it. The smaller the pixels of the grid the more detail can potentially be displayed. Taking into account the sampling theorem we might choose the pixels to be about half the width of the point spread function to adequately sample it (Fig. 18 (i)). There is nothing to be gained from using much smaller pixels than this, since there is no additional detail within the point spread function (Fig.
1mm. This would require 3600×4300 pixels to cover the radiograph. e. 8MB; if we required more gray levels, and used 16 bits per pixel, the file size would be twice as big. g. size of detectors or size of image file. A slightly coarser pixel size than optimum is chosen, whereby the pre-sampled modulation transfer function extends a little beyond the Nyquist frequency. This allows the majority of the frequency content to be recorded with adequate fidelity but permits a degree of aliasing at the higher frequencies.