By Isaac Bankman

ISBN-10: 0120777908

ISBN-13: 9780120777907

In recent times, the notable advances in clinical imaging tools have elevated their use significantly for diagnostics in addition to making plans and follow-up of therapy. rising from the fields of radiology, scientific physics and engineering, scientific imaging now not easily bargains with the know-how and interpretation of radiographic photos. The unlimited probabilities offered via computing device technological know-how and expertise, coupled with engineering advances in sign processing, optics and nuclear medication have created the greatly improved box of scientific imaging.

The guide of clinical Imaging is the 1st complete compilation of the strategies and methods used to research and manage clinical pictures once they were generated or digitized. The guide is equipped in six sections that relate to the most capabilities wanted for processing: enhancement, segmentation, quantification, registration, visualization in addition to compression garage and telemedicine.

* the world over well known authors(Johns Hopkins, Harvard, UCLA, Yale, Columbia, UCSF)
* contains imaging and visualization
* includes over 60 pages of attractive, four-color photos

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Extra resources for Handbook of Medical Imaging: Processing and Analysis

Example text

2 Threshold Estimation for Denoising 1 Introduction Image enhancement techniques have been widely used in the ®eld of radiology, where the subjective quality of images is important for human interpretation and diagnosis. Contrast is an important factor in subjective evaluation of image quality. Many algorithms for accomplishing contrast enhancement have been developed and applied to problems in medical imaging. A comprehensive survey of several methods has been published by Wang et al.

24 5 Anisotropic Adaptive Filtering . . . . . . . . . . . . . . . . . . . . . 6 Examples of Anisotropic Filtering in 2D and 3D References . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 1 Introduction Adaptive ®lters are commonly used in image processing to enhance or restore data by removing noise without signi®cantly blurring the structures in the image. The adaptive ®ltering literature is vast and cannot adequately be summarized in a short chapter.

24 5 Anisotropic Adaptive Filtering . . . . . . . . . . . . . . . . . . . . . 6 Examples of Anisotropic Filtering in 2D and 3D References . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 1 Introduction Adaptive ®lters are commonly used in image processing to enhance or restore data by removing noise without signi®cantly blurring the structures in the image. The adaptive ®ltering literature is vast and cannot adequately be summarized in a short chapter.

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Handbook of Medical Imaging: Processing and Analysis by Isaac Bankman


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