Download Abdomen and Thoracic Imaging: An Engineering & Clinical by Mahmoud Mostapha, Fahmi Khalifa, Amir Alansary (auth.), PDF
By Mahmoud Mostapha, Fahmi Khalifa, Amir Alansary (auth.), Ayman S. El-Baz, Luca Saba, Jasjit Suri (eds.)
The e-book covers novel suggestions of state-of-the-art in engineering and scientific research and techniques for reading belly imaging, together with lung, mediastinum, pleura, liver, kidney and gallbladder. within the final years the imaging strategies have skilled an enormous development within the analysis and characterization of the pathologies that have an effect on belly organs. particularly, the advent of super speedy CT scanners and excessive Magnetic box MR platforms permit imaging with an attractive point of aspect the anatomy and pathology of liver, kidney, pancreas, gallbladder in addition to lung and mediastinum. in addition, because of the advance of robust laptop and complicated mathematical algorithms the quantitative and automated\semi automatic analysis of the pathology is changing into a truth. scientific photo research performs an important function within the clinical imaging box, together with computer-aided prognosis, organ/lesion segmentation, picture registration, and image-guided treatment.
This ebook will conceal all of the imaging innovations, strength for utilizing such imaging clinically, and supply current and destiny purposes as utilized to the stomach and thoracic imaging with the main international popular scientists in those fields. the most target of this e-book is to assist develop clinical learn in the wide box of belly imaging. This booklet makes a speciality of significant traits and demanding situations during this region, and it provides paintings aimed to spot new concepts and their use in scientific imaging research for belly imaging.
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Additional info for Abdomen and Thoracic Imaging: An Engineering & Clinical Perspective
A viscous fluid model combined with an NGF-based cost function was used for elastic kidney registration. However, the kidney was segmented interactively with the nearest neighbor approach, the framework was tested only on 4 data sets of two healthy volunteers, and the reported GFR measurements were slightly underestimated relative to the creatinine reference values. Positano et al.  proposed a CAD system for the estimation for renal parameters. Their system included a two-step rigid registration framework to compensate for kidney motion using MI and adaptive prediction of kidney position over the course of the respiratory cycle.
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