By Mahmoud Mostapha, Fahmi Khalifa, Amir Alansary (auth.), Ayman S. El-Baz, Luca Saba, Jasjit Suri (eds.)
The e-book covers novel techniques of cutting-edge in engineering and medical research and techniques for studying stomach imaging, together with lung, mediastinum, pleura, liver, kidney and gallbladder. within the final years the imaging thoughts have skilled an immense development within the analysis and characterization of the pathologies that impact belly organs. particularly, the creation of tremendous quickly CT scanners and excessive Magnetic box MR platforms permit imaging with a ravishing point of aspect the anatomy and pathology of liver, kidney, pancreas, gallbladder in addition to lung and mediastinum. additionally, due to the advance of robust desktop and complicated mathematical algorithms the quantitative and automated\semi automatic analysis of the pathology is changing into a fact. clinical photo research performs an important function within the scientific imaging box, together with computer-aided analysis, organ/lesion segmentation, photograph registration, and image-guided treatment.
This booklet will conceal the entire imaging recommendations, strength for utilizing such imaging clinically, and provide current and destiny functions as utilized to the stomach and thoracic imaging with the main international well known scientists in those fields. the most objective of this publication is to aid boost clinical examine in the huge box of stomach imaging. This publication makes a speciality of significant developments and demanding situations during this sector, and it provides paintings aimed to spot new innovations and their use in scientific imaging research for stomach imaging.
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Extra resources for Abdomen and Thoracic Imaging: An Engineering & Clinical Perspective
25 only on the geometric features to compensate for the kidney motion. These approaches can be extended to delay with 3D data. • Fusion of information from different modalities (US, MRI, and CT) is also another major challenge. This is due to the fact that different modalities give different clinical information and have their own image resolutions. References 1. Nankivell BJ, Alexander SI (2010) Rejection of the kidney allograft. North Eng J Med 363 (15):1451–1562 2. USRDS (2010) US Renal Data System Annual Data Report 2011: Atlas of Chronic Kidney Disease and End-Stage Renal Disease in the United States, National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda 3.
For the classification of kidney status, five features (three are derived from the gamma-variate functional model and two are from the perfusion data, namely the time-to-peak and average plateau, see Fig. 7) were chosen and the study included 50 transplant patients (27 non-rejection and 23 acute rejection). Semiautomated estimation of renal parameters was performed by Hodneland et al. . A viscous fluid model combined with an NGF-based cost function was used for elastic kidney registration.
Alansary was a part-time employee at the Middle East Technology company for 2 years, from February 2009 to February 2011. He joined the BioImaging Laboratory at University of Louisville, Louisville KY, as a research assistance in 2012. His general interests are in Digital Image Processing, Medical Imaging, and Computer Vision. Currently, Mr. Al Ansary is researching in Medical Image Analysis field and Autism Diagnostics. Sc. S. degrees in Computer Engineering from Mansoura University, Mansoura, Egypt.
Abdomen and Thoracic Imaging: An Engineering & Clinical Perspective by Mahmoud Mostapha, Fahmi Khalifa, Amir Alansary (auth.), Ayman S. El-Baz, Luca Saba, Jasjit Suri (eds.)