By Mahmoud Mostapha, Fahmi Khalifa, Amir Alansary (auth.), Ayman S. El-Baz, Luca Saba, Jasjit Suri (eds.)
The e-book covers novel recommendations of cutting-edge in engineering and medical research and methods for studying belly imaging, together with lung, mediastinum, pleura, liver, kidney and gallbladder. within the final years the imaging strategies have skilled a major development within the analysis and characterization of the pathologies that have an effect on belly organs. particularly, the creation of super quick CT scanners and excessive Magnetic box MR structures let imaging with a good looking 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 machine and complex mathematical algorithms the quantitative and automated\semi automatic prognosis of the pathology is turning into a truth. clinical photograph research performs a necessary function within the scientific imaging box, together with computer-aided prognosis, organ/lesion segmentation, snapshot registration, and image-guided remedy.
This ebook will hide all of the imaging strategies, power for employing such imaging clinically, and supply current and destiny purposes as utilized to the stomach and thoracic imaging with the main international well known scientists in those fields. the most objective of this booklet is to assist boost medical examine in the vast box of belly imaging. This publication makes a speciality of significant developments and demanding situations during this quarter, and it provides paintings aimed to spot new options and their use in scientific imaging research for belly imaging.
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Extra info for Abdomen and Thoracic Imaging: An Engineering & Clinical Perspective
Springer, New York, pp 235–280 141. Rueckert D, Clarkson MJ, Hill DLG, Hawkes DJ (2000) Non-rigid registration using higherorder mutual information. In: Proceedings of SPIE medical imaging 2000: image processing (SPIE’00), vol 3979, pp 438–447 142. Khalifa F, Beache GM, Elnakib A, Sliman H, Gimel’farb G, Welch KC, El-Baz A (2012) A new nonrigid registration framework for improved visualization of transmural perfusion gradients on cardiac first-pass perfusion MRI. In: Proceedings of IEEE international symposium on biomedical imaging: from nano to macro (ISBI’12), Barcelona, 2–5 May 2012, pp 828–831 143.
Gas-filled microbubbles, acting as amplifiers of the blood backscattering signal, are used as a contrast agent. Because the bubbles are naturally eliminated by metabolism processes, this modality is considered as completely safe for the patients even with renal or liver failure (unlike contrast-enhanced CT, for example). However the usually poor quality of CEUS images makes any computer-based analysis challenging: in addition to having powerful speckle noise, the image is very grainy and almost binary as a result of ultrasound interactions with individual bubbles.
B) Evolution of the ellipse along the iterations (orange) and final result (green). (c) Ellipse contour and center superimposed on the product w I at convergence Fig. 3 Results of the ellipsoid detection (red) compared to the ground truth (green), on slices of the volumes shown in Fig. 1 Kidney Segmentation via Implicit Template Deformation The previously detected ellipsoid will now be deformed to segment the kidney more precisely. We follow the template deformation framework described in [13, 14] and extended in , as it is a very efficient model-based algorithm and it has already been applied successfully to kidney segmentation in CT images .
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.)