Tissue Elasticity Imaging: Volume One: Theory and Methods offers an extensive treatment of the fundamentals and applications of this groundbreaking diagnostic modality. The book introduces elasticity imaging, its history, the fundamental physics, and the different elasticity imaging methods, along with their implementation details, problems and artefacts. It is an essential resource for all researchers and practitioners interested in any elasticity imaging modality. As many diseases, including cancers, alter tissue mechanical properties, it is not always possible for conventional methods to detect changes, but with elasticity images that are produced by slow tissue deformation or low-frequency vibration, these changes can be displayed.
- Offers the first comprehensive reference on elasticity imaging
- Discusses the fundamentals of technology and their limitations and solutions, along with advanced methods and future directions
- Addresses the technologies and applications useful to both researchers and clinical practitioners
- Includes an online reference section regularly updated with advances in technology and applications
2. History of elasticity imaging
3. Governing theory of elasticity imaging
4. Vibration sonoelastography
5. Quasi-static elastography
6. ARFI and shear-wave imaging
8. Magnetic resonance elastography
9. Inverse problems
10. Lateral and shear strain imaging
11. Optical Elastography
Dr. S. Kaisar Alam has more than 25 years of research experience in tissue elasticity imaging and in quantitative ultrasound. He is one of a select group of researchers with experience in both quasi-static and dynamic elasticity imaging. He has written more than 35 papers in international journals and holds several patents. Dr. Alam is a member of Sigma Xi, and a Senior Member of the AIUM and IEEE. He has served in the AIUM Technical Standards Committee and in the RSNA QIBA US SWS Technical Committee. He is an Associate Editor of Elsevier's journal Ultrasonics and a member of the editorial board of Ultrasonic Imaging and the Journal of Medical Engineering. Dr. Alam was a recipient of the prestigious Fulbright Scholar Award in 2011-2012.
Garra, Brian S.
Dr. Brian S. Garra completed his residency training at the University of Utah and spent three years as an Army radiologist in Germany before returning to Washington DC and the National Institutes of Health in the mid 1980's. After four years at the NIH, he joined the faculty of Georgetown University as Director of Ultrasound. In 1998, he left Georgetown to become Professor & Vice Chairman of Radiology at the University of Vermont/Fletcher Allen Healthcare. In 2009, Dr Garra returned to the Washington DC area as Chief of Imaging Systems & Research in Radiology at the Washington DC Veterans Affairs Medical Center.In April 2010, he also joined the FDA as Associate Director in the Division of Imaging and Applied Mathematics/OSEL. In 2018 he left the VA and currently splits his time between the FDA and private practice radiology in Florida. His clinical activities include spinal MRI and general ultrasound. His research interests include PACS, digital signal processing, quantitative ultrasound including Doppler, ultrasound elastography, and photoacoustic tomography. He was chair of the FDA radiological Devices Panel from 1999 to 2002 and has been involved in the approval of several new technologies including high resolution breast ultrasound, the first digital mammographic system, the first computer aided detection system for mammography, and the first computer aided nodule detection system for chest radiographs as well as the ultrasound contrast agent albunex. He also led the team that developed the AIUM breast ultrasound accreditation program, and helped develop the ARDMS registry in breast ultrasound. He is currently also vice chairman of the Ultrasound Coordinating Committee of the RSNA Quantitative Imaging Biomarker Alliance (QIBA) and is the principal author of the forthcoming QIBA Ultrasound Shear Wave Speed Profile which will provide a standard approach to acquisition of shear wave speed data for research, clinical application and regulatory testing.