Amir Amini
Amir Amini, Ph.D., is Professor and Endowed Chair in Bioimaging in the ECE Dept., University of Louisville. He received B.S. in EE from the University of Massachusetts, Amherst with high honors when at 18 he was the youngest graduate of the University and Ph.D. in EE from University of Michigan, Ann Arbor in 1990. After postdoctoral work on biomedical imaging (1990-1992), he was on faculty at Yale as Assistant Professor (1992-1996). He then moved to Washington University in St. Louis where he was Assistant Professor and then Associate Professor with tenure (1996-2006). He has been at University of Louisville since August 2006 where he directs the Medical Imaging Laboratory. Professor Amini has been on the editorial board of IEEE Trans. On Medical Imaging since 1999 , on Elsevier's journal of Computerized Medical Imaging and Graphics since 2012, on IEEE Trans. on Biomedical Engineering since 2014, and on IEEE Journal of Biomedical Health Informatics since 2016. Professor Amini was selected a Fellow of the IEEE Engineering in Medicine and Biology Society in November 2006 with the citation, ``for contributions to Cardiovascular Imaging and Medical Image Analysis.'' With more than 430,000 members in over 150 countries, IEEE (Institute of Electrical and Electronics Engineers) is the world's largest professional society dedicated to the advancement of technology. Only 0.1 percent of the active membership worldwide can be elevated to the rank of Fellow in any given year. More recently, in January 2013, he received the Distinguished Lecturer Award from the IEEE Engineering in Medicine and Biology Society. In 2013, he was selected to serve on the IEEE EMBS Technical Committee on Biomedical Imaging and Image Processing. This committee which has around a dozen members from around the world provides advice to the IEEE Engineering in Medicine and Biology for the field of biomedical imaging. Since 2015 he has served as chair of its awards subcommittee. Dr. Amini was elected by the North American membership of IEEE EMBS to serve on its global leadership team (Ad Com) for the term 2016-2018. He chaired the IEEE International Symposium on Biomedical Imaging which took place in Washington, D.C. in April 2018. He was elected to the College of Fellows of the American Institute of Medical and Biological Engineering as part of the class of 2017 and of the SPIE - the International Society for Optics, Photonics, and Imaging as of January 2019. Dr. Amini was elected and will serve as Vice President for Publications for the IEEE Engineering in Medicine and Biology Society - 2020-2022. He is VP Elect in 2019. Dr. Amini's research has been funded by the National Science Foundation, the National Institutes of Health, and several private foundations. He has edited a number of books and proceedings as outlined in his full CV.
Education
- M.S.E. in Electrical Engineering, University of Michigan - Ann Arbor, 1984
- B.S. in Electrical Engineering, University of Massachusetts - Amherst, 1983
- Postdoctoral in Radiological Imaging and Medical Image Computing, Yale University, 1991
- Ph.D. in Electrical Engineering, University of Michigan - Ann Arbor, 1990
Publications
Heart disease is the leading cause of death in the modern world. Cardiac imaging is routinely applied for assessment and diagnosis of cardiac diseases. Computerized image analysis methods are now widely applied to cardiac segmentation and registration in order to extract the anatomy and contractile function of the heart. The vast number of recent papers on this topic point to the need for an up to date survey in order to summarize and classify the published literature. This paper presents a survey of shape modeling applications to cardiac image analysis from MRI, CT, echocardiography, PET, and SPECT and aims to (1) introduce new methodologies in this field, (2) classify major contributions in image:based cardiac modeling, (3) provide a tutorial to beginners to initiate their own studies, and (4) introduce the major challenges of registration and segmentation and provide practical examples. The techniques surveyed include statistical models, deformable models/level sets, biophysical models, and non-rigid registration, using basis functions. About 130 journal articles are categorized based on methodology, output, imaging system, modality, and validations. The advantages and disadvantages of the registration and validation techniques are discussed as appropriate in each section.