Amir Amini (academic)

Last updated
Amir Amini
Professor Amir Amini.jpg
NationalityAmerican
Alma materUniversity of Massachusetts, Amherst
The University of Michigan, Ann Arbor
Occupation(s)Engineer
Professor
Scientific career
FieldsMedical Imaging, Artificial Intelligence
Institutions Yale University
Washington University in St. Louis
University of Louisville

Amir Amini is the professor and endowed chair in bioimaging at the University of Louisville. Prior to this, he was the founder of the Cardiovascular Image Analysis Laboratory and associate professor at the Washington University in St. Louis. He was elected a fellow of the IEEE (Engineering in Medicine and Biology Society) in 2007, the College of Fellows of the American Institute of Medical and Biological Engineering in 2017, the International Society for Optics, Photonics, and Imaging in 2019, the Asia-Pacific Artificial Intelligence Association in 2021, and the International Academy of Medical and Biological Engineering in 2024.

Contents

Early life and education

Amir Amini attended Center Grove High School in Greenwood, Indiana. [1] He graduated with the B.S. in Electrical Engineering with high honors from the University of Massachusetts at Amherst in 1983, where he was the youngest member of his graduating class at the age of 18. In 1984 he received an MSE degree from University of Michigan, Ann Arbor, where he also earned his PhD from the Artificial Intelligence Lab in 1990. [2] [3] [4]

Career

Teaching

Following two years of postdoctoral work at Yale University, [5] Amini served as an assistant professor from 1992 to 1996. He was then on the faculty at Washington University in St. Louis from 1996 to 2006, where he became an associate professor with tenure [6] and founded the Cardiovascular Image Analysis Laboratory. [5] He is now the professor and endowed chair in bioimaging at the University of Louisville, where he has taught since 2006 and directs the Medical Imaging Laboratory. [7] In 2009 and 2011 he was the recipient of the University of Louisville Faculty Favorite Award for teaching excellence [2] He serves on the executive committee of the Center for AI in Radiological Sciences at the University of Louisville. [8]

Professional activities

Amini was the chair of SPIE Medical Imaging Conference on Physiology, Function, and Structure from Medical Images from 2002 to 2006, and in 2007 he co-chaired the SPIE Medical Imaging Symposium. [2] That year he was also elected a fellow of the IEEE (Engineering in Medicine and Biology Society) with the citation “for contributions to cardiovascular imaging and medical image analysis”. [9]

He joined the editorial board of the journal IEEE Transactions on Medical Imaging in 1999 and the editorial board of the journal Computerized Medical Imaging and Graphics in 2012. [2] After receiving the Distinguished Lecturer Award from the IEEE EMBS in 2013, he served on the IEEE EMBS Technical Committee on Biomedical Imaging and Image Processing. Between 2016 and 2018, he served on the IEEE EMBS Administrative Committee. [6] He Chaired the IEEE International Symposium on Biomedical Imaging in Washington, D.C. in 2018. [10]

In 2017 he was elected a fellow of the College of Fellows of the American Institute of Medical and Biological Engineering “for outstanding contributions to cardiovascular imaging, medical image analysis, and magnetic resonance imaging of flow and motion”. [11] He was next elected a fellow of the International Society for Optics, Photonics, and Imaging in 2019. [12] Additionally, he is a fellow of the Asia-Pacific Artificial Intelligence Association. [13] From 2020 to 2021, he served as the Vice President for Publications for the IEEE Engineering in Medicine and Biology Society for the term 2020-2021. [14] Amini has been on the editorial board of IEEE Transactions on Biomedical Engineering since 2014, [2] IEEE Journal of Biomedical Health Informatics between (2016-2019), the IEEE Open Journal of Engineering in Medicine and Biology since 2019, [15] and the IEEE Reviews in Biomedical Engineering since 2020. [16]

Research

Amini has made contributions in development and application of AI methods to medical imaging as well as development and application of MRI methods for determining flow and motion, including research supported by National Institute of Health [17] and National Science Foundation grants. [18] An area of significant focus for Amini’s laboratory is vascular and valvular flow imaging with MRI. [19] Under NIH funding, his laboratory has developed scan efficient 4D Flow MRI Methods with non-Cartesian trajectories [20] [21] [22] and deep Convolutional Neural Network models for efficient reconstruction of 4D flow MR images. [23] His laboratory has also developed computational, AI methods for Velocity to Pressure mapping for estimation of intravascular and transvalvular pressure gradients. [24] [25] [26]

Amini has worked on the development of computational methods for analysis of biomedical images, as well as the development of AI and Deep Learning methods for segmentation, disease classification, and analysis of medical images. [27] [28] [29] [30] Another area of research has been imaging motion with tagged MRI for determination of left-ventricular function and myocardial strain. [31] [32] [33] Other research activities have included development of methods for image segmentation, determination of motion and tissue strain from US echocardiography, and lung 4D X-ray CT. [34] [35] [36] [37] In 2020, he received the University of Massachusetts at Amherst College of Engineering Distinguished Alumni Award. [38]

Related Research Articles

<span class="mw-page-title-main">Magnetic resonance imaging</span> Medical imaging technique

Magnetic resonance imaging (MRI) is a medical imaging technique used in radiology to form pictures of the anatomy and the physiological processes inside the body. MRI scanners use strong magnetic fields, magnetic field gradients, and radio waves to generate images of the organs in the body. MRI does not involve X-rays or the use of ionizing radiation, which distinguishes it from computed tomography (CT) and positron emission tomography (PET) scans. MRI is a medical application of nuclear magnetic resonance (NMR) which can also be used for imaging in other NMR applications, such as NMR spectroscopy.

<span class="mw-page-title-main">Computer-aided diagnosis</span> Type of diagnosis assisted by computers

Computer-aided detection (CADe), also called computer-aided diagnosis (CADx), are systems that assist doctors in the interpretation of medical images. Imaging techniques in X-ray, MRI, endoscopy, and ultrasound diagnostics yield a great deal of information that the radiologist or other medical professional has to analyze and evaluate comprehensively in a short time. CAD systems process digital images or videos for typical appearances and to highlight conspicuous sections, such as possible diseases, in order to offer input to support a decision taken by the professional.

<span class="mw-page-title-main">ITK-SNAP</span> Medical imaging software

ITK-SNAP is an interactive software application that allows users to navigate three-dimensional medical images, manually delineate anatomical regions of interest, and perform automatic image segmentation. The software was designed with the audience of clinical and basic science researchers in mind, and emphasis has been placed on having a user-friendly interface and maintaining a limited feature set to prevent feature creep. ITK-SNAP is most frequently used to work with magnetic resonance imaging (MRI), cone-beam computed tomography (CBCT) and computed tomography (CT) data sets.

<span class="mw-page-title-main">Cardiac magnetic resonance imaging</span> Biomedical imaging technology

Cardiac magnetic resonance imaging, also known as cardiovascular MRI, is a magnetic resonance imaging (MRI) technology used for non-invasive assessment of the function and structure of the cardiovascular system. Conditions in which it is performed include congenital heart disease, cardiomyopathies and valvular heart disease, diseases of the aorta such as dissection, aneurysm and coarctation, coronary heart disease. It can also be used to look at pulmonary veins.

<span class="mw-page-title-main">3D Slicer</span> Image analysis and scientific visualization software

3D Slicer (Slicer) is a free and open source software package for image analysis and scientific visualization. Slicer is used in a variety of medical applications, including autism, multiple sclerosis, systemic lupus erythematosus, prostate cancer, lung cancer, breast cancer, schizophrenia, orthopedic biomechanics, COPD, cardiovascular disease and neurosurgery.

Yi Wang is the Faculty Distinguished Professor of Radiology and professor of biomedical engineering at Cornell University. He is a Fellow of the American Institute for Medical and Biological Engineering (2007), the IEEE, and a Senior Fellow of the International Society for Magnetic Resonance in Medicine (ISMRM).

Bin He is a Chinese American biomedical engineering scientist. He is the Trustee Professor of the Department of Biomedical Engineering, professor by courtesy in the Department of Electrical and Computer Engineering, and Professor of Neuroscience Institute, and was the head of the department of Biomedical Engineering at Carnegie Mellon University. Prior, he was Distinguished McKnight University Professor of Biomedical Engineering and Medtronic-Bakken Endowed Chair for Engineering in Medicine at the University of Minnesota. He previously served as the director of the Institute for Engineering in Medicine and the Center for Neuroengineering at the University of Minnesota. He was the Editor in Chief of the IEEE Transactions on Biomedical Engineering and serves as the editor in chief of IEEE Reviews in Biomedical Engineering. He was the president of the IEEE Engineering in Medicine & Biology Society (EMBS) from 2009 to 2010 and chair of International Academy of Medical and Biological Engineering from 2018 to 2021.

EOS is a medical imaging system designed to provide frontal and lateral radiography images, while limiting the X-ray dose absorbed by the patient in a sitting or standing position. The system relies on the high sensitivity of a detector invented by Georges Charpak, which earned him the 1992 Nobel prize. This technology not only enhances patient safety but also improves diagnostic accuracy, making EOS particularly valuable in monitoring musculoskeletal conditions and guiding orthopedic treatments.

Medical image computing (MIC) is an interdisciplinary field at the intersection of computer science, information engineering, electrical engineering, physics, mathematics and medicine. This field develops computational and mathematical methods for solving problems pertaining to medical images and their use for biomedical research and clinical care.

<span class="mw-page-title-main">Magnetic resonance velocimetry</span>

Magnetic resonance velocimetry (MRV) is an experimental method to obtain velocity fields in fluid mechanics. MRV is based on the phenomenon of nuclear magnetic resonance and adapts a medical magnetic resonance imaging system for the analysis of technical flows. The velocities are usually obtained by phase contrast magnetic resonance imaging techniques. This means velocities are calculated from phase differences in the image data that has been produced using special gradient techniques. MRV can be applied using common medical MRI scanners. The term magnetic resonance velocimetry became current due to the increasing use of MR technology for the measurement of technical flows in engineering.

<span class="mw-page-title-main">Ron Kikinis</span> American physician and scientist (born 1956)

Ron Kikinis is an American physician and scientist best known for his research in the fields of imaging informatics, image guided surgery, and medical image computing. He is a professor of radiology at Harvard Medical School. Kikinis is the founding director of the Surgical Planning Laboratory in the Department of Radiology at Brigham and Women's Hospital, in Boston, Massachusetts. He is the vice-chair for Biomedical Informatics Research in the Department of Radiology.

Maryellen L. Giger, is an American physicist who has made significant contributions to the field of medical imaging.

<span class="mw-page-title-main">Roderic I. Pettigrew</span> American medical imaging scientist and physician

Roderic Ivan Pettigrew is an American physicist, engineer, and physician who is CEO of EnHealth and Executive Dean for EnMed at Texas A&M University. From 2002-November 2017, he was the founding director of the National Institute of Biomedical Imaging and Bioengineering (NIBIB) at the National Institutes of Health (NIH). He is a pioneer and world expert in cardiovascular magnetic resonance imaging (MRI).

<span class="mw-page-title-main">Vince Calhoun</span> American engineer and neuroscientist (Born 1967)

Vince Daniel Calhoun is an American engineer and neuroscientist. He directs the Tri-institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), a partnership between Georgia State University, Georgia Institute of Technology, and Emory University, and holds faculty appointments at all three institutions. He was formerly the President of the Mind Research Network and a Distinguished Professor of Electrical and Computer Engineering at the University of New Mexico.

Luis Marti-Bonmati is a Spanish professor and researcher. He is the director of the Clinical Area of Medical Imaging Department at La Fe Polytechnic and University Hospital, and Head of Radiology Department at QuironSalud Hospital, Valencia, Spain. Marti-Bonmati is the founder of QUIBIM S.L., and is the Director of its Scientific Advisory Board. He is a member of the Spanish National Royal Academy of Medicine. He is also the director of the Biomedical Imaging Research Group (GIBI230) at La Fe Health Research Institute. The group is now included in the Imaging La Fe node at Distributed Network for Biomedical Imaging (ReDIB) Unique Scientific and Technical Infrastructures (ICTS), Valencia, Spain.

<span class="mw-page-title-main">Leslie Ying</span> Biomedical engineer

Leslie Ying is an American biomedical engineering scientist in the field of medical imaging. She is the Clifford C. Furnas Professor of Biomedical Engineering and Electrical Engineering at University at Buffalo, The State University of New York. Ying is the Editor-in-Chief of IEEE Transactions on Medical Imaging and is also an American Institute for Medical and Biological Engineering (AIMBE) Fellow.

Jerry Ladd Prince is the William B. Kouwenhoven Professor of Electrical and Computer Engineering at Johns Hopkins University. He has over 44,000 citations, and an h-index of 85.

<span class="mw-page-title-main">Michael Unser</span> Swiss engineer (born 1958)

Michael Unser (born April 9, 1958 in Zug, Switzerland) is a Swiss engineer and a professor at the École Polytechnique Fédérale de Lausanne (EPFL). His research focuses on the field of biomedical image processing.

Daniel Kevin Sodickson is an American physicist and an expert in the field of biomedical imaging. A past president and gold medalist of the International Society for Magnetic Resonance in Medicine, he is credited with foundational work in parallel magnetic resonance imaging (MRI), in which distributed arrays of detectors are used to gather magnetic resonance images at previously inaccessible speeds. Sodickson is an elected Fellow of the US National Academy of Inventors. He currently serves as Vice-Chair for Research in the Department of Radiology at New York University (NYU) Grossman School of Medicine, as Director of the department's Bernard and Irene Schwartz Center for Biomedical Imaging, as Principal Investigator of the Center for Advanced Imaging Innovation and Research, and as Co-Director of NYU's Tech4Health Institute.

<span class="mw-page-title-main">Ge Wang (scientist)</span> Medical imaging scientist

Ge Wang is a medical imaging scientist focusing on computed tomography (CT) and artificial intelligence (AI) especially deep learning. He is the Clark & Crossan Chair Professor of Biomedical Engineering and the Director of the Biomedical Imaging Center at Rensselaer Polytechnic Institute, Troy, New York, USA. He is known for his employment on CT and AI-based imaging. He is Fellow of American Institute for Medical and Biological Engineering (AIMBE), Institute of Electrical and Electronics Engineers (IEEE), International Society for Optics and Photonics (SPIE), Optical Society of America (OSA/Optica), American Association of Physicists in Medicine (AAPM), American Association for the Advancement of Science (AAAS), and National Academy of Inventors (NAI).

References

  1. "Interview with Dr. Amir A. Amini". 10 May 2016.
  2. 1 2 3 4 5 "Amir Amini".
  3. "BME Lecture Series: Amir Amini, University of Louisville | Samueli School of Engineering at UC Irvine". engineering.uci.edu. 14 March 2024.
  4. "Past Event Overview | SPIE, the international society for optics and photonics: SPIE".
  5. 1 2 "Amir Amini — Bucks For Brains". louisville.edu.
  6. 1 2 https://www.embs.org/wp-content/uploads/2018/10/AMINI-bio.pdf
  7. "Amir Amini". J.B. Speed School of Engineering - University of Louisville.
  8. "Center for AI in Radiological Sciences — School of Medicine University of Louisville". louisville.edu.
  9. https://www.embs.org/wp-content/uploads/2019/02/2007-Awards-booklet.pdf
  10. "ISBI 2018".
  11. "Amir A. Amini, Ph.D. COF-2087 - AIMBE".
  12. "Complete list of SPIE Fellows". spie.org.
  13. "Asia-Pacific Artificial Intelligence Association". www.aaia-ai.org.
  14. "IEEE Engineering in Medicine and Biology Society". IEEE Transactions on Biomedical Engineering. 68 (9): C2. September 2021. doi:10.1109/TBME.2021.3097622.
  15. "Associate Editors".
  16. "Associate Editors".
  17. "Dr. Amini's Groundbreaking Research Receives $430,000 NIH Grant to Revolutionize Valvular Heart Disease Diagnostics". J.B. Speed School of Engineering - University of Louisville. October 4, 2023.
  18. "NSF Award Search: Award # 9796207 - Vision Algorithms for Analysis of Tissue and Fluid Deformations from Medical Images". www.nsf.gov.
  19. Cardiovascular and Neurovascular Imaging. CRC. 2015. p. 311. ISBN   978-1-4398-9057-8.
  20. “4D UTE Flow: A Phase-Contrast MRI Technique for Assessment and Visualization of Stenotic Flows,” M. Kadbi, M. Negahdar, J. Cha, M. Traughber, P. Martin, M. Stoddard, and A. Amini, Magn Reson Med, 73(3), 939-950, March 2015.
  21. “4D Spiral Imaging of Flows in Stenotic Phantoms and Subjects with Aortic Stenosis,” MJ Negahdar, Mo Kadbi, M. Kendrick, R. Longaker, M. Stoddard, A. Amini, Magnetic Resonance in Medicine, Volume 75, No. 3, Pages 1018-1029, March 2016. DOI: 10.1002/mrm.25636
  22. “Dual-Venc Acquisition for 4D Flow MR Imaging of Aortic Stenosis with Spiral Read-Outs”, Sean Callahan, Narayana Singam, Michael Kendrick, MJ Negahdar, Hui Wang, Marcus Stoddard, A. Amini, Journal of Magnetic Resonance Imaging, Vol. 52, No. 1, pages 117-128, July 2020.
  23. “FlowRAU-Net: Accelerated 4D Flow MRI of Aortic Valvular Flows with a Deep 2D Residual Attention Network,” R. Nath, S. Callahan, M. Stoddard and A. A. Amini, IEEE Transactions on Biomedical Engineering, 2022, doi: 10.1109/TBME.2022.3180691.
  24. “Factors Affecting the Accuracy of Pressure Measurements in Vascular Stenoses from PC MRI,” Abbas Nasiraei-Moghaddam, Nasser Fatouraee, Geoffrey Behrens, Ramesh Agarwal, Eric Choi, and Amir A. Amini, Magnetic Resonance in Medicine, Volume 52, No. 2, pp. 300-309, August 2004.
  25. Relative Pressure Estimation from 4D Flow MRI Using Generalized Bernoulli Equation in a Phantom Model of Arterial Stenosis, Amirkhosro Kazemi, Daniel Adam Padgett, Sean Callahan, Marcus Stoddard, and Amir A Amini, Magnetic Resonance Materials in Physics, Biology and Medicine, Vol. 35, pp. 733–748, 2022.
  26. “4Dflow-VP-Net: A Deep Convolutional Neural Network for Non-Invasive Estimation of Relative Pressures in Stenotic Flows from 4D Flow MRI”, R. Nath, Amirkhosro Kazemi, S. Callahan, M. Stoddard and A. A. Amini, Magn Reson Med. 2023; 90(5): 2175-2189. doi: 10.1002/mrm.29791
  27. “AI in Medical Imaging Informatics: Current Challenges and Future Directions,” A. S. Panayides, A. Amini, et al., IEEE Journal of Biomedical Health Informatics, (24)7:1837-1857, July 2020.
  28. “Lung Nodule Malignancy Prediction from Longitudinal CT Scans with Siamese Convolutional Attention Networks,” B. P. Veasey, J. Broadhead, M. Dahle, A. Seow, and A. Amini, IEEE Open Journal of Engineering in Medicine and Biology, vol. 1, pp. 257-264, 2020.
  29. “Recurrent Attention Network for False Positive Reduction in the Detection of Pulmonary Nodules in Thoracic CT Scans” M. Farhangi, N. Petrick, B. Sahiner, H. Frigui, A. Amini, A. Pezeshk, Medical Physics, DOI: 10.1002/mp.14076 February 2020.
  30. "3D Active Contour Segmentation Based on Sparse Linear Combination of Training Shapes (SCoTS)”, M. Farhangi, H. Frigui, A. Seow, and A. Amini, IEEE Trans. On Medical Imaging, Vol. 36, Issue 11, Nov. 2017, pp. 2239-2249
  31. “Tagged MRI Analysis Techniques: I”, I. El-Sayed, A. Hussanein, H. Wang, and A. Amini, Chapter 15 of Heart Mechanics: Magnetic Resonance Imaging – Advanced Techniques, Clinical Applications and Future Trends, I. El-Sayed (Ed.), CRC Press, May 2017.
  32. “Cardiac Motion and Deformation Recovery from MRI: A Review,” H. Wang and A. Amini, IEEE Trans on Med Imaging, , Vol. 31, No. 2, pp. 487-503, Feb. 2012.
  33. “Analysis of 3D Cardiac Deformations with 3D SinMod,” Hui Wang, C. Stoeck, S. Kozerke, and A. Amini, Conf Proc IEEE Eng Med Biol Soc. 2013;2013:4386-9. (United States Patent 10776998 9/15/2020)
  34. Segmentation and Tracking of Lung Nodules via Graph-Cuts Incorporating Shape Prior and Motion from 4D CT”, J. Cha, M. Farhangi, N. Dunlap, and A. Amini, Medical Physics, vol. 45, no. 1, pp. 297-306, January 2018
  35. “Tissue Doppler Imaging Optical Flow (TDIOF): A Combined B-Mode and Tissue Doppler Approach for Cardiac Motion Estimation in Echocardiographic Images,” V. Tavakoli, N. Bhatia, M. Stoddard, and A. Amini, IEEE Trans. on Biomedical Engineering, 61(8):2264-2277, 2014, doi:10.1109/TBME.2014.2299551.
  36. “Comparison of Indices of Regional Lung Function from 4D CT: Jacobian vs. Strain of Deformation”, M.R., N. Dunlap, A. Zacarias, A. C. Civelek, S.Y. Woo, and A. Amini, International Symposium on Biomedical Imaging, San Francisco, CA, April 2013.
  37. “A Survey of Shaped-Based Registration and Segmentation Techniques for Cardiac Images,” V. Tavakoli and A. Amini, Computer Vision and Image Understanding, 117 (9), 966-989, September 2013.
  38. "Alumni Awards : College of Engineering : UMass Amherst".