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Axel W. E. Wismueller, M.D., M.Sc., Ph.D.

Contact Information

Phone Numbers

Appointment: (585) 784-2985

Administrative: (585) 273-1971

Fax: (585) 276-2851

URMFGA member of the University of Rochester Medical Faculty Group

groupAn Accountable Health Partner

assignmentAccepting New Patients

Research Labs

Faculty Appointments

Patient Care Setting

Imaging Sciences


Professional Background

Dr. Axel W. E. Wismüller is one of the pioneers of Artificial Intelligence (AI) in radiology. With a 25+ years outstanding leadership, funding and publication track record, he is one of very few individuals worldwide serving as both a clinically practicing radiologist and an internationally renowned scientist, thus bridging the gap between fundamental research and clinical application of AI in radiology.

Dr. Wismüller is Professor of Radiology, Biomedical & Electrical Engineering. He is Director of the AI Radiology Laboratory at URMC. In his clinical practice, he serves as an Attending Radiologist for cardiothoracic and body imaging, including CT, MRI and ultrasound. Based on his dual professional qualification in both science and medicine, his funded research focuses on developing and clinically evaluating cutting-edge machine learning, AI and health informatics technologies to expedite patient- and provider-centered image interpretation, clinical understanding, and efficient health care management – with the overall goal to improve patient health and well-being.

Dr. Wismüller holds multiple national and international patents for his inventions of novel machine learning methods. He is author of >220 peer-reviewed scientific publications, holds US and European medical licenses, US and German Board Certifications in Diagnostic Radiology, and a state doctorate (Habilitation) with adjunct professorship at Ludwig Maximilian University (LMU) Munich. Dr. Wismüller has recently been elected and honored as a Senior Member of the International Society for Optics (SPIE) for his outstanding contributions to AI in medical imaging. He has served as a founding faculty member of the Goergen Institute for Data Science.

Dr. Wismüller is widely known for clinical applications of his research, which most notably include a system for automatic analysis of chest radiographs, imaging biomarkers for breast cancer and brain tumor diagnosis, bone stability prediction in osteoporosis, and imaging assessment of neuroinflammatory disorders, such as MS.

Dr. Wismüller attended medical school in Munich, with additional clinical training at Yale University. He received his MD degree from Technical University of Munich (TUM) in 1992, which included a scientific dissertation in neurology. In addition, he received a MSc degree in Physics from LMU, which included a master's thesis on machine learning. From 1997 to 2007, he completed his radiology residency and a fellowship in Diagnostic Radiology at LMU Medical Center, where he founded and directed an interdisciplinary research laboratory on AI in radiology. In 2006, he received a PhD degree in Electrical and Computer Engineering at the highest-ranked German engineering school, TUM, for a PhD thesis on a novel machine learning algorithm invented by him (XOM), for which he holds national and international patents.

Dr. Wismüller has been the PI of a NIH R01 Award on exploring large-scale functional connectivity in the human brain. Supported by NIDA and its AIDS research program, the CRCNS program of the National Science Foundation (NSF), and co-funded by the German Research Ministry, this international project led to fundamental discoveries in the field of brain connectivity analysis, which were published in highest-ranked neuroradiology journals NeuroImage and NeuroImage:Clinical.

As an active member of multiple societies in both medicine and engineering, e.g. ACR, RSNA and SPIE, Dr. Wismüller has served on numerous academic and administrative committees in both the US and Europe. He has successfully supervised scientific theses of >30 post-doctoral fellows, PhD and MSc students from engineering, computer science, mathematics, biology and academic medicine at both leading US and European universities. Besides NIH-funded awards, he has served as the PI in a multi-center CTSI translational research award and in several NYSTAR-funded public-private research projects with leading industry partners.



MD | Technical University Of Munich (Germany)

PHD | Technical University Of Munich (Germany)

Post-doctoral Training & Residency

04/01/2005 - 01/31/2007
Fellowship in Radiology, General at University Hospitals

01/01/1997 - 03/31/2005
Residency in Radiology, General at University Hospitals

11/01/1990 - 06/04/1996
Graduate at Ludwig-Maximilians-Universitaet Munchen (Germany)

07/01/1989 - 12/31/1990
Residency in Internal Medicine at University Hospitals

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2020 - Present
Mangurian Foundation Research Award: Exploring Large-Scale Network Connectivity in the Human Brain

2018 - Present
Goergen Institute for Data Science, Research Award: Deep Machine Learning for Radiomics in Cancer Diagnostics

2016 - Present
Senior Membership Award for outstanding contributions in the field of Artificial Intelligence in medical imaging
Sponsor: International Society for Optics and Photonics - SPIE

2012 - Present
Principal Investigator, National Institutes of Health (NIH)/NIDA R01 Award
Sponsor: Brain Connectivity in HIV-Related Cognitive Impairment
Location: Supported by NIDA and co-funded by German Ministry of Research

Harry W. Fischer Funds Award, University of Rochester Medical Center
Sponsor: Imaging for Oncoplastic Resections of Breast Cancer

Upstate New York Translational Research Network (UNYTRN) Award
Sponsor: Clinical and Translational Sciences Institute (CTSI)
Location: Multidimensional Imaging for Breast Cancer Diagnosis

Center for Emerging and Innovative Sciences (CEIS) Research Award: Computer-Aided Analysis of Interstitial Lung Disease Patterns
Sponsor: Funded by NYSTAR

Charles and Janet Forbes Entrepreneurial Award for Biomedical Engineering Senior Design Project
Sponsor: Department of Biomedical Engineering, University of Rochester
Location: Transportation Device for Urinalysis by Raman Spectroscopy

2003 - 2005
Ludwig Maximilians University Munich Research Grant
Location: Intelligent MRI Data Analysis

2000 - 2003
German Research Council (DFG) Graduate Research Program Award
Location: Speech, Mimics and Motion in Technical Information Systems

2000 - 2001
Max Planck Institute of Psychiatry Grant Award
Location: Segmentation of White Matter Lesions from Multispectral MRI Data

Institute of Phonetics Grant Award
Sponsor: Ludwig Maximilians University Munich
Location: MRI of the Human Vocal Tract

Novartis Pharmaceutical Corporation Grant Award
Sponsor: Segmentation of Lower Extremity Edema in MRI Data

1998 - 1999
Marconi Corporation Grant Award
Sponsor: MRI Segmentation and Registration

Max Planck Institute of Psychiatry Grant Award
Sponsor: Explorative Analysis of Functional MRI Data of the Human Brain

1997 - Present
Hanns Seidel Foundation, Senior Laureate Fellow

1996 - 1997
Hanns Seidel Foundation Postgraduate Fellowship Award

Wacker Chemical Corporation Research Grant Award
Location: Intelligent control of chemical waste combustion plants

Sun Microsystems Corporation Scientific Conference Organization Grant Award
Location: Symp. on Biological Information Processing and Neural Networks

Hanns Seidel Foundation Scientific Conference Organization Grant Award
Location: Symp. on Biological Information Processing and Neural Networks

1985 - 1989
Hanns Seidel Foundation Undergraduate Fellowship Award

1982 - 1986
State of Bavaria Scholarship Award for Outstanding Achievements

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Journal Articles

Wismüller A, DSouza AM, Abidin AZ, Ali Vosoughi M, Gange C, Cortopassi IO, Bozovic G, Bankier AA, Batra K, Chodakiewitz Y, Xi Y, Whitlow CT, Ponnatapura J, Wendt GJ, Weinberg EP, Stockmaster L, Shrier DA, Shin MC, Modi R, Lo HS, Kligerman S, Hamid A, Hahn LD, Garcia GM, Chung JH, Altes T, Abbara S, Bader AS. "Early-stage COVID-19 pandemic observations on pulmonary embolism using nationwide multi-institutional data harvesting." NPJ digital medicine.. 2022 Aug 19; 5(1):120. Epub 2022 Aug 19.

Wismüller A, Dsouza AM, Vosoughi MA, Abidin A. "Large-scale nonlinear Granger causality for inferring directed dependence from short multivariate time-series data." Scientific reports.. 2021 Apr 9; 11(1):7817. Epub 2021 Apr 09.

Axel Wismüller; Larry Stockmaster. "Investigating Covid-19 Pandemic-Induced Effects on Detection of Emergent Clinical Imaging Findings by Large-Scale Tracking of Utilization and Reading Results for AI-Based Image Analysis Services". Proc. of SPIE. Accepted for publication. 2021; .

Books & Chapters

Chapter Title: Segmentation with Neural Networks
Book Title: Handbook of Medical Imaging
Author List: Axel Wismüller
Edited By: Isaac N. Bankman
Published By: Academic Press; 2009 in Amsterdam, Boston, Heidelberg

Book Title: Computer Science in Biomedicine: Multidimensional Analysis of Spatio-Temporal Patterns. Thesis for State Doctorate (Habilitation)
Author List: Axel Wismüller
Published By: Faculty of Medicine, Ludwig Maximilian University (LMU); 2007 in Munich, Germany

Book Title: Exploratory Morphogenesis: A Novel Computational Framework for Self-Organization – Cross-Fertilization between Electrical, Biomedical, and Computer Engineering. Ph.D. Doctorate Thesis
Author List: Axel Wismüller
Published By: Technical University of Munich (TUM); 2006 in Munich, Germany