Wismüller Lab
Welcome to the Wismüller Lab
The mission of Professor Wismüller's research group is to develop novel intuitively intelligible computational visualization methods for the exploratory analysis of high-dimensional data from biomedical imaging. Specifically, the focus of our research is on developing robust and adaptive systems for computer-aided analysis and visualization which combine principles and computational strategies inspired by biology with machine learning and image processing/computer vision approaches from electrical engineering and computer science.
Research efforts in Professor Wismüller's group are taking place at two complementary levels:
- Mathematical algorithms for computational image analysis
- Pattern recognition in clinical real-world applications
Application areas range from functional MRI for human brain mapping, MRI mammography for breast cancer diagnosis, image segmentation in Multiple Sclerosis and Alzheimer's Dementia to multi-modality fusion, biomedical time-series analysis, and quantitative bio-imaging. Professor Wismüller's laboratory is located in the Rochester Center for Brain Imaging, which houses a whole body 3T Siemens MRI Scanner and several high field magnets.
Axel W. E. Wismueller, M.D., M.Sc., Ph.D.
Principal Investigator
Projects
View All Projects
Publications
View All Publications- Early-stage COVID-19 pandemic observations on pulmonary embolism using nationwide multi-institutional data harvesting.; NPJ digital medicine; Vol 5(1), pp. 120. 2022 Aug 19.
- Large-scale nonlinear Granger causality for inferring directed dependence from short multivariate time-series data.; Scientific reports; Vol 11(1). 2021 Apr 09.
- 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 Jan 01.
- Large-scale Augmented Granger Causality (lsAGC) for Connectivity Analysis in Complex Systems: From Computer Simulations to Functional MRI (fMRI); Proc. of SPIE. Accepted for publication.. 2021 Jan 01.
- Network Connectivity Analysis in Complex Systems Using Large-Scale Non-Linear Granger Causality (lsNGC); Proc. of SPIE. Accepted for publication.. 2021 Jan 01.
- Large-Scale Extended Granger Causality for Classification of Marijuana Users From Functional MRI; Proc. of SPIE. Accepted for publication.. 2021 Jan 01.
- Detecting cognitive impairment in HIV-infected individuals using mutual connectivity analysis of resting state functional MRI.; Journal of neurovirology. 2020 Jan 07.
News
Affiliations
April 20, 2017
Watch how the A-Team won the RocHackHealth Health Care Data Hackathon
March 6, 2017
Congratulations to Adora on Receiving the SPIE Medical Imaging 2017 Travel Grant
February 12, 2017
SPIE Medical Imaging 2017 Conference, Orlando, Florida: Wismüller Lab Delivers Five Scientific Oral Presentations
January 9, 2017
Wismüller Laboratory Attends RSNA 2016 (Nov. 27 - Dec. 2)
Contact Us
Wismüller Lab
601 Elmwood Ave, Box 608
Rochester, NY 14642