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.
Current Research Projects
Five scientific publications accepted at SPIE Medical Imaging 2015 Conference: Computational Radiology Lab goes to Orlando, Florida
Congratulations to Adora DSouza on receiving the CFAR World AIDS Day Symposium Graduate Student Poster Award!
- Integrating Dimension Reduction and Out-of-Sample Extension in Automated Classification of Ex Vivo Human Patellar Cartilage on Phase Contrast X-Ray Computed Tomography. PLoS One. 10, e0117157. (2015 Jan 01).
- Improving bone strength prediction in human proximal femur specimens through geometrical characterization of trabecular bone microarchitecture and support vector regression. J Electron Imaging. 23, 013013. (2014 Feb 04).
- Computer-aided diagnosis for phase-contrast X-ray computed tomography: quantitative characterization of human patellar cartilage with high-dimensional geometric features. J Digit Imaging. 27, 98-107. (2014 Feb 01).