Skip to main content
Explore URMC

menu

  • wismuller lab photo 1
  • wismuller lab photo 2
  • wismuller lab photo 3
  • wismuller lab photo 4
  • wismuller lab photo 5

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.

Publications

    1. DSouza AM
    2. Abidin AZ
    3. Schifitto G
    4. Wismüller A
    A multivoxel pattern analysis framework with mutual connectivity analysis investigating changes in resting state connectivity in patients with HIV associated neurocognitive disorder; Magnetic Resonance Imaging; Vol 62, pp. 121-128. 2019 Jan 01.
    1. Chockanathan U
    2. DSouza AM
    3. Abidin AZ
    4. Schifitto G
    5. Wismüller A
    Automated diagnosis of HIV-associated neurocognitive disorders using large-scale Granger causality analysis of resting-state functional MRI; Computers in Biology and Medicine; Vol 106, pp. 24-30. 2019 Jan 01.
    1. DSouza AM
    2. Abidin AZ
    3. Wismüller A
    Classification of autism spectrum disorder from resting-state fMRI with mutual connectivity analysis; Proc. of SPIE; Vol 109531D. 2019 Jan 01.
    1. Abidin AZ
    2. Dsouza AM
    3. Wismüller A
    Detecting connectivity changes in autism spectrum disorder using large-scale Granger causality; Proc. of SPIE; Vol 109490M. 2019 Jan 01.
    1. DSouza AM
    2. Abidin AZ
    3. Wismüller A
    Automated identification of thoracic pathology from chest radiographs with enhanced training pipeline; Proc. of SPIE; Vol 109503F. 2019 Jan 01.
    1. Abidin AZ
    2. Dar R
    3. D'Souza AM
    4. Lin EP
    5. Wismüller A
    Investigating a quantitative radiomics approach for brain tumor classification; Proc. of SPIE; Vol 109530B. 2019 Jan 01.
    1. DSouza AM
    2. Abidin AZ
    3. Chockanathan U
    4. Schifitto G
    5. Wismüller A
    Mutual connectivity analysis of resting-state functional MRI data with local models.; NeuroImage. 2018 May 16.

View All Publications

Contact Us

  Wismüller Lab
601 Elmwood Ave, Box 608
Rochester, NY 14642