Machine Learning and Big Data Analysis Group

In close collaboration with clinical partners from the University Hospital of Zurich (Department of Radiation Oncology, Nuclear Medicine, Rheumatology and Cardiology) the Big Data, Texture Analysis and Machine Learning Research group aims to integrate research and to build collaborations between basic scientists, clinical scientists, physicians, and radiologists establishing a strong resource for imaging-based research at the University of Zurich. There is also close collaboration with the Computer Vision Laboratory at the Department of Information Technology and Electrical Engineering of the ETH Zurich.

Ongoing projects include studies on new developments for multi-modality imaging including CT, and MR imaging and ultrasound, using a huge variety of custom-made and freely available software tools. Typical research questions address efficiency improvements in the clinical workflow by automatic detection and classification of benign and malignant lesions, correlative reseach regarding imaging features and underlying molecular genetics (radiogenomics), as well as improved treatment monitoring using techniques of machine learning. 

From the University of Zurich

Medical students, master students, and fellows

From the Department of Information Technology and Electrical Engineering of the ETH Zurich

Prof. Dr. E. Konukoglu

Imaging Resources

• X-ray (different vendors)
• DEXA und pQCT (Lunar, XCT 3000)
• Dual-Source/-energy CT (2x 128; Siemens Somatom Force, Flash and Definition Edge)
• MRI (different vendors ; 1 x 1.5T; 8 x 3.0T; 1 x 7.0T)
• Fluoroscopy (GE and Siemens, 4x)
• PET-CT (GE, 2x)
• PET-MR (GE, 1x)
• 3D Lab

Software Resources

• ViDi Suite
• MaZda
• Weka
• ScikitLearn
• Tensor Flow
• Keras
• Various Matlab Codes