Image Analysis Ltd combines leading expertise in medical imaging and advanced computer science to bring practical innovation to the computer-aided diagnosis market.
Our new generation of computer-aided detection (CAD) software solutions provide the very latest technological advancements to radiologists, clinics and researchers.
The software solutions have been specifically designed and developed in conjunction with leading medical experts in rheumatology, oncology and general radiology.
Radiology Residency and Fellowship
n\a
Undergraduate, Medical School, and Graduate School (Degrees, Major, and Institution)
Expertise:
PhD in Computer Science, University of Leeds, Leeds
MSc in Mathematics, Saint Petersburg State University
Msc in Information Technology in Finland
Clinical, Academic, or Industry Experience
MRI, DCE-MRI, CT, US
Clinical, academic, research, or business interests within radiology
Rheumatology, oncology, neurology. Focus on development of innovative solutions for rheumatoid arthritis and breast cancer diagnosis and diagnostic decision support. Interest in
-state of the art noise reducing algorithms
-fast and efficient real-time image processing
-intuitive user interface
-comprehensive parametric maps showing broad-ranging kinetic parameters
-threshold independent analysis
plus automated region of interest placement, and more
Publications, Honors, and Awards
most recent
[1] Olga Kubassova, Mikael Boesen, Marco A. Cimmino, and Henning Bliddal, Computer-aided detection of
disease activity in rheumatoid arthritis: a novel software tool, Dynamika, for enhancing scoring efficacy
and quantification, In press, 2009.
[2] Mikael Boesen, Mikkel Ostergaard, Marco Cimmino, Olga Kubassova, Karl Erik Jensen, and Henning
Bliddal, MR quantifiation of rheumatoid arthritis: Current knowledge and future perspectives, European
Journal of Radiology, In press, 2009
[3] Olga Kubassova, Mikael Boesen, Henning Bliddal et al. Book Chapter `Quantifying Damage: scoring
systems in RA and OA', In `MRI and Ultrasound in the Diagnosis and Management of Rheumatological
Diseases', James D. Katz and Kathleen Brindle, Editors. Annals of the New York Academy of Sciences,
New York, NY. 2008.
[4] Henning Bliddal, Mikael Boesen, Robin Christensen, Olga Kubassova, and Soren Torp-Pedersen, Book
chapter 'Imaging as a follow-up tool in clinical trials and clinical practice' In `Best Practice & Research in
Clinical Rheumatology', Marco Cimmino, Prof Maurizio Cutolo and Walter Grassi, Editors Vol. 22, No 6,
pp. 1109{1126, 2008.
[5] Olga Kubassova, Mikael Boesen, and Henning Bliddal, General Framework for Unsupervised Evaluation of
Quality of Segmentation results. In IEEE International Conference of Image Proccessing, WP-PE.8, 2008,
October, 2008.
[6] Olga Kubassova, Roger Boyle, and Mikael Boesen Impact of Registration on Enhancement Curve Estima-
tion in DCE-MRI Data. In Proceedings workshop on Functional Image Analysis of International Conference
on Medical Image Computing and Computer Assisted Intervention,2008.
[8] O. Kubassova, R. D. Boyle, and A. Radjenovic. Quantitative Analysis of Dynamic Contrast-Enhanced MRI
Datasets of the Metacarpophalangeal Joints. In Journal of Academic Radiology, volume 14, number 10 pages
2007.
[9] O. Kubassova, M. Boesen, R. D. Boyle, M. A. Cimmino, K. E. Jensen, H. Bliddal, and A. Radjenovic.
Fast and robust analysis of dynamic contrast enhanced MRI datasets. In Proceedings of International
Conference on Medical Image Computing and Computer Assisted Intervention, 2007.
[10] O. Kubassova. Automatic segmentation of blood vessels from dynamic MRI datasets. In Proceedings of
International Conference on Medical Image Computing and Computer Assisted Intervention, 2007
.
[11] O. Kubassova, R. D. Boyle, and A. Radjenovic. Novel method for quantitative evaluation of segmentation
outputs for dynamic contrast-enhanced MRI data in RA studies. In Proceedings of Joint Disease Workshop,
International Conference on Medical Image Computing and Computer Assisted Intervention, 2006.
[12] O. Kubassova, R. D. Boyle, and A. Radjenovic. Improved parameter extraction from dynamic contrast-
enhanced MRI data in RA studies. In Proceedings of Joint Disease Workshop, International Conference
on Medical Image Computing and Computer Assisted Intervention, 2006.
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