Print Print Send link Bookmark and Share

Biosignal and medical image processing and interpretation

Competence

We combine top-level technical expertise in the fields of signal processing, image processing, statistics, data-mining and pattern recognition with the understanding of healthcare-domain specific challenges to create solutions, simply for a better life.

Challenges

Technological advances have made possible the acquisition, processing, and storing of huge amounts of biological and medical data - inside hospitals, at home, or on the move. For example, a large number of different signals are acquired during surgery or critical care in hospitals. Modern hospitals produce dozens of terabytes of image data every year. Wearable biomedical sensors and systems provide health- and wellness-related data. Interpretation of this data requires deep understanding of measurement technologies, human behaviour and physiology, signal processing and interpretation methods.

It is a daunting task to extract from this huge amount of data the essential information that increases knowledge, improves quality of life, and reduces costs to society. It requires strong interdisciplinary knowledge, combining clinical and technical expertise, and the realisation that (a) every person is different, and no ‘generic’ solution exists, so personalised solutions are needed; and (b) much clinical knowledge is based on expertise and cannot be put into clear algorithms or rules.

Solutions

We provide technical expertise in biosignal and image processing to address clinically relevant problems. We also provide a deep understanding of application domains and the ability to communicate the practical implications of technical issues to healthcare professionals and industry (such as developers of monitoring or imaging systems).

We provide signal and image processing and interpretation methods for:

  • healthcare applications (patient monitoring, decision support and assistance)
  • signal acquisition and interpretation methods for pervasive and personalised health care (e.g., for fitness instruments, applications for health or chronic disease management or for independent living)
  • medical image-processing methods for image segmentation, registration, and computer-assisted diagnosis.

One of our emerging research areas is personalized healthcare, where we link information from physiological measurements down to genetic levels. Project activities are done in close collaboration with clinicians and partners from industry.

Benefits

  • Accessibility to a team of technical experts with long-standing experience in co-operation with industry and healthcare professionals
  • Knowledge of special issues (and typical pitfalls) associated with applying signal, image processing, and statistics in real-life healthcare settings

References and merits

Strong international links

IEEE/EMBS, IFMBE, EAMBES, editorial board memberships in various biomedical engineering journals, memberships in key organisations (especially in Europe), membership in IEEE TC in Wearable Biomedical Systems

Strong networking with healthcare professionals

Close and long-standing cooperation with healthcare professionals, such as clinicians from hospitals in Finland as well as abroad, and professionals in other healthcare organisations, patient organisations, etc.

Industrial partners: a wide variety of Finnish as well as international companies, ranging from global market players to Finnish SME’s (references available upon request).

Strong links to medical and health societies and a large number of publications during the last decade: over 100 original publications in scientific journals, over 100 publications in scientific conferences, several patents (and patents pending) related to biosignal and image processing – mostly transferred to our customers.

Otto Schmitt award and IEEE Fellowship in 2008 by Professor Niilo Saranummi


The surgical stress index is one example of a signal-processing method for use in patient monitoring during anaesthesia. It combines features from various signals to obtain an index of surgical stress. The method was developed in close co-operation between GE Healthcare and VTT. For details, see British Journal of Anaesthesia, 98(4) 447-55, 2007


Development of methods based on statistical atlases is a core competence in our medical-image processing activities.


Additional information

Kari Kohtamäki
Customer Manager
+358 20 722 6007

Mark van Gils
Senior research scientist (signal and image processing)
+358 20 722 3342

Additional information

Kari Kohtamäki
Customer Manager
+358 20 722 6007

Mark van Gils
Senior research scientist (signal and image processing)
+358 20 722 3342

See also

    Publications
    Examples of current EU projects: