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Image-guided neurosurgery

The main goal is to improve the clinical understanding of relationships between clinical/radiological characteristics, disease courses and treatment responses in brain tumor patients. This will enable improved classification and improve patient selection and choice of treatment. We use machine learning to build computer models to predict the clinical outcome of brain tumor patients considering at the same time the characteristics of the individual patient and data from hundreds of previous patients.

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Approximately 1000 people are diagnosed with cancer in the central nervous system in Norway every year (Norwegian cancer registry). Brain cancer is the deadliest cancer type in people under the age of 40 and one of the most common types of cancer in children. The tumors are heterogeneous and there is great variability in aggressiveness, growth rate and treatment responses. Symptoms and prognosis vary widely and can be difficult to predict even for experienced doctors. To improve the clinical understanding of disease courses and treatment responses The Brain tumor registry and biobank of Mid-Norway was established in 2015 by clinicians and researchers at St. Olavs hospital and NTNU. Based on the data in this registry and data from national and international collaborators, researchers at SINTEF develop computer models to automatically analyze images, predict known prognostic factors and disease course using artificial intelligence and machine learning algorithms.

More specifically, we use deep learning methods to:

(1) Develop tools for quantitative radiological assessment of brain tumors. This includes automatic segmentation of pre-operative, intraoperative, post-operative and follow-up MR/CT/US images to

a. quantify initial tumor localization and volume
b. characterize tumor resection during surgery,
c. quantify residual tumor localization and volume
d. assessment of tumor response to radiation/chemotherapy
e. quantify tumor regrowth.

(2) Combine the use of clinical and radiological data for personalized prediction of clinically important parameters such as survival and post-operative functional level.





Key Factors

Project start



Norwegian National Advisory Unit for Ultrasound and Image Guided Therapy

Cooperation Partners

St. Olavs hospital and NTNU

Project Type 

Norwegian National Advisory Unit

Project Members