The software Brain Tumor Image Analysis (BraTumIA) has been developed in collaboration with the medical image analysis group (Prof. Reyes) of the Institute of Surgical Technology & Biomechanics (ISTB) at the University of Bern. BraTumIA offers an automatic tumor segmentation of pre- and postoperative Magnetic Resonance (MR) images of glioblastoma patients. It requires T1-weighted images, T1-weighted gadolinium-enhanced images, T2-weighted images and FLAIR images as input data. BraTumIA relies on machine learning techniques to solve the problem of tumor segmentation and comes with a Graphical User Interface (GUI) (see Figure 1). It can be downloaded for free. For more information, please check our recent publication [1] and visit the website of BraTumIA



Figure 1: Graphical User Interface of BraTumIA. The glioblastoma is segmented into necrosis (red), edema (blue), enhancing (yellow) and non-enhancing tumor (pink).



[1] Meier R., Knecht U., Loosli T., Bauer S., Slotboom J., Wiest R., and Reyes M.. Clinical Evaluation of a Fully-automatic Segmentation Method for Longitudinal Brain Tumor Volumetry. Nature Scientific Reports, 6, 2016.

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