A Hybrid Model for Multimodal Brain Tumor Segmentation

Meier, Raphael; Bauer, Stefan; Slotboom, Johannes; Wiest, Roland; Reyes, Mauricio (2013). A Hybrid Model for Multimodal Brain Tumor Segmentation. NCI-MICCAI Challenge on Multimodal Brain Tumor Segmentation. Proceedings of NCI-MICCAI BRATS 2013, pp. 31-37. Nagoya: Miccai Society

Full text not available from this repository. (Request a copy)

We present a fully automatic segmentation method for multi-modal brain tumor segmentation. The proposed generative-discriminative hybrid model generates initial tissue probabilities, which are used subsequently for enhancing the classi�cation and spatial regularization. The model has been evaluated on the BRATS2013 training set, which includes multimodal MRI images from patients with high- and low-grade gliomas. Our method is capable of segmenting the image into healthy (GM, WM, CSF) and pathological tissue (necrotic, enhancing and non-enhancing tumor, edema). We achieved state-of-the-art performance (Dice mean values of 0.69 and 0.8 for tumor subcompartments and complete tumor respectively) within a reasonable timeframe (4 to 15 minutes).

Item Type:

Conference or Workshop Item (Paper)

Division/Institute:

04 Faculty of Medicine > Department of Radiology, Neuroradiology and Nuclear Medicine (DRNN) > Institute of Diagnostic and Interventional Neuroradiology
04 Faculty of Medicine > Pre-clinic Human Medicine > Institute for Surgical Technology & Biomechanics ISTB

UniBE Contributor:

Meier, Raphael; Slotboom, Johannes and Wiest, Roland

Subjects:

600 Technology > 610 Medicine & health
500 Science > 570 Life sciences; biology

Publisher:

Miccai Society

Language:

English

Submitter:

Martin Zbinden

Date Deposited:

25 Jun 2014 16:41

Last Modified:

25 Jun 2014 16:41

Related URLs:

URI:

https://boris.unibe.ch/id/eprint/48410

Actions (login required)

Edit item Edit item
Provide Feedback