Towards a Second Brain Images of Tumours for Evaluation (BITE2) Database
One of the main challenges facing members of the medical imaging community is the lack of real clinical cases and ground truth datasets with which to validate new registration, segmentation, and other image processing algorithms. In this work we present a collection of data from tumour patients acquired at the Montreal Neurological Institute and Hospital that will be released as a publicly available dataset to the image processing community. The database is comprised of 9 patient data sets, in its initial release, that consist of a preoperative and postoperative, gadolinium enhanced T1w MRI, pre- and post- resection tracked intra-operative ultrasound slices and volumes, expert tumour segmentations following the BRATS benchmark, and intra-operative ultrasound with/and MRI registration validation target points. This database extends the already widely used BITE database by improving the quality of registration validation and the variety of data being made available. By including addition features such as expert tumour segmentations, the database will appeal to a broader spectrum of image processing researchers and be useful for validating a wider range of techniques for image-guided neurosurgery.
KeywordsDatabase Validation Medical imaging Intra-operative ultrasound
- 3.Guizard, N., et al.: Robust individual template pipeline for longitudinal MR images. In: MICCAI 2012 Workshop on Novel Biomarkers for Alzheimer’s Disease and Related Disorders (2012)Google Scholar
- 6.Gerard, I.J., Kersten-Oertel, M., Drouin, S., Hall, J.A., Petrecca, K., Nigris, D., Arbel, T., Louis Collins, D.: Improving patient specific neurosurgical models with intraoperative ultrasound and augmented reality visualizations in a neuronavigation environment. In: Oyarzun Laura, C., Shekhar, R., Wesarg, S., González Ballester, M.Á., Drechsler, K., Sato, Y., Erdt, M., Linguraru, M.G. (eds.) CLIP 2015. LNCS, vol. 9401, pp. 28–35. Springer, Heidelberg (2016). doi: 10.1007/978-3-319-31808-0_4 CrossRefGoogle Scholar
- 8.Gerard, I.J., Collins, D.L.: An analysis of tracking error in image-guided neurosurgery. Int. J. Comput. Assist. Radiol. Surg. (2015)Google Scholar
- 10.Gerard, I.J., et al.: The validation grid: a new tool to validate multimodal image registration. Int. J. CARS 11(1), S1–S316 (2016)Google Scholar