EPISURG is a clinical dataset of $T_1$-weighted magnetic resonance images (MRI) from 430 epileptic patients who underwent resective brain surgery at the National Hospital of Neurology and Neurosurgery (Queen Square, London, United Kingdom) between 1990 and 2018.
The NIfTI files are anonymised and the images have been defaced to further protect the patients' identity.
The dataset comprises 430 postoperative MRI. The corresponding preoperative MRI is present for 269 subjects.
Three human raters segmented the resection cavity on partially overlapping subsets of EPISURG:
If you use this dataset for your research please cite the following publications:
Pérez-García F., Rodionov R., Alim-Marvasti A., Sparks R., Duncan J.S., Ourselin S. (2020) Simulation of Brain Resection for Cavity Segmentation Using Self-supervised and Semi-supervised Learning. In: Martel A.L. et al. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2020. Lecture Notes in Computer Science, vol 12263. Springer, Cham. https://doi.org/10.1007/978-3-030-59716-0_12
Pérez-García F., Rodionov R., Alim-Marvasti A., Sparks R., Duncan J.S., Ourselin S. EPISURG: MRI dataset for quantitative analysis of resective neurosurgery for refractory epilepsy. University College London (2020). DOI 10.5522/04/9996158.v1
The 3D Slicer extension EPISURG may be used to visualise the dataset.
The EPISURG data are distributed to the greater scientific community under the following terms:
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