Brats MICCAI Brain tumor dataset
BraTS has always been focusing on the evaluation of state-of-the-art methods for the segmentation of brain tumors in multimodal magnetic resonance imaging (MRI) scans. BraTS 2019 utilizes multi-institutional pre-operative MRI scans and focuses on the segmentation of intrinsically heterogeneous (in appearance, shape, and histology) brain tumors, namely gliomas. Furthemore, to pinpoint the clinical relevance of this segmentation task, BraTS’19 also focuses on the prediction of patient overall survival, via integrative analyses of radiomic features and machine learning algorithms. Finally, BraTS'19 intends to experimentally evaluate the uncertainty in tumor segmentations.
Here, Instructions are to develop code to read the files. Where path of dataset should be set. From that path one counter read the files in particular sequence one by one. From the path there will form four sub files in which dataset volumes are arrange in to T1, T2, Flair and T1Ce sequences. Every volume have 155 slices. Slices are infact MRI image. 155 slices are for one volume. And 210 Volumes are High grades Glioma dataset. Wereas 75 Volumes are in another type of glioma. Hence total is 285. Therefore for this huge dataset, Matlab is best plateform for programming but system memory should be more than 16 GB. Processor should be 3.0 Ghz. Hard disk should more 500 GB.