--- license: cc-by-nc-nd-4.0 task_categories: - image-classification - image-segmentation - image-to-image - object-detection language: - en tags: - medical - biology - code --- # Brain MRI Dataset, Fazekas I Detection & Segmentation The dataset consists of .dcm files containing **MRI scans of the brain** of the person with a **focal gliosis of the brain (Fazekas I)**. The images are **labeled** by the doctors and accompanied by **report** in PDF-format. The dataset includes 6 studies, made from the different angles which provide a comprehensive understanding of a Fazekas I. ### MRI study angles in the dataset ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fa2352c6f001824bf56b835d6719d8fd6%2FFrame%2088.png?generation=1709728481188479&alt=media) # 💴 For Commercial Usage: Full version of the dataset includes 100,000 brain studies of people with different conditions, leave a request on **[TrainingData](https://trainingdata.pro/datasets/brain-mri?utm_source=huggingface&utm_medium=cpc&utm_campaign=fazekas-mri)** to buy the dataset ### Types of diseases and conditions in the full dataset: - Cancer - Multiple sclerosis - Metastatic lesion - Arnold-Chiari malformation - Focal gliosis of the brain - **AND MANY OTHER CONDITIONS** ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fd708c1c5e76d877ce883fa730e78a1ff%2F3.gif?generation=1709728732378049&alt=media) The dataset holds great value for researchers and medical professionals involved in oncology, radiology, and medical imaging. It can be used for a wide range of purposes, including developing and evaluating novel imaging techniques, training and validating machine learning algorithms for automated tumor detection and segmentation, analyzing tumor response to different treatments, and studying the relationship between imaging features and clinical outcomes. # 💴 Buy the Dataset: This is just an example of the data. Leave a request on [https://trainingdata.pro/datasets](https://trainingdata.pro/datasets/brain-mri?utm_source=huggingface&utm_medium=cpc&utm_campaign=fazekas-mri) to discuss your requirements, learn about the price and buy the dataset # Content ### The dataset includes: - **ST000001**: includes subfolders with 6 studies. Each study includes MRI-scans in **.dcm and .jpg formats**, - **DICOMDIR**: includes information about the patient's condition and links to access files, - **Brain_MRI_5.pdf**: includes medical report, provided by the radiologist, - **.csv file**: includes id of the studies and the number of files ### Medical reports include the following data: - Patient's **demographic information**, - **Description** of the case, - Preliminary **diagnosis**, - **Recommendations** on the further actions *All patients consented to the publication of data* # Medical data might be collected in accordance with your requirements. ## [TrainingData](https://trainingdata.pro/datasets/brain-mri?utm_source=huggingface&utm_medium=cpc&utm_campaign=fazekas-mri) provides high-quality data annotation tailored to your needs More datasets in TrainingData's Kaggle account: **https://www.kaggle.com/trainingdatapro/datasets** TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets** *keywords: mri brain scan, brain tumor, brain cancer, oncology, neuroimaging, radiology, brain metastasis, glioblastoma, meningioma, pituitary tumor, medulloblastoma, astrocytoma, oligodendroglioma, ependymoma, neuro-oncology, brain lesion, brain metastasis detection, brain tumor classification, brain tumor segmentation, brain tumor diagnosis, brain tumor prognosis, brain tumor treatment, brain tumor surgery, brain tumor radiation therapy, brain tumor chemotherapy, brain tumor clinical trials, brain tumor research, brain tumor awareness, brain tumor support, brain tumor survivor, neurosurgery, neurologist, neuroradiology, neuro-oncologist, neuroscientist, medical imaging, cancer detection, cancer segmentation, tumor, computed tomography, head, skull, brain scan, eye sockets, sinuses, computer vision, deep learning*