Datasets:
File size: 3,902 Bytes
b1156ac 9293f9f c893ea3 9293f9f b1156ac 9293f9f a139c6b 9293f9f a139c6b 9293f9f a139c6b 9293f9f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 |
---
license: cc-by-nc-nd-4.0
task_categories:
- image-to-image
- image-classification
- image-segmentation
- object-detection
language:
- en
tags:
- biology
- medical
---
# Multiple Sclerosis Dataset, Brain MRI Object Detection & Segmentation Dataset
The dataset consists of .dcm files containing **MRI scans of the brain** of the person with a multiple sclerosis. The images are **labeled** by the doctors and accompanied by **report** in PDF-format.
The dataset includes **13 studies**, made from the different angles which provide a comprehensive understanding of a multiple sclerosis as a condition.
### MRI study angles in the dataset
![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F9fe7ab0fb5e7d66b0028561d78258baf%2FFrame%2080.png?generation=1707937444108216&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=multiple-sclerosis)** 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%2Fae5d9eb364be2e6a718b1ed7ebaa8ba1%2Fezgif.com-animated-gif-maker.gif?generation=1707936352780047&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 multiple sclerosis detection and segmentation, analyzing 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=multiple-sclerosis) to discuss your requirements, learn about the price and buy the dataset
# Content
### The dataset includes:
- **ST000001**: includes subfolders with 13 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_2.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=multiple-sclerosis) provides high-quality data annotation tailored to your needs
*keywords: brain mri, multiple sclerosis, neuroimaging, mri scans, lesions, brain atrophy, white matter abnormalities, disease progression, neurodegeneration, inflammation, imaging biomarkers, mri analysis, brain volume loss, gray matter changes, myelin damage, optic neuritis, spinal cord lesions, radiological assessment, aneurysm, cancer detection, cancer segmentation, tumor, computed tomography, head, skull, brain scan, eye sockets, sinuses, medical imaging, radiology dataset, neurology dataset, oncology dataset, image dataset, abnormalities detection, brain anatomy, health, brain formations, imaging procedure, x-rays measurements, machine learning, computer vision, deep learning* |