--- license: cc-by-nc-nd-4.0 task_categories: - image-classification - image-to-image - image-segmentation - object-detection language: - en tags: - medical - biology - code --- # Spine MRI Dataset, Anomaly Detection & Segmentation The dataset consists of .dcm files containing **MRI scans of the spine** of the person with several dystrophic changes, such as osteochondrosis, spondyloarthrosis, hemangioma, physiological lordosis smoothed, osteophytes and aggravated defects. The images are **labeled** by the doctors and accompanied by **report** in PDF-format. The dataset includes 9 studies, made from the different angles which provide a comprehensive understanding of a several dystrophic changes and useful in training spine anomaly classification algorithms. Each scan includes detailed imaging of the spine, including the *vertebrae, discs, nerves, and surrounding tissues*. ### MRI study angles in the dataset ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F62acce9c1d60720bdd396e036718f406%2FFrame%2084.png?generation=1708543957118470&alt=media) # 💴 For Commercial Usage: Full version of the dataset includes 20,000 spine studies of people with different conditions, leave a request on **[TrainingData](https://trainingdata.pro/datasets/spine-mri?utm_source=huggingface&utm_medium=cpc&utm_campaign=spinal-cord-dataset)** to buy the dataset ### Types of diseases and conditions in the full dataset: - Degeneration of discs - Osteophytes - Osteochondrosis - Hemangioma - Disk extrusion - Spondylitis - **AND MANY OTHER CONDITIONS** ![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2Fd2f21b9ac7dc26a3554e4647db47df57%2F3.gif?generation=1708543677763656&alt=media) Researchers and healthcare professionals can use this dataset to study spinal conditions and disorders, such as herniated discs, spinal stenosis, scoliosis, and fractures. The dataset can also be used to develop and evaluate new imaging techniques, computer algorithms for image analysis, and artificial intelligence models for automated diagnosis. # 💴 Buy the Dataset: This is just an example of the data. Leave a request on [https://trainingdata.pro/datasets](https://trainingdata.pro/datasets/spine-mri?utm_source=huggingface&utm_medium=cpc&utm_campaign=spinal-cord-dataset) to discuss your requirements, learn about the price and buy the dataset # Content ### The dataset includes: - **ST000001**: includes subfolders with 9 studies. Each study includes MRI-scans in **.dcm and .jpg formats**, - **DICOMDIR**: includes information about the patient's condition and links to access files, - **Spine_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/spine-mri?utm_source=huggingface&utm_medium=cpc&utm_campaign=spinal-cord-dataset) provides high-quality data annotation tailored to your needs More datasets in TrainingData's Kaggle account: **** TrainingData's GitHub: **https://github.com/Trainingdata-datamarket/TrainingData_All_datasets** *keywords: mri spine scans, spinal imaging, radiology dataset, neuroimaging, medical imaging data, image segmentation, lumbar spine mri, thoracic spine mri, cervical spine mri, spine anatomy, spinal cord mri, orthopedic imaging, radiologist dataset, mri scan analysis, spine mri dataset, machine learning medical imaging, spinal abnormalities, image classification, neural network spine scans, mri data analysis, deep learning medical imaging, mri image processing, spine tumor detection, spine injury diagnosis, mri image segmentation, spine mri classification, artificial intelligence in radiology, spine abnormalities detection, spine pathology analysis, mri feature extraction.*