Computed Tomography (CT) of the Brain - Object Detection dataset

The dataset consists of CT brain scans with cancer, tumor, and aneurysm. Each scan represents a detailed image of a patient's brain taken using CT (Computed Tomography). The data are presented in 2 different formats: .jpg and .dcm.

💴 For Commercial Usage: Full version of the dataset includes much more brain scans of people with different conditions, leave a request on TrainingData to buy the dataset

The dataset of CT brain scans is valuable for research in neurology, radiology, and oncology. It allows the development and evaluation of computer-based algorithms, machine learning models, and deep learning techniques for automated detection, diagnosis, and classification of these conditions.

Types of brain diseases in the dataset:

• cancer
• tumor
• aneurysm

OTHER MEDICAL DATASETS:

• Computed Tomography (CT) of the Chest
• Computed Tomography (CT) of the Spine - Scoliosis
• Knee X-rays - 4 Stages of Osteoarthritis
• Chest X-ray - 17 Diseases 🏥
• Spine X-ray - Scoliosis and 6 other diseases

💴 Buy the Dataset: This is just an example of the data. Leave a request on https://trainingdata.pro/datasets to discuss your requirements, learn about the price and buy the dataset

Content

The folder "files" includes 3 folders:

• corresponding to name of the brain disease and including ct scans of people with this disease (cancer, tumor or aneurysm)
• including brain scans in 2 different formats: .jpg and .dcm.

File with the extension .csv includes the following information for each media file:

• dcm: link to access the .dcm file,
• jpg: link to access the .jpg file,
• type: name of the brain disease on the ct

Medical data might be collected in accordance with your requirements.

TrainingData provides high-quality data annotation tailored to your needs

keywords: 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