Datasets:
TrainingDataPro
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README.md
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### MRI study angles in the dataset
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![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F9fe7ab0fb5e7d66b0028561d78258baf%2FFrame%2080.png?generation=1707937444108216&alt=media)
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# 💴 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/
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### Types of diseases and conditions in the full dataset:
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- Cancer
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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.
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# 💴 Buy the Dataset: This is just an example of the data. Leave a request on [https://trainingdata.pro/
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# Content
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# Medical data might be collected in accordance with your requirements.
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## [TrainingData](https://trainingdata.pro/
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*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*
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### MRI study angles in the dataset
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![](https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F12421376%2F9fe7ab0fb5e7d66b0028561d78258baf%2FFrame%2080.png?generation=1707937444108216&alt=media)
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# 💴 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
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### Types of diseases and conditions in the full dataset:
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- Cancer
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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.
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# 💴 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
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# Content
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# Medical data might be collected in accordance with your requirements.
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## [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
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*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*
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