BraTS Dataset скачать в хорошем качестве

BraTS Dataset

In this video, you will learn about BraTS (Brain Tumor Segmentation), a dataset that plays a crucial role in training AI models for brain tumor detection. You will get an overview of the dataset, its structure, and the different MRI modalities it includes, such as T1, T1Gd, T2, and FLAIR, each contributing valuable insights for tumor segmentation. The video will also explain how segmentation masks guide AI in distinguishing between tumor regions and healthy tissue. Additionally, we will discuss how to access and download the dataset from Kaggle, along with the metadata structure and how it helps in AI training. You will see visualizations of NIfTI files and learn how to work with them programmatically. We will also introduce an example Kaggle notebook that demonstrates a 3D brain tumor segmentation using U-Net, achieving high accuracy in tumor classification. Furthermore, the video will highlight the significance of BraTS in the BraTS Challenge at MICCAI 2024, where researchers push the boundaries of AI in healthcare. Finally, we will discuss the strengths and limitations of BraTS, showing why it is a game-changer in medical Imaging. If you are interested in exploring the dataset further, you can check out the available Kaggle notebooks and related research papers. +Link to the dataset: https://www.kaggle.com/datasets/awsaf49/br... +Link to the Kaggle notebook:https://www.kaggle.com/code/khaledsayedaaa... +Paper Link: https://www.mdpi.com/2075-4418/13/9/1562