Tools to Create Synthetic Data for Brain Images

Abstract

In the areas of neuroscience, medical imaging, and machine learning, the creation of synthetic data for brain scans has become a key approach. This chapter explores the concept and significance of synthetic data generation for brain images. In tasks like brain picture segmentation, disease detection, and image analysis, machine learning models perform better when using synthetic data as a catalyst for data augmentation. A wide range of methods and resources including MRI simulators, 3D modeling software, deep learning frameworks, and medical imaging software are used to create synthetic brain images. To guarantee the validity and applicability of synthetic data, however, ethical issues, data representativeness, and transparency in the generation process continue to be essential factors. Synthetic brain data are becoming more useful and realistic as technology develops, and this has the potential to completely change the fields of neuroscience and medical imaging.