We apply nnU-Net to the segmentation task of BraTS 2020 challenge. The unmodified baseline configuration already achieves a respectable result. By incorporating BraTS-specific modifications regarding postprocessing, region-based training, more aggressive data augmentation as well several minor pipeline we are able improve its performance substantially. furthermore re-implement ranking scheme de...

In this paper, different approaches are discussed for medical image segmentation. These are based on thresholding, learning, modeling and automatic fuzzy method. Segmentation techniques, discussed under these approaches are used in different applications. In identification of brain lesions, vessel lumen segmentation and histopathology cancer image segmentation. Further used in tissue segmentati...

Brain tumor is the most deadly disease that affects human life span. To segment the brain tumor part, many segmentation techniques have been emerged in image processing like region based Segmentation, Boundary based segmentation. In this paper, several entropies based methods and several cluster techniques are compared and analyzed for brain tumor segmentation. Several entropies such as rough e...

Recent advances in computing power and additive manufacturing (3D printing) have now made possible the efficient simulation, optimization, and replication of patient-specific procedures and prosthetics for neurosurgery applications. Two very promising applications are in finite element modeling for brain injury simulation and detection and applying additive manufacturing towards brain analogues...