Medical image segmentation

Medical image segmentation aims to detect the boundaries separating different objects from the background inside a two-dimensional or three-dimensional medical image. Medical images are highly variable in nature, and this makes the medical image segmentation difficult. The variations arise because of major modes of variation in human anatomy and because of different modalities of the images being segmented (for example, X-ray, MRI, CT, microscopy, endoscopy, OCT, and so on) used to obtain medical images. Further diagnostic insights can be obtained from segmentation results to help doctors make decisions. Regions with missing edges, the absence of texture contrast, and so on create major issues, and many segmentation approaches have been proposed to fix them. The automatic measurement of organs, cell counting, and simulations based on the extracted boundary...