Vision transformers for segmenting organs and tissues in CT scans of arbitrary imaging ranges
Automatic segmentation of organs and tissues in computed tomography (CT) images can aid clinicians in anatomical contextualization for planning surgery or dosimetry. CT scans can cover varying axial ranges of the body. This thesis aims to develop a neural network based on vision transformers for segmenting organs and tissues in CT images of arbitrary axial ranges. Two models are presented, one bas
