@inbook {1030, title = {Method for Automatically Segmenting the Spinal Cord and Canal from 3D CT Images}, booktitle = {Joint Hungarian-Austrian conference on image processing and pattern recognition. 5th conference of the Hungarian Association for Image Processing and Pattern Recognition (K{\'E}PAF), 29th workshop of the Austrian Association for Pattern Reco}, year = {2005}, month = {2005///}, pages = {311 - 318}, publisher = {OCG}, organization = {OCG}, address = {Vienna}, abstract = {We present two approaches for automatically segmenting thespinal cord/canal from native CT images of the thorax region containing the spine. Different strategies are included to handle images where only part of the spinal column is visible. The algorithms require one seed point given on a slice located in the middle region of the spine, and the rest is automatic. The spatial extent of the spinal cord/canal is determined automatically using anatomical information for segmenting the spinal canal while active contours are applied if the spinal cord is to be segmented. Both methods work in 2D and use propagated information from neighboring slices. They are also very rapid in execution, that means an efficient, user-friendly workflow. The methods were evaluated by radiologists and were found to be useful and met the accuracy and repeatability requirements for the particular task. }, author = {L{\'a}szl{\'o} G{\'a}bor Ny{\'u}l and Judit Kany{\'o} and E{\"o}rs M{\'a}t{\'e} and G{\'e}za Makay and Emese Balogh and M{\'a}rta Fidrich and Attila Kuba}, editor = {Dmitrij Chetverikov and L{\'a}szl{\'o} Cz{\'u}ni and Markus Vincze} }