@inproceedings{f138017fff1149edb5423cc0b41705d8,
title = "Affinely Registered Multi-object Atlases as Shape Prior for Grid Cut Segmentation of Lumbar Vertebrae from CT Images",
abstract = "In this paper, we present a method for automatic segmentation of lumbar vertebrae from a given lumbar spinal CT image. More specifically, our automatic lumbar vertebrae segmentation method consists of two steps: affine atlas-target registration-based label fusion and bone-sheetness assisted multi-label grid cut which has the inherent advantage of automatic separation of the five lumbar vertebrae from each other. We evaluate our method on 21 clinical lumbar spinal CT images with the associated manual segmentation and conduct a leave-one-out study. Our method achieved an average Dice coefficient of 93.9 ± 1.0\% and an average symmetric surface distance of 0.41 ± 0.08 mm.",
keywords = "CT, Grid cut, Lumbar vertebrae, Multi-object atlas, Segmentation",
author = "Weimin Yu and Wenyong Liu and Liwen Tan and Shaoxiang Zhang and Guoyan Zheng",
note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing AG, part of Springer Nature.; 15th International Conference on Image Analysis and Recognition, ICIAR 2018 ; Conference date: 27-06-2018 Through 29-06-2018",
year = "2018",
doi = "10.1007/978-3-319-93000-8\_11",
language = "英语",
isbn = "9783319929996",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "90--95",
editor = "\{ter Haar Romeny\}, Bart and Fakhri Karray and Aurelio Campilho",
booktitle = "Image Analysis and Recognition - 15th International Conference, ICIAR 2018, Proceedings",
address = "德国",
}