@inproceedings{b39cc619d07e4747a42f78a93bd47951,
title = "Automated 3D Segmentation of the Lung Airway Tree Using Gain-Based Region Growing Approach",
abstract = "In diagnosing lung diseases, it is highly desirable to be able to segment the lung into physiological structures, such as the intra-thoracic airway tree and the pulmonary structure. Providing an in-vivo and non-invasive tool for 3D reconstruction of anatomical tree structures such as the bronchial tree from 2D and 3D data acquisitions is a challenging issue for computer vision in medical imaging. Due to the complexity of the tracheobronchial tree, the segmentation task is non trivial. This paper describes a 3D adaptive region growing algorithm incorporating gain calculation for segmenting the primary airway tree using a stack of 2D CT slices. The algorithm uses an entropy-based measure known as information gain as a heuristic for selecting the voxels that are most likely to represent the airway regions.",
author = "Harbir Singh and Michael Crawford and John Curtain and Reyer Zwiggelaar",
year = "2004",
month = sep,
day = "20",
doi = "10.1007/978-3-540-30136-3\_118",
language = "English",
isbn = "978-3-540-22977-3",
volume = "3217",
series = "Lecture Notes in Computer Science",
publisher = "Springer Nature",
pages = "975--982",
booktitle = "Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2004",
address = "Switzerland",
edition = "1 PART 2",
note = "7th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2004 ; Conference date: 26-09-2004 Through 29-09-2004",
}