Intrathoracic airway trees: segmentation and airway morphology analysis from low-dose CT scans
By J. Tschirren, E. Hoffman, G. McLennan, Milan Sonka. IEEE Transactions on Medical Imaging, 2005
329 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Pulmonary and Respiratory Medicine, Radiology, Nuclear Medicine and Imaging
View Paper: https://www.semanticscholar.org/paper/cd4178a915c871a75de501bd1549300d9bb45ff2
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Xavier Bresson
- Tom Goldstein
- Stanley J. Osher
- G. Funka-Lea
- Kensaku Mori
- Mathias Prokop
- Isabelle Bloch
- Jan Sijbers
In Pulmonary and Respiratory Medicine
In Radiology, Nuclear Medicine and Imaging
- B. van Ginneken
- Mathias Prokop
- Jamshid Dehmeshki
- Xujiong Ye
- Jan Sijbers
- Stanley J. Osher
- Tom Goldstein
- Xavier Bresson
Citations in the corpus
- Segmentation of Pulmonary Nodules in Thoracic CT Scans: A Region Growing Approach (2008, methodology): “The fuzzy connectivity algorithm has been used in various medical applications [20]–[23].”
- Extraction of Airways From CT (EXACT'09) (2012, methodology): “assessed the detection rate of their algorithm by manually assigning anatomical labels to detected branches [11], while Fetita et al.”
- A review of 3D vessel lumen segmentation techniques: Models, features and extraction schemes (2009, methodology): “, 2005), by skeletonization of the local binary mask (Manniesing and Niessen, 2004; Tschirren et al., 2005) (see Section 4.”
- Geometric Applications of the Split Bregman Method: Segmentation and Surface Reconstruction (2010, background): “For other state-of-the-art approaches that do not fall into this framework, see [24, 44, 12].”