Robust Initialization of Active Shape Models for Lung Segmentation in CT Scans: A Feature-Based Atlas Approach
Model-based segmentation methods have the advantage of incorporating a priori shape information into the segmentation process but suffer from the drawback that the model must be initialized sufficiently close to the target. We propose a novel approach for initializing an active shape model (ASM) and...
Saved in:
| Main Authors: | Gurman Gill, Matthew Toews, Reinhard R. Beichel |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2014-01-01
|
| Series: | International Journal of Biomedical Imaging |
| Online Access: | http://dx.doi.org/10.1155/2014/479154 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Enhancing lung disease diagnosis with deep-learning-based CT scan image segmentation
by: Rima Tri Wahyuningrum, et al.
Published: (2025-09-01) -
A Two-Stage U-Net Framework for Interactive Segmentation of Lung Nodules in CT Scans
by: Luis Fernandes, et al.
Published: (2025-01-01) -
Advancing deep learning-based segmentation for multiple lung cancer lesions in real-world multicenter CT scans
by: Xavier Rafael-Palou, et al.
Published: (2025-08-01) -
Automated lung tumor detection and diagnosis in CT Scans using texture feature analysis and SVM
by: Tim Adams, et al.
Published: (2018-09-01) -
The Efficacy of PET/CT Scan in CT‐Guided Needle Biopsy of Large Lung Mass
by: Min Kyun Kang
Published: (2025-05-01)