Open Access3D segmentation of lungs with juxta-pleural tumor using the improved active shape model approach
Author(s) -
Shanhui Sun,
Hongliang Ren,
Donghai Tian,
Wei Wu
Publication year - 2021
Publication title -
technology and health care
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.281
H-Index - 44
eISSN - 1878-7401
pISSN - 0928-7329
DOI - 10.3233/thc-218037
Subject(s) - segmentation , computer science , outlier , pattern recognition (psychology) , artificial intelligence , noise (video) , principal component analysis , robust principal component analysis , sample (material) , image (mathematics) , chemistry , chromatography
At present, there are many methods for pathological lung segmentation. However, there are still two unresolved problems. (1) The search steps in traditional ASM is a least square optimization method, which is sensitive to outlier marker points, and it makes the profile update to the transition area in the middle of normal lung tissue and tumor rather than a true lung contour. (2) If the noise images exist in the training dataset, the corrected shape model cannot be constructed.