Transformer-Based Recognition Model for Ground-Glass Nodules from the View of Global 3D Asymmetry Feature Representation
Ground-glass nodules (GGN) are the main manifestation of early lung cancer, and accurate and efficient identification of ground-glass pulmonary nodules is of great significance for the treatment of lung diseases. In response to the problem of traditional machine learning requiring manual feature ext...
Main Authors: | Jun Miao, Maoxuan Zhang, Yiru Chang, Yuanhua Qiao |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2023-12-01
|
Series: | Symmetry |
Subjects: | |
Online Access: | https://www.mdpi.com/2073-8994/15/12/2192 |
Similar Items
-
Machine Learning Model of ResNet50-Ensemble Voting for Malignant–Benign Small Pulmonary Nodule Classification on Computed Tomography Images
by: Weiming Li, et al.
Published: (2023-11-01) -
A Deep Learning Review of ResNet Architecture for Lung Disease Identification in CXR Image
by: Syifa Auliyah Hasanah, et al.
Published: (2023-12-01) -
Computed tomographic features of pulmonary pure ground-glass nodule: a comparison between neoplastic and non-neoplastic nodules
by: Mona Ahmed Fouad Hafez, et al.
Published: (2022-11-01) -
Robust Learning with Implicit Residual Networks
by: Viktor Reshniak, et al.
Published: (2020-12-01) -
A Radiomics Approach Based on Follow-Up CT for Pathological Subtypes Classification of Pulmonary Ground Glass Nodules
by: Chenchen Ma, et al.
Published: (2022-10-01)