Feature-interactive Siamese graph encoder-based image analysis to predict STAS from histopathology images in lung cancer
Abstract Spread through air spaces (STAS) is a distinct invasion pattern in lung cancer, crucial for prognosis assessment and guiding surgical decisions. Histopathology is the gold standard for STAS detection, yet traditional methods are subjective, time-consuming, and prone to misdiagnosis, limitin...
Saved in:
| Main Authors: | Liangrui Pan, Qingchun Liang, Wenwu Zeng, Yijun Peng, Zhenyu Zhao, Yiyi Liang, Jiadi Luo, Xiang Wang, Shaoliang Peng |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2024-12-01
|
| Series: | npj Precision Oncology |
| Online Access: | https://doi.org/10.1038/s41698-024-00771-y |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Research hotspots and trends in lung cancer STAS: a bibliometric and visualization analysis
by: Xiuhua Peng, et al.
Published: (2025-01-01) -
Opportunities and challenges in the application of large artificial intelligence models in radiology
by: Liangrui Pan, et al.
Published: (2024-06-01) -
Graph-based analysis of histopathological images for lung cancer classification using GLCM features and enhanced graph
by: Imam Dad, et al.
Published: (2025-05-01) -
Siamese-SAM: Remote Sensing Image Change Detection with Siamese Structure Segment Anything Model
by: Gang Wei, et al.
Published: (2025-03-01) -
Prediction of STAS in lung adenocarcinoma with nodules ≤ 2 cm using machine learning: a multicenter retrospective study
by: Zhan Zhang, et al.
Published: (2025-03-01)