SAM-Swin: SAM-driven dual-swin transformers with adaptive lesion enhancement for Laryngo-Pharyngeal tumor detection
- 8 December 2025
- journal article
- Published by Elsevier in Medical Image Analysis
- Vol. 109, 103906
Abstract
No abstract availableKeywords
Funding Information
- Basic and Applied Basic Research Foundation of Guangdong Province (2022B1515130009)
- Basic and Applied Basic Research Foundation of Guangdong Province (2025A1515011614)
- National Natural Science Foundation of China (62473267,82403695)
This publication has 20 references indexed in Scilit:
- Segment anything model for medical images?Medical Image Analysis, 2023
- Segment anything model for medical image analysis: An experimental studyMedical Image Analysis, 2023
- DLGNet: A dual-branch lesion-aware network with the supervised Gaussian Mixture model for colon lesions classification in colonoscopy imagesMedical Image Analysis, 2023
- RadFormer: Transformers with global–local attention for interpretable and accurate Gallbladder Cancer detectionMedical Image Analysis, 2022
- Diagnosis of ulcerative colitis from endoscopic images based on deep learningBiomedical Signal Processing and Control, 2022
- Boundary-aware context neural network for medical image segmentationMedical Image Analysis, 2022
- ELNet:Automatic classification and segmentation for esophageal lesions using convolutional neural networkMedical Image Analysis, 2021
- Laryngeal preneoplastic lesions and cancer: challenging diagnosis. Qualitative literature review and meta-analysis.Critical Reviews in Oncology/Hematology, 2016
- Functional Outcomes after Chemoradiotherapy of Laryngeal and Pharyngeal CancersCurrent Oncology Reports, 2012
- Current opinion in diagnosis and treatment of laryngeal carcinomaCancer Treatment Reviews, 2006