Research graph
References from Quantifying the Resolution Ceiling of Prototype-Based Few-Shot Segmentation on Sub-Centimetre Pulmonary Nodules: A Training-Free Geometric Analysis. Local targets link to admitted publications; unresolved targets remain external evidence.
Self-supervised learning for few-shot medical image segmentation
10.1109/tmi.2022.3150682 · 2022 · External reference
Q-Net: Query-informed few-shot medical image segmentation
2024 · External reference
Few-shot medical image segmentation with high-fidelity prototypes
10.1016/j.media.2024.103412 · 2025 · External reference
Few-shot medical image segmentation via a region-enhanced prototypical transformer
2023 · External reference
10.1109/isbi56570.2024.10635439
10.1109/isbi56570.2024.10635439 · External reference
Few-shot learning for medical image segmentation: A review and comparative study
10.1145/3746224 · 2026 · External reference
10.1109/tnnls.2025.3568479
10.1109/tnnls.2025.3568479 · External reference
Unresolved reference
External reference
Understanding metric-related pitfalls in image analysis validation
10.1038/s41592-023-02150-0 · 2024 · External reference
Multilevel support-assisted prototype optimization network for few-shot medical segmentation of lung lesions
10.1038/s41598-025-87829-4 · 2025 · External reference
Unresolved reference
External reference
Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels
10.1016/j.media.2022.102385 · 2022 · External reference
Few-shot segmentation framework for lung nodules via an optimized active contour model
10.1002/mp.16933 · 2024 · External reference
10.1109/cvpr.2011.5995323
10.1109/cvpr.2011.5995323 · External reference
Supervised evaluation of image segmentation and object proposal techniques
10.1109/tpami.2015.2481406 · 2016 · External reference
Unresolved reference
External reference
10.1007/978-3-031-18814-5_11
10.1007/978-3-031-18814-5_11 · External reference
Unresolved reference
External reference
Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem
10.1186/s41747-020-00173-2 · 2020 · External reference
Convolutional neural network architectures for texture classification of pulmonary nodules
2019 · External reference
LNDb challenge on automatic lung cancer patient management
10.1016/j.media.2021.102027 · 2021 · External reference
The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A completed reference database of lung nodules on CT scans
10.1118/1.3528204 · 2011 · External reference
Unresolved reference
External reference
The Cancer Imaging Archive (TCIA): Maintaining and operating a public information repository
10.1007/s10278-013-9622-7 · 2013 · External reference
Lung nodule malignancy classification using only radiologist-quantified image features as inputs to statistical learning algorithms
10.1117/1.jmi.3.4.044504 · 2016 · External reference
Unresolved reference
External reference
Few-shot segmentation framework for lung nodules via an optimized active contour model
10.1002/mp.16933 · ExternalCitation · doi-reference
10.1007/978-3-031-18814-5_11
10.1007/978-3-031-18814-5_11 · ExternalCitation · doi-reference
The Cancer Imaging Archive (TCIA): Maintaining and operating a public information repository
10.1007/s10278-013-9622-7 · ExternalCitation · doi-reference
LNDb challenge on automatic lung cancer patient management
10.1016/j.media.2021.102027 · ExternalCitation · doi-reference
Anomaly detection-inspired few-shot medical image segmentation through self-supervision with supervoxels
10.1016/j.media.2022.102385 · ExternalCitation · doi-reference
Few-shot medical image segmentation with high-fidelity prototypes
10.1016/j.media.2024.103412 · ExternalCitation · doi-reference
Understanding metric-related pitfalls in image analysis validation
10.1038/s41592-023-02150-0 · ExternalCitation · doi-reference
Multilevel support-assisted prototype optimization network for few-shot medical segmentation of lung lesions
10.1038/s41598-025-87829-4 · ExternalCitation · doi-reference
10.1109/cvpr.2011.5995323
10.1109/cvpr.2011.5995323 · ExternalCitation · doi-reference
10.1109/isbi56570.2024.10635439
10.1109/isbi56570.2024.10635439 · ExternalCitation · doi-reference
Self-supervised learning for few-shot medical image segmentation
10.1109/tmi.2022.3150682 · ExternalCitation · doi-reference
10.1109/tnnls.2025.3568479
10.1109/tnnls.2025.3568479 · ExternalCitation · doi-reference
Supervised evaluation of image segmentation and object proposal techniques
10.1109/tpami.2015.2481406 · ExternalCitation · doi-reference
Lung nodule malignancy classification using only radiologist-quantified image features as inputs to statistical learning algorithms
10.1117/1.jmi.3.4.044504 · ExternalCitation · doi-reference
The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A completed reference database of lung nodules on CT scans
10.1118/1.3528204 · ExternalCitation · doi-reference
Few-shot learning for medical image segmentation: A review and comparative study
10.1145/3746224 · ExternalCitation · doi-reference
Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem
10.1186/s41747-020-00173-2 · ExternalCitation · doi-reference
