Aneurysm Segmentation
This work aims to alleviate class imbalance and inter-class interference.
Posts by Collection
portfolio
Cerebral Vasculature Segmentation
Cerebral Vasculature Segmentation on 3DRA and MRA modelity
Brain Tumor Segmentation
Brain Tumor Segmentation with three different methods.
Segmentation with Ambiguous/Partial Label
Short description of portfolio item number 1
publications
FMNet: feature mining networks for brain tumor segmentation
Published in 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI), 2019
Brain Tumor Segmentation
Recommended citation: Fengming Lin, et al. FMNet: feature mining networks for brain tumor segmentation. In 2019 IEEE 31st International Conference on Tools with Artificial Intelligence (ICTAI) (pp. 555-560). IEEE. http://fmlinks.github.io/files/paper_lin2019fmnet.pdf
Path aggregation U-Net model for brain tumor segmentation
Published in Multimedia Tools and Applications, 2020
Brain Tumor Segmentation
Recommended citation: Fengming Lin, et al. Path aggregation U-Net model for brain tumor segmentation[J]. Multimedia Tools and Applications, 2021, 80: 22951-22964. http://fmlinks.github.io/files/paper_lin2021path.pdf
High-throughput 3DRA segmentation of brain vasculature and aneurysms using deep learning
Published in Computer Methods and Programs in Biomedicine, 2023
Class Imbalance, Small Target, Cerebral Vessel and Aneurysm Segmentation
Recommended citation: Fengming Lin, et al. High-throughput 3DRA segmentation of brain vasculature and aneurysms using deep learning. Computer Methods and Programs in Biomedicine, 230, 107355. http://fmlinks.github.io/files/paper_lin2023high.pdf
Adaptive Semi-Supervised Segmentation of Brain Vessels with Ambiguous Labels
Published in MICCAI DALI, 2023
Semi-Supervised Learning
Recommended citation: Fengming Lin, et al. Adaptive Semi-Supervised Segmentation of Brain Vessels with Ambiguous Labels. arXiv preprint arXiv:2308.03613. http://fmlinks.github.io/files/paper_lin2023adaptive.pdf
Unsupervised Domain Adaptation for Brain Vessel Segmentation through Transwarp Contrastive Learning
Published in ISBI, 2024
Domain Adaptation
Recommended citation: Fengming Lin, et al. Unsupervised Domain Adaptation for Brain Vessel Segmentation through Transwarp Contrastive Learning[C]//2024 IEEE 21th International Symposium on Biomedical Imaging (ISBI). IEEE, 2024. http://fmlinks.github.io/files/paper_lin2023unsupervised.pdf
GS-EMA: Integrating Gradient Surgery Exponential Moving Average with Boundary-Aware Contrastive Learning for Enhanced Domain Generalization in Aneurysm Segmentation
Published in ISBI, 2024
Domain Generalization, Gradient Surgery, Contrastive Learning
Recommended citation: Fengming Lin, et al. GS-EMA: Integrating Gradient Surgery Exponential Moving Average with Boundary-Aware Contrastive Learning for Enhanced Domain Generalization in Aneurysm Segmentation[C]//2024 IEEE 21th International Symposium on Biomedical Imaging (ISBI). IEEE, 2024. http://fmlinks.github.io/files/paper_lin2023gsema.pdf
talks
Talk 1 on Relevant Topic in Your Field
Published:
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Conference Proceeding talk 3 on Relevant Topic in Your Field
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teaching
Teaching experience 1
Undergraduate course, University 1, Department, 2014
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Teaching experience 2
Workshop, University 1, Department, 2015
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