Interpretable refinement of medical foundation-model segmentation via visual thinking states and uncertainty gating

Segment Anything

Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A. C., Lo, W.-Y., et al. (2023) · 2023 IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv51070.2023.00371 · Cited by 11,953 · see citing works

nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation

Isensee, F., Jaeger, P. F., Kohl, S. A. A., Petersen, J., & Maier-Hein, K. H. (2021) · Nature Methods · doi:10.1038/s41592-020-01008-z · Cited by 10,477 · see citing works

Swin-Unet: Unet-like pure transformer for medical image segmentation

Cao, H., Wang, Y., Chen, J., Jiang, D., Zhang, X., Tian, Q., & Wang, M. (2023) · Lecture Notes in Computer Science · doi:10.1007/978-3-031-25066-8_9 · Cited by 5,640 · see citing works

SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers

Xie, E., Wang, W., Yu, Z., Anandkumar, A., Alvarez, J. M., & Luo, P. (2021) · arXiv · doi:10.48550/arxiv.2105.15203 · Cited by 5,090 · see citing works

The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions

Tschandl, P., Rosendahl, C., & Kittler, H. (2018) · Scientific Data · doi:10.1038/sdata.2018.161 · Cited by 3,628 · see citing works

Metrics for evaluating 3D medical image segmentation: analysis, selection, and tool

Taha, A. A., & Hanbury, A. (2015) · BMC Medical Imaging · doi:10.1186/s12880-015-0068-x · Cited by 3,022 · see citing works

Segment anything in medical images

Ma, J., He, Y., Li, F., Han, L., You, C., & Wang, B. (2024) · Nature Communications · doi:10.1038/s41467-024-44824-z · Cited by 2,913 · see citing works

Skin lesion analysis toward melanoma detection: A challenge at the 2017 International symposium on biomedical imaging (ISBI), hosted by the international skin imaging collaboration (ISIC)

Codella, N. C. F., Gutman, D., Celebi, M. E., Helba, B., Marchetti, M. A., Dusza, S. W., Kalloo, A., Liopyris, K., Mishra, N., Kittler, H., et al. (2018) · 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) · doi:10.1109/isbi.2018.8363547 · Cited by 2,620 · see citing works

LoRA: Low-Rank Adaptation of Large Language Models

Hu, E. J., Shen, Y., Wallis, P., Allen-Zhu, Z., Li, Y., Wang, S., Wang, L., & Chen, W. (2021) · arXiv · doi:10.48550/arxiv.2106.09685 · Cited by 2,523 · see citing works

Dataset of breast ultrasound images

Al-Dhabyani, W., Gomaa, M., Khaled, H., & Fahmy, A. (2020) · Data in Brief · doi:10.1016/j.dib.2019.104863 · Cited by 2,405 · see citing works

The Medical Segmentation Decathlon

Antonelli, M., Reinke, A., Bakas, S., Farahani, K., Kopp-Schneider, A., Landman, B. A., Litjens, G., Menze, B., Ronneberger, O., Summers, R. M., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-30695-9 · Cited by 1,384 · see citing works

Medical SAM adapter: Adapting segment anything model for medical image segmentation

Wu, J., Wang, Z., Hong, M., Ji, W., Fu, H., Xu, Y., Xu, M., & Jin, Y. (2025) · Medical Image Analysis · doi:10.1016/j.media.2025.103547 · Cited by 909 · see citing works

UNeXt: MLP-Based Rapid Medical Image Segmentation Network

Valanarasu, J. M. J., & Patel, V. M. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-16443-9_3 · Cited by 854 · see citing works

MA-SAM: Modality-agnostic SAM adaptation for 3D medical image segmentation

Chen, C., Miao, J., Wu, D., Zhong, A., Yan, Z., Kim, S., Hu, J. J., Liu, Z., Sun, L., Li, X., et al. (2024) · Medical Image Analysis · doi:10.1016/j.media.2024.103310 · Cited by 246 · see citing works

Anomaly Detection-Inspired Few-Shot Medical Image Segmentation Through Self-Supervision With Supervoxels

Hansen, S., Gautam, S., Jenssen, R., & Kampffmeyer, M. C. (2022) · Medical Image Anal. · doi:10.1016/j.media.2022.102385 · Cited by 185 · see citing works

A review of uncertainty estimation and its application in medical imaging

Zou, K., Chen, Z., Yuan, X., Shen, X., Wang, M., & Fu, H. (2023) · Meta-Radiology · doi:10.1016/j.metrad.2023.100003 · Cited by 173 · see citing works

Multi-Task Learning For Thyroid Nodule Segmentation With Thyroid Region Prior

Gong, H., Chen, G., Wang, R., Xie, X., Mao, M., Yu, Y., Chen, F., & Li, G. (2021) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi48211.2021.9434087 · Cited by 162 · see citing works

Explainable artificial intelligence for medical imaging systems using deep learning: a comprehensive review

Houssein, E. H., Gamal, A. M., Younis, E. M. G., & Mohamed, E. (2025) · Cluster Computing · doi:10.1007/s10586-025-05281-5 · Cited by 144 · see citing works

Unleashing the Potential of SAM for Medical Adaptation via Hierarchical Decoding

Cheng, Z., Wei, Q., Zhu, H., Wang, Y., Qu, L., Shao, W., & Zhou, Y. (2024) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr52733.2024.00337 · Cited by 76 · see citing works

Q-Net: Query-Informed Few-Shot Medical Image Segmentation

Shen, Q., Li, Y., Jin, J., & Liu, B. (2024) · Lecture notes in networks and systems · doi:10.1007/978-3-031-47724-9_40 · Cited by 64 · see citing works

I-MedSAM: Implicit Medical Image Segmentation with Segment Anything

Wei, X., Cao, J., Jin, Y., Lu, M., Wang, G., & Zhang, S. (2024) · Lecture notes in computer science · doi:10.1007/978-3-031-72684-2_6 · Cited by 48 · see citing works

EdgeSAM: Prompt-In-the-Loop Distillation for SAM

Zhou, C., Li, X., Loy, C. C., & Dai, B. (2025) · International Journal of Computer Vision · doi:10.1007/s11263-025-02562-9 · Cited by 44 · see citing works

Enhancing AI reliability: A foundation model with uncertainty estimation for optical coherence tomography-based retinal disease diagnosis

Peng, Y., Lin, A., Wang, M., Lin, T., Liu, L., Wu, J., Zou, K., Shi, T., Feng, L., Liang, Z., et al. (2024) · Cell Reports Medicine · doi:10.1016/j.xcrm.2024.101876 · Cited by 28 · see citing works

Hi- g MISnet: generalized medical image segmentation using DWT based multilayer fusion and dual mode attention into high resolution p GAN

Showrav, T. T., & Hasan, M. K. (2024) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ad3cb3 · Cited by 15 · see citing works

De-LightSAM: Modality-Decoupled Lightweight SAM for Generalizable Medical Segmentation

Xu, Q., Li, J., He, X., et al. (2025) · IEEE Transactions on Circuits and Systems for Video Technology · doi:10.1109/tcsvt.2025.3621309 · Cited by 14 · see citing works

U-MedSAM: Uncertainty-Aware MedSAM for Medical Image Segmentation

Wang, X., Liu, X., Huang, P., Huang, P., Hu, S., & Hongtu Zhu, B. (2025) · Lecture notes in computer science · doi:10.1007/978-3-031-81854-7_14 · Cited by 11 · see citing works

IRU-Net: Brain Tumor Detection in MRI Images Using the End-to-End Inception Residual UNet Model

Aldhaher, E. A. G. (2025) · International journal of advances in soft computing and its applications · doi:10.15849/ijasca.250730.05 · Cited by 2