I-MedSAM: Implicit Medical Image Segmentation with Segment Anything
Fuente:
arXiv
Saved in:
| Main Authors: | Wei, Xiaobao, Cao, Jiajun, Jin, Yizhu, Lu, Ming, Wang, Guangyu, Zhang, Shanghang |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
MedSAM3: Delving into Segment Anything with Medical Concepts
by: Liu, Anglin, et al.
Published: (2025)
by: Liu, Anglin, et al.
Published: (2025)
MedSAM2: Segment Anything in 3D Medical Images and Videos
by: Ma, Jun, et al.
Published: (2025)
by: Ma, Jun, et al.
Published: (2025)
Challenge Summary U-MedSAM: Uncertainty-aware MedSAM for Medical Image Segmentation
by: Wang, Xin, et al.
Published: (2024)
by: Wang, Xin, et al.
Published: (2024)
Efficient MedSAMs: Segment Anything in Medical Images on Laptop
by: Ma, Jun, et al.
Published: (2024)
by: Ma, Jun, et al.
Published: (2024)
MedSAM-U: Uncertainty-Guided Auto Multi-Prompt Adaptation for Reliable MedSAM
by: Zhou, Nan, et al.
Published: (2024)
by: Zhou, Nan, et al.
Published: (2024)
MCP-MedSAM: A Powerful Lightweight Medical Segment Anything Model Trained with a Single GPU in Just One Day
by: Lyu, Donghang, et al.
Published: (2024)
by: Lyu, Donghang, et al.
Published: (2024)
MedSAM-Agent: Empowering Interactive Medical Image Segmentation with Multi-turn Agentic Reinforcement Learning
by: Liu, Shengyuan, et al.
Published: (2026)
by: Liu, Shengyuan, et al.
Published: (2026)
Medical SAM Adapter: Adapting Segment Anything Model for Medical Image Segmentation
by: Wu, Junde, et al.
Published: (2023)
by: Wu, Junde, et al.
Published: (2023)
SSL-MedSAM2: A Semi-supervised Medical Image Segmentation Framework Powered by Few-shot Learning of SAM2
by: Gong, Zhendi, et al.
Published: (2025)
by: Gong, Zhendi, et al.
Published: (2025)
MedCore: Boundary-Preserving Medical Core Pruning for MedSAM
by: Zhang, Cenwei, et al.
Published: (2026)
by: Zhang, Cenwei, et al.
Published: (2026)
NTO3D: Neural Target Object 3D Reconstruction with Segment Anything
by: Wei, Xiaobao, et al.
Published: (2023)
by: Wei, Xiaobao, et al.
Published: (2023)
MedSAM-CA: A CNN-Augmented ViT with Attention-Enhanced Multi-Scale Fusion for Medical Image Segmentation
by: Tian, Peiting, et al.
Published: (2025)
by: Tian, Peiting, et al.
Published: (2025)
SAM3-I: Segment Anything with Instructions
by: Li, Jingjing, et al.
Published: (2025)
by: Li, Jingjing, et al.
Published: (2025)
DeSAM: Decoupled Segment Anything Model for Generalizable Medical Image Segmentation
by: Gao, Yifan, et al.
Published: (2023)
by: Gao, Yifan, et al.
Published: (2023)
Point-supervised Brain Tumor Segmentation with Box-prompted MedSAM
by: Liu, Xiaofeng, et al.
Published: (2024)
by: Liu, Xiaofeng, et al.
Published: (2024)
S-SAM: SVD-based Fine-Tuning of Segment Anything Model for Medical Image Segmentation
by: Paranjape, Jay N., et al.
Published: (2024)
by: Paranjape, Jay N., et al.
Published: (2024)
SAM-Med3D-MoE: Towards a Non-Forgetting Segment Anything Model via Mixture of Experts for 3D Medical Image Segmentation
by: Wang, Guoan, et al.
Published: (2024)
by: Wang, Guoan, et al.
Published: (2024)
pFedSAM: Personalized Federated Learning of Segment Anything Model for Medical Image Segmentation
by: Wang, Tong, et al.
Published: (2025)
by: Wang, Tong, et al.
Published: (2025)
SAIF: A Stability-Aware Inference Framework for Medical Image Segmentation with Segment Anything Model
by: Wu, Ke, et al.
Published: (2026)
by: Wu, Ke, et al.
Published: (2026)
Automating MedSAM by Learning Prompts with Weak Few-Shot Supervision
by: Gaillochet, Mélanie, et al.
Published: (2024)
by: Gaillochet, Mélanie, et al.
Published: (2024)
Medical SAM 2: Segment medical images as video via Segment Anything Model 2
by: Zhu, Jiayuan, et al.
Published: (2024)
by: Zhu, Jiayuan, et al.
Published: (2024)
SAM3-Adapter: Efficient Adaptation of Segment Anything 3 for Camouflage Object Segmentation, Shadow Detection, and Medical Image Segmentation
by: Chen, Tianrun, et al.
Published: (2025)
by: Chen, Tianrun, et al.
Published: (2025)
Swin-LiteMedSAM: A Lightweight Box-Based Segment Anything Model for Large-Scale Medical Image Datasets
by: Gao, Ruochen, et al.
Published: (2024)
by: Gao, Ruochen, et al.
Published: (2024)
SAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation
by: Xiong, Xinyu, et al.
Published: (2024)
by: Xiong, Xinyu, et al.
Published: (2024)
DC-SAM: In-Context Segment Anything in Images and Videos via Dual Consistency
by: Qi, Mengshi, et al.
Published: (2025)
by: Qi, Mengshi, et al.
Published: (2025)
SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images
by: Wang, Haoyu, et al.
Published: (2023)
by: Wang, Haoyu, et al.
Published: (2023)
Optimization of MedSAM model based on bounding box adaptive perturbation algorithm
by: Li, Boyi, et al.
Published: (2025)
by: Li, Boyi, et al.
Published: (2025)
SAM-I2I: Unleash the Power of Segment Anything Model for Medical Image Translation
by: Huo, Jiayu, et al.
Published: (2024)
by: Huo, Jiayu, et al.
Published: (2024)
AffordanceSAM: Segment Anything Once More in Affordance Grounding
by: Jiang, Dengyang, et al.
Published: (2025)
by: Jiang, Dengyang, et al.
Published: (2025)
RemoteSAM: Towards Segment Anything for Earth Observation
by: Yao, Liang, et al.
Published: (2025)
by: Yao, Liang, et al.
Published: (2025)
MedLSAM: Localize and Segment Anything Model for 3D CT Images
by: Lei, Wenhui, et al.
Published: (2023)
by: Lei, Wenhui, et al.
Published: (2023)
SAM2-Adapter: Evaluating & Adapting Segment Anything 2 in Downstream Tasks: Camouflage, Shadow, Medical Image Segmentation, and More
by: Chen, Tianrun, et al.
Published: (2024)
by: Chen, Tianrun, et al.
Published: (2024)
FusionSAM: Visual Multi-Modal Learning with Segment Anything
by: Li, Daixun, et al.
Published: (2024)
by: Li, Daixun, et al.
Published: (2024)
SAM3D: Segment Anything Model in Volumetric Medical Images
by: Bui, Nhat-Tan, et al.
Published: (2023)
by: Bui, Nhat-Tan, et al.
Published: (2023)
Biomedical SAM 2: Segment Anything in Biomedical Images and Videos
by: Yan, Zhiling, et al.
Published: (2024)
by: Yan, Zhiling, et al.
Published: (2024)
SAM Struggles in Concealed Scenes -- Empirical Study on Segment Anything
by: Ji, Ge-Peng, et al.
Published: (2023)
by: Ji, Ge-Peng, et al.
Published: (2023)
FocSAM: Delving Deeply into Focused Objects in Segmenting Anything
by: Huang, You, et al.
Published: (2024)
by: Huang, You, et al.
Published: (2024)
Med-PerSAM: One-Shot Visual Prompt Tuning for Personalized Segment Anything Model in Medical Domain
by: Yoon, Hangyul, et al.
Published: (2024)
by: Yoon, Hangyul, et al.
Published: (2024)
Assessing Foundational Medical 'Segment Anything' (Med-SAM1, Med-SAM2) Deep Learning Models for Left Atrial Segmentation in 3D LGE MRI
by: Mehrnia, Mehri, et al.
Published: (2024)
by: Mehrnia, Mehri, et al.
Published: (2024)
X-SAM: From Segment Anything to Any Segmentation
by: Wang, Hao, et al.
Published: (2025)
by: Wang, Hao, et al.
Published: (2025)
Similar Items
-
MedSAM3: Delving into Segment Anything with Medical Concepts
by: Liu, Anglin, et al.
Published: (2025) -
MedSAM2: Segment Anything in 3D Medical Images and Videos
by: Ma, Jun, et al.
Published: (2025) -
Challenge Summary U-MedSAM: Uncertainty-aware MedSAM for Medical Image Segmentation
by: Wang, Xin, et al.
Published: (2024) -
Efficient MedSAMs: Segment Anything in Medical Images on Laptop
by: Ma, Jun, et al.
Published: (2024) -
MedSAM-U: Uncertainty-Guided Auto Multi-Prompt Adaptation for Reliable MedSAM
by: Zhou, Nan, et al.
Published: (2024)