Cover Image

SAM-Fed: SAM-Guided Federated Semi-Supervised Learning for Medical Image Segmentation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Nasirihaghighi, Sahar, Ghamsarian, Negin, Li, Yiping, Breeuwer, Marcel, Sznitman, Raphael, Schoeffmann, Klaus
Format:	Preprint
Published:	2025
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Feedback-Driven Pseudo-Label Reliability Assessment: Redefining Thresholding for Semi-Supervised Semantic Segmentation
by: Ghamsarian, Negin, et al.
Published: (2025)

Dual Invariance Self-training for Reliable Semi-supervised Surgical Phase Recognition
by: Nasirihaghighi, Sahar, et al.
Published: (2025)

GynSurg: A Comprehensive Gynecology Laparoscopic Surgery Dataset
by: Nasirihaghighi, Sahar, et al.
Published: (2025)

WetCat: Enabling Automated Skill Assessment in Wet-Lab Cataract Surgery Videos
by: Ghamsarian, Negin, et al.
Published: (2025)

SemiSAM: Enhancing Semi-Supervised Medical Image Segmentation via SAM-Assisted Consistency Regularization
by: Zhang, Yichi, et al.
Published: (2023)

PG-SAM: Prior-Guided SAM with Medical for Multi-organ Segmentation
by: Zhong, Yiheng, et al.
Published: (2025)

pFedSAM: Personalized Federated Learning of Segment Anything Model for Medical Image Segmentation
by: Wang, Tong, et al.
Published: (2025)

SEG-SAM: Semantic-Guided SAM for Unified Medical Image Segmentation
by: Huang, Shuangping, et al.
Published: (2024)

SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation
by: Zhu, Hongjie, et al.
Published: (2025)

SemiVT-Surge: Semi-Supervised Video Transformer for Surgical Phase Recognition
by: Li, Yiping, et al.
Published: (2025)

PGP-SAM: Prototype-Guided Prompt Learning for Efficient Few-Shot Medical Image Segmentation
by: Yan, Zhonghao, et al.
Published: (2025)

A SAM-guided and Match-based Semi-Supervised Segmentation Framework for Medical Imaging
by: Xu, Guoping, et al.
Published: (2024)

BALR-SAM: Boundary-Aware Low-Rank Adaptation of SAM for Resource-Efficient Medical Image Segmentation
by: Liu, Zelin, et al.
Published: (2025)

SAM-DA: Decoder Adapter for Efficient Medical Domain Adaptation
by: Tejero, Javier Gamazo, et al.
Published: (2025)

SemiSAM+: Rethinking Semi-Supervised Medical Image Segmentation in the Era of Foundation Models
by: Zhang, Yichi, et al.
Published: (2025)

SeqSAM: Autoregressive Multiple Hypothesis Prediction for Medical Image Segmentation using SAM
by: Towle, Benjamin, et al.
Published: (2025)

ProMISe: Promptable Medical Image Segmentation using SAM
by: Wang, Jinfeng, et al.
Published: (2024)

Data-Efficient Learning for Generalizable Surgical Video Understanding
by: Nasirihaghighi, Sahar
Published: (2025)

ProtoSAM: One-Shot Medical Image Segmentation With Foundational Models
by: Ayzenberg, Lev, et al.
Published: (2024)

Challenge Summary U-MedSAM: Uncertainty-aware MedSAM for Medical Image Segmentation
by: Wang, Xin, et al.
Published: (2024)

Efficient Knowledge Distillation of SAM for Medical Image Segmentation
by: Patil, Kunal Dasharath, et al.
Published: (2025)

MIAS-SAM: Medical Image Anomaly Segmentation without thresholding
by: Colussi, Marco, et al.
Published: (2025)

Robust Box Prompt based SAM for Medical Image Segmentation
by: Huang, Yuhao, et al.
Published: (2024)

SSL-MedSAM2: A Semi-supervised Medical Image Segmentation Framework Powered by Few-shot Learning of SAM2
by: Gong, Zhendi, et al.
Published: (2025)

SparseMamba-PCL: Scribble-Supervised Medical Image Segmentation via SAM-Guided Progressive Collaborative Learning
by: Qiu, Luyi, et al.
Published: (2025)

S^4M: Boosting Semi-Supervised Instance Segmentation with SAM
by: Yoon, Heeji, et al.
Published: (2025)

Medical SAM3: A Foundation Model for Universal Prompt-Driven Medical Image Segmentation
by: Jiang, Chongcong, et al.
Published: (2026)

SAM2-SGP: Enhancing SAM2 for Medical Image Segmentation via Support-Set Guided Prompting
by: Xing, Yang, et al.
Published: (2025)

ConformalSAM: Unlocking the Potential of Foundational Segmentation Models in Semi-Supervised Semantic Segmentation with Conformal Prediction
by: Chen, Danhui, et al.
Published: (2025)

SAM Carries the Burden: A Semi-Supervised Approach Refining Pseudo Labels for Medical Segmentation
by: Keuth, Ron, et al.
Published: (2024)

MedSAM3: Delving into Segment Anything with Medical Concepts
by: Liu, Anglin, et al.
Published: (2025)

Is SAM 2 Better than SAM in Medical Image Segmentation?
by: Sengupta, Sourya, et al.
Published: (2024)

SAM as the Guide: Mastering Pseudo-Label Refinement in Semi-Supervised Referring Expression Segmentation
by: Yang, Danni, et al.
Published: (2024)

Medical Image Segmentation with SAM-generated Annotations
by: Häkkinen, Iira, et al.
Published: (2024)

MedSAM-Agent: Empowering Interactive Medical Image Segmentation with Multi-turn Agentic Reinforcement Learning
by: Liu, Shengyuan, et al.
Published: (2026)

ClipSAM: CLIP and SAM Collaboration for Zero-Shot Anomaly Segmentation
by: Li, Shengze, et al.
Published: (2024)

Self-Prompt SAM: Medical Image Segmentation via Automatic Prompt SAM Adaptation
by: Xie, Bin, et al.
Published: (2025)

WeakMedSAM: Weakly-Supervised Medical Image Segmentation via SAM with Sub-Class Exploration and Prompt Affinity Mining
by: Wang, Haoran, et al.
Published: (2025)

FloorSAM: SAM-Guided Floorplan Reconstruction with Semantic-Geometric Fusion
by: Ye, Han, et al.
Published: (2025)

Learnable Prompting SAM-induced Knowledge Distillation for Semi-supervised Medical Image Segmentation
by: Huang, Kaiwen, et al.
Published: (2024)