:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhuang, Tonghao, Hu, Shanglong, Luo, Yongsheng, Zhang, Zhiqi, Li, Yu
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence
Online Access:	https://arxiv.org/abs/2605.19799
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Challenging DINOv3 Foundation Model under Low Inter-Class Variability: A Case Study on Fetal Brain Ultrasound
by: Conti, Edoardo, et al.
Published: (2025)

Dual Agreement Consistency Learning with Foundation Models for Semi-Supervised Fetal Heart Ultrasound Segmentation and Diagnosis
by: Wang, Fangyijie, et al.
Published: (2026)

SemiSAM+: Rethinking Semi-Supervised Medical Image Segmentation in the Era of Foundation Models
by: Zhang, Yichi, 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)

MedCore: Boundary-Preserving Medical Core Pruning for MedSAM
by: Zhang, Cenwei, et al.
Published: (2026)

Leveraging Information Divergence for Robust Semi-Supervised Fetal Ultrasound Image Segmentation
by: Wang, Fangyijie, et al.
Published: (2025)

Leveraging Self-Supervised Learning for Fetal Cardiac Planes Classification using Ultrasound Scan Videos
by: Benjamin, Joseph Geo, et al.
Published: (2024)

MedSAM-U: Uncertainty-Guided Auto Multi-Prompt Adaptation for Reliable MedSAM
by: Zhou, Nan, et al.
Published: (2024)

MedDINOv3: How to adapt vision foundation models for medical image segmentation?
by: Li, Yuheng, et al.
Published: (2025)

Boundary-Refined Prototype Generation: A General End-to-End Paradigm for Semi-Supervised Semantic Segmentation
by: Dong, Junhao, et al.
Published: (2023)

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

FetalCLIP: A Visual-Language Foundation Model for Fetal Ultrasound Image Analysis
by: Maani, Fadillah, et al.
Published: (2025)

From SAM to DINOv2: Towards Distilling Foundation Models to Lightweight Baselines for Generalized Polyp Segmentation
by: Agnihotri, Shivanshu, et al.
Published: (2025)

HDC: Hierarchical Distillation for Multi-level Noisy Consistency in Semi-Supervised Fetal Ultrasound Segmentation
by: Le, Tran Quoc Khanh, 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)

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)

ST-SAM: SAM-Driven Self-Training Framework for Semi-Supervised Camouflaged Object Detection
by: Hu, Xihang, et al.
Published: (2025)

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

NeuroSeg Meets DINOv3: Transferring 2D Self-Supervised Visual Priors to 3D Neuron Segmentation via DINOv3 Initialization
by: Cheng, Yik San, et al.
Published: (2026)

Synergistic Multiscale Detail Refinement via Intrinsic Supervision for Underwater Image Enhancement
by: Zhang, Dehuan, et al.
Published: (2023)

FetalAgents: A Multi-Agent System for Fetal Ultrasound Image and Video Analysis
by: Hu, Xiaotian, et al.
Published: (2026)

Semantic Segmentation Refiner for Ultrasound Applications with Zero-Shot Foundation Models
by: Indelman, Hedda Cohen, et al.
Published: (2024)

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

Standardized 2D Ultrasound Sequences for Fetal Cardiac Screening: A Platform for AI Integration
by: Agnieszka Nocun, et al.
Published: (2026)

Epistemic-aware Vision-Language Foundation Model for Fetal Ultrasound Interpretation
by: He, Xiao, et al.
Published: (2025)

Med-DualLoRA: Local Adaptation of Foundation Models for 3D Cardiac MRI
by: Perramon-Llussà, Joan, et al.
Published: (2026)

Automating MedSAM by Learning Prompts with Weak Few-Shot Supervision
by: Gaillochet, Mélanie, et al.
Published: (2024)

Context-Aware Weakly Supervised Image Manipulation Localization with SAM Refinement
by: Wang, Xinghao, et al.
Published: (2025)

Entropy-Guided Agreement-Diversity: A Semi-Supervised Active Learning Framework for Fetal Head Segmentation in Ultrasound
by: Wang, Fangyijie, et al.
Published: (2026)

Benchmarking Ultrasound Foundation Models for Fetal Plane Classification
by: Barrientos, Leya, et al.
Published: (2026)

Zero-Shot Pseudo Labels Generation Using SAM and CLIP for Semi-Supervised Semantic Segmentation
by: Saito, Nagito, et al.
Published: (2025)

SAM2-3dMed: Empowering SAM2 for 3D Medical Image Segmentation
by: Yang, Yeqing, et al.
Published: (2025)

Synergistic Ultrasound‐Photo Enhancement of Ferroelectric Catalysis via Molecular Multiferroics
by: Lin‐Yu Zhao, et al.
Published: (2025)

SAM-guided Pseudo Label Enhancement for Multi-modal 3D Semantic Segmentation
by: Yang, Mingyu, et al.
Published: (2025)

TransMedSeg: A Transferable Semantic Framework for Semi-Supervised Medical Image Segmentation
by: Wang, Mengzhu, et al.
Published: (2025)

DINOv3
by: Siméoni, Oriane, et al.
Published: (2025)

SIE3D: Single-Image Expressive 3D Avatar Generation via Semantic Embedding and Perceptual Expression Loss
by: Huang, Zhiqi, et al.
Published: (2025)

Accurate and Efficient Fetal Birth Weight Estimation from 3D Ultrasound
by: Wang, Jian, et al.
Published: (2025)

SAM-Fed: SAM-Guided Federated Semi-Supervised Learning for Medical Image Segmentation
by: Nasirihaghighi, Sahar, et al.
Published: (2025)

DSU-Net:An Improved U-Net Model Based on DINOv2 and SAM2 with Multi-scale Cross-model Feature Enhancement
by: Xu, Yimin, et al.
Published: (2025)