Cover Image

XAttnRes: Cross-Stage Attention Residuals for Medical Image Segmentation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Liu, Xinyu, Xu, Qing, Chen, Zhen
Format:	Preprint
Published:	2026
Subjects:	Computer Vision and Pattern Recognition Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

LV-XAttn: Distributed Cross-Attention for Long Visual Inputs in Multimodal Large Language Models
by: Chang, Tzu-Tao, et al.
Published: (2025)

Boundless Across Domains: A New Paradigm of Adaptive Feature and Cross-Attention for Domain Generalization in Medical Image Segmentation
by: Xu, Yuheng, et al.
Published: (2024)

DAUNet: A Lightweight UNet Variant with Deformable Convolutions and Parameter-Free Attention for Medical Image Segmentation
by: Munir, Adnan, et al.
Published: (2025)

Attention-Mamba: A Mamba-Enhanced Multi-Scale Parallel Inference Network for Medical Image Segmentation
by: Zhang, Yanhua, et al.
Published: (2024)

A Foundation Model for General Moving Object Segmentation in Medical Images
by: Yan, Zhongnuo, et al.
Published: (2023)

Zero-Residual Concept Erasure via Progressive Alignment in Text-to-Image Model
by: Chen, Hongxu, et al.
Published: (2025)

SimSAM: Zero-shot Medical Image Segmentation via Simulated Interaction
by: Towle, Benjamin, et al.
Published: (2024)

Model Checking in Medical Imaging for Tumor Detection and Segmentation
by: Elfatimi, Elhoucine, et al.
Published: (2025)

SeqSAM: Autoregressive Multiple Hypothesis Prediction for Medical Image Segmentation using SAM
by: Towle, Benjamin, 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)

SegWithU: Uncertainty as Perturbation Energy for Single-Forward-Pass Risk-Aware Medical Image Segmentation
by: Fu, Tianhao, et al.
Published: (2026)

Adaptive Interactive Segmentation for Multimodal Medical Imaging via Selection Engine
by: Li, Zhi, et al.
Published: (2024)

AutoMiSeg: Automatic Medical Image Segmentation via Test-Time Adaptation of Foundation Models
by: Li, Xingjian, et al.
Published: (2025)

Multi-Layer Feature Fusion with Cross-Channel Attention-Based U-Net for Kidney Tumor Segmentation
by: Neha, Fnu, et al.
Published: (2024)

MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal MRI Segmentation
by: Yahathugoda, Yovin, et al.
Published: (2025)

CLoPA: Continual Low Parameter Adaptation of Interactive Segmentation for Medical Image Annotation
by: Esmaeili, Parhom, et al.
Published: (2026)

Progressive Growing of Patch Size: Curriculum Learning for Accelerated and Improved Medical Image Segmentation
by: Fischer, Stefan M., et al.
Published: (2025)

MAIS: Memory-Attention for Interactive Segmentation
by: Orbes-Arteaga, Mauricio, et al.
Published: (2025)

Residual-SwinCA-Net: A Channel-Aware Integrated Residual CNN-Swin Transformer for Malignant Lesion Segmentation in BUSI
by: Naz, Saeeda, et al.
Published: (2025)

GLoG-CSUnet: Enhancing Vision Transformers with Adaptable Radiomic Features for Medical Image Segmentation
by: Eghbali, Niloufar, et al.
Published: (2025)

Harmonizing Generalization and Specialization: Uncertainty-Informed Collaborative Learning for Semi-supervised Medical Image Segmentation
by: Lu, Wenjing, et al.
Published: (2025)

ScribFormer: Transformer Makes CNN Work Better for Scribble-based Medical Image Segmentation
by: Li, Zihan, et al.
Published: (2024)

Adapting Segment Anything Model to Melanoma Segmentation in Microscopy Slide Images
by: Liu, Qingyuan, et al.
Published: (2024)

Automatic Aorta Segmentation with Heavily Augmented, High-Resolution 3-D ResUNet: Contribution to the SEG.A Challenge
by: Wodzinski, Marek, et al.
Published: (2023)

Two Stage Segmentation of Cervical Tumors using PocketNet
by: Twam, Awj, et al.
Published: (2024)

Cross-model Mutual Learning for Exemplar-based Medical Image Segmentation
by: En, Qing, et al.
Published: (2024)

Efficient Image Generation with Variadic Attention Heads
by: Walton, Steven, et al.
Published: (2022)

Semi-Supervised 3D Medical Segmentation from 2D Natural Images Pretrained Model
by: Yeung, Pak-Hei, et al.
Published: (2025)

Anytime, Anywhere, Anyone: Investigating the Feasibility of Segment Anything Model for Crowd-Sourcing Medical Image Annotations
by: Kulkarni, Pranav, et al.
Published: (2024)

Towards Ground-truth-free Evaluation of Any Segmentation in Medical Images
by: Senbi, Ahjol, et al.
Published: (2024)

Multi-modal Vision Pre-training for Medical Image Analysis
by: Rui, Shaohao, et al.
Published: (2024)

Learning Visual Feature-Based World Models via Residual Latent Action
by: Zhang, Xinyu, et al.
Published: (2026)

SegGen: Supercharging Segmentation Models with Text2Mask and Mask2Img Synthesis
by: Ye, Hanrong, et al.
Published: (2023)

Not All Attention Heads Are What You Need: Refining CLIP's Image Representation with Attention Ablation
by: Lin, Feng, et al.
Published: (2025)

Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation
by: Tong, Jintao, et al.
Published: (2025)

Exploring Transfer Learning in Medical Image Segmentation using Vision-Language Models
by: Poudel, Kanchan, et al.
Published: (2023)

Hidden in the Noise: Two-Stage Robust Watermarking for Images
by: Arabi, Kasra, et al.
Published: (2024)

MAPSeg: Unified Unsupervised Domain Adaptation for Heterogeneous Medical Image Segmentation Based on 3D Masked Autoencoding and Pseudo-Labeling
by: Zhang, Xuzhe, et al.
Published: (2023)

CLoE: Expert Consistency Learning for Missing Modality Segmentation
by: Tong, Xinyu, et al.
Published: (2026)