Cover Image

S3TU-Net: Structured Convolution and Superpixel Transformer for Lung Nodule Segmentation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Wu, Yuke, Liu, Xiang, Shi, Yunyu, Chen, Xinyi, Wang, Zhenglei, Xu, YuQing, Wang, Shuo Hong
Format:	Preprint
Published:	2024
Subjects:	Image and Video Processing Computer Vision and Pattern Recognition Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A Cross Spatio-Temporal Pathology-based Lung Nodule Dataset
by: Jian, Muwei, et al.
Published: (2024)

CATFA-Net: A Trans-Convolutional Approach for Accurate Medical Image Segmentation
by: Mallick, Siddhartha, et al.
Published: (2026)

FusionLungNet: Multi-scale Fusion Convolution with Refinement Network for Lung CT Image Segmentation
by: Rezvani, Sadjad, et al.
Published: (2024)

Attention-ResUNet and EfficientSASM-UNet: UNet based frameworks for Lung and Nodule segmentation
by: Abdullah, Muhammad, et al.
Published: (2025)

Deep Learning-Based Channel Squeeze U-Structure for Lung Nodule Detection and Segmentation
by: Sui, Mingxiu, et al.
Published: (2024)

CSF-Net: Cross-Modal Spatiotemporal Fusion Network for Pulmonary Nodule Malignancy Predicting
by: Shen, Yin, et al.
Published: (2025)

Convolutional Transformer-Based Image Compression
by: Arezki, Bouzid, et al.
Published: (2024)

MBA-Net: SAM-driven Bidirectional Aggregation Network for Ovarian Tumor Segmentation
by: Gao, Yifan, et al.
Published: (2024)

PASC-Net:Plug-and-play Shape Self-learning Convolutions Network with Hierarchical Topology Constraints for Vessel Segmentation
by: Zhang, Xiao, et al.
Published: (2025)

Hierarchical Homogeneity-Based Superpixel Segmentation: Application to Hyperspectral Image Analysis
by: Ayres, Luciano Carvalho, et al.
Published: (2024)

LiNUS: Lightweight Automatic Segmentation of Deep Brain Nuclei for Real-Time DBS Surgery
by: Zhang, Shuo, et al.
Published: (2026)

Cuboid-Net: A Multi-Branch Convolutional Neural Network for Joint Space-Time Video Super Resolution
by: Fu, Congrui, et al.
Published: (2024)

Improved Focus on Hard Samples for Lung Nodule Detection
by: Chen, Yujiang, et al.
Published: (2024)

Matching the Optimal Denoiser in Point Cloud Diffusion with (Improved) Rotational Alignment
by: Daigavane, Ameya, et al.
Published: (2025)

A Lung Nodule Dataset with Histopathology-based Cancer Type Annotation
by: Jian, Muwei, et al.
Published: (2024)

Lung Nodule-SSM: Self-Supervised Lung Nodule Detection and Classification in Thoracic CT Images
by: Noreen, Muniba, et al.
Published: (2025)

TaQ-DiT: Time-aware Quantization for Diffusion Transformers
by: Liu, Xinyan, et al.
Published: (2024)

Advanced Lung Nodule Segmentation and Classification for Early Detection of Lung Cancer using SAM and Transfer Learning
by: V, Asha, et al.
Published: (2024)

TransLK-Net: Entangling Transformer and Large Kernel for Progressive and Collaborative Feature Encoding and Decoding in Medical Image Segmentation
by: Yang, Jin, et al.
Published: (2025)

MiTU-Net: A fine-tuned U-Net with SegFormer backbone for segmenting pubic symphysis-fetal head
by: Wang, Fangyijie, et al.
Published: (2024)

SGDC: Structurally-Guided Dynamic Convolution for Medical Image Segmentation
by: Shi, Bo, et al.
Published: (2026)

Diagnostic Impact of Cine Clips for Thyroid Nodule Assessment on Ultrasound
by: Yang, Jichen, et al.
Published: (2026)

A Composite Alignment-Aware Framework for Myocardial Lesion Segmentation in Multi-sequence CMR Images
by: Gao, Yifan, et al.
Published: (2025)

ELFATT: Efficient Linear Fast Attention for Vision Transformers
by: Wu, Chong, et al.
Published: (2025)

EMeRALDS: Electronic Medical Record Driven Automated Lung Nodule Detection and Classification in Thoracic CT Images
by: Eman, Hafza, et al.
Published: (2025)

MESAHA-Net: Multi-Encoders based Self-Adaptive Hard Attention Network with Maximum Intensity Projections for Lung Nodule Segmentation in CT Scan
by: Usman, Muhammad, et al.
Published: (2023)

Multi-Aperture Fusion of Transformer-Convolutional Network (MFTC-Net) for 3D Medical Image Segmentation and Visualization
by: Shabani, Siyavash, et al.
Published: (2024)

EDU-Net: Retinal Pathological Fluid Segmentation in OCT Images with Multiscale Feature Fusion and Boundary Optimization
by: Lei, Zijun, et al.
Published: (2026)

DBF-Net: A Dual-Branch Network with Feature Fusion for Ultrasound Image Segmentation
by: Xu, Guoping, et al.
Published: (2024)

Dual channel CW nnU-Net for 3D PET-CT Lesion Segmentation in 2024 autoPET III Challenge
by: Wang, Ching-Wei, et al.
Published: (2024)

Evaluating Utility of Memory Efficient Medical Image Generation: A Study on Lung Nodule Segmentation
by: Khadra, Kathrin, et al.
Published: (2024)

An Efficient Approach to Detecting Lung Nodules Using Swin Transformer
by: Shakuri, Saeed, et al.
Published: (2025)

TRUST -- Transformer-Driven U-Net for Sparse Target Recovery
by: An, Di, et al.
Published: (2025)

BreakNet: Discontinuity-Resilient Multi-Scale Transformer Segmentation of Retinal Layers
by: Ganjee, Razieh, et al.
Published: (2024)

SpeHeatal: A Cluster-Enhanced Segmentation Method for Sperm Morphology Analysis
by: Shi, Yi, et al.
Published: (2025)

MambaClinix: Hierarchical Gated Convolution and Mamba-Based U-Net for Enhanced 3D Medical Image Segmentation
by: Bian, Chenyuan, et al.
Published: (2024)

Rel-UNet: Reliable Tumor Segmentation via Uncertainty Quantification in nnU-Net
by: Ziaee, Seyed Sina, et al.
Published: (2025)

Transforming Heart Chamber Imaging: Self-Supervised Learning for Whole Heart Reconstruction and Segmentation
by: Qayyum, Abdul, et al.
Published: (2024)

DDUNet: Dual Dynamic U-Net for Highly-Efficient Cloud Segmentation
by: Li, Yijie, et al.
Published: (2025)

Superpixel-Based Building Damage Detection from Post-earthquake Imagery Using Deep Neural Networks
by: Wang, Jun
Published: (2021)