Papers Retinal Vessel Segmentation
“Retinal Vessel Segmentation” 태그가 달린 논문 165편 · 필터 해제
From Convolution to Transformer: A Comparative Study of U-Net Variants for Brain Tumor and Retinal Vessel Segmentation
Medical image segmentation plays an important role in computer aided diagnosis, treatment planning, and disease monitoring. U-Net has been widely used for biomedical image segmentation because of its encoder decoder stru…
Retinal Vessel SegmentationMedical Image SegmentationBrain Tumor SegmentationLightVesselNet: An Ultra-Lightweight Sub-100K Parameter Network for Retinal Blood Vessel Segmentation
Retinal blood vessel segmentation plays a vital role in the early detection of diabetic retinopathy and glaucoma. While recent deep learning models have achieved great segmentation accuracy, they typically require heavy …
Retinal Vessel SegmentationGaze into the Details: Locality-Sensitive Enhancement for OCTA Retinal Vessel Segmentation
Existing deep learning frameworks for Optical Coherence Tomography Angiography (OCTA) vessel segmentation are largely derived from the U-Net architecture, which serves as the foundation for most current designs. However,…
Retinal Vessel SegmentationELEMENT: Multi-Modal Retinal Vessel Segmentation Based on a Coupled Region Growing and Machine Learning Approach
Vascular structures in the retina contain important information for the detection and analysis of ocular diseases, including age-related macular degeneration, diabetic retinopathy and glaucoma. Commonly used modalities i…
Retinal Vessel SegmentationPolygon-mamba: Retinal vessel segmentation using polygon scanning mamba and space-frequency collaborative attention
Retinal vessel segmentation is crucial for diagnosis and assessment of ocular diseases. Notably, segmentation of small retinal vessels has been consistently recognized as a challenging and complex task. To tackle this ch…
Retinal Vessel SegmentationRethinking Uncertainty in Segmentation: From Estimation to Decision
In medical image segmentation, uncertainty estimates are often reported but rarely used to guide decisions. We study the missing step: how uncertainty maps are converted into actionable policies such as accepting, flaggi…
Retinal Vessel SegmentationMedical Image SegmentationEffect of Input Resolution on Retinal Vessel Segmentation Performance: An Empirical Study Across Five Datasets
Most deep learning pipelines for retinal vessel segmentation resize fundus images to satisfy GPU memory constraints and enable uniform batch processing. However, the impact of this resizing on thin vessel detection remai…
Retinal Vessel SegmentationVessel DetectionCross-Domain Vessel Segmentation via Latent Similarity Mining and Iterative Co-Optimization
Retinal vessel segmentation serves as a critical prerequisite for automated diagnosis of retinal pathologies. While recent advances in Convolutional Neural Networks (CNNs) have demonstrated promising performance in this …
Retinal Vessel SegmentationHMS-VesselNet: Hierarchical Multi-Scale Attention Network with Topology-Preserving Loss for Retinal Vessel Segmentation
Retinal vessel segmentation methods based on standard overlap losses tend to miss thin peripheral vessels because these structures occupy very few pixels and have low contrast against the background. We propose HMS-Vesse…
Retinal Vessel SegmentationVFGS-Net: Frequency-Guided State-Space Learning for Topology-Preserving Retinal Vessel Segmentation
Accurate retinal vessel segmentation is a critical prerequisite for quantitative analysis of retinal images and computer-aided diagnosis of vascular diseases such as diabetic retinopathy. However, the elongated morpholog…
Retinal Vessel SegmentationRepresentation LearningTFFM: Topology-Aware Feature Fusion Module via Latent Graph Reasoning for Retinal Vessel Segmentation
Precise segmentation of retinal arteries and veins carries the diagnosis of systemic cardiovascular conditions. However, standard convolutional architectures often yield topologically disjointed segmentations, characteri…
Retinal Vessel SegmentationWaveRNet: Wavelet-Guided Frequency Learning for Multi-Source Domain-Generalized Retinal Vessel Segmentation
Domain-generalized retinal vessel segmentation is critical for automated ophthalmic diagnosis, yet faces significant challenges from domain shift induced by non-uniform illumination and varying contrast, compounded by th…
Retinal Vessel SegmentationTopoLoRA-SAM: Topology-Aware Parameter-Efficient Adaptation of Foundation Segmenters for Thin-Structure and Cross-Domain Binary Semantic Segmentation
Foundation segmentation models such as the Segment Anything Model (SAM) exhibit strong zero-shot generalization through large-scale pretraining, but adapting them to domain-specific semantic segmentation remains challeng…
Retinal Vessel SegmentationZero-shot GeneralizationSemantic SegmentationPolyp SegmentationAdaptive Frequency Domain Alignment Network for Medical image segmentation
High-quality annotated data plays a crucial role in achieving accurate segmentation. However, such data for medical image segmentation are often scarce due to the time-consuming and labor-intensive nature of manual annot…
Retinal Vessel SegmentationMedical Image SegmentationDomain AdaptationRobust Multi-Disease Retinal Classification via Xception-Based Transfer Learning and W-Net Vessel Segmentation
In recent years, the incidence of vision-threatening eye diseases has risen dramatically, necessitating scalable and accurate screening solutions. This paper presents a comprehensive study on deep learning architectures …
Retinal Vessel SegmentationTransfer LearningDB-KAUNet: An Adaptive Dual Branch Kolmogorov-Arnold UNet for Retinal Vessel Segmentation
Accurate segmentation of retinal vessels is crucial for the clinical diagnosis of numerous ophthalmic and systemic diseases. However, traditional Convolutional Neural Network (CNN) methods exhibit inherent limitations, s…
Retinal Vessel SegmentationMM-UNet: Morph Mamba U-shaped Convolutional Networks for Retinal Vessel Segmentation
Accurate detection of retinal vessels plays a critical role in reflecting a wide range of health status indicators in the clinical diagnosis of ocular diseases. Recently, advances in deep learning have led to a surge in …
Retinal Vessel SegmentationArtery-Vein Segmentation from Fundus Images using Deep Learning
Segmenting of clinically important retinal blood vessels into arteries and veins is a prerequisite for retinal vessel analysis. Such analysis can provide potential insights and bio-markers for identifying and diagnosing …
Retinal Vessel SegmentationImage SegmentationBioVessel-Net and RetinaMix: Unsupervised Retinal Vessel Segmentation from OCTA Images
Structural changes in retinal blood vessels are critical biomarkers for the onset and progression of glaucoma and other ocular diseases. However, current vessel segmentation approaches largely rely on supervised learning…
Retinal Vessel SegmentationLFA-Net: A Lightweight Network with LiteFusion Attention for Retinal Vessel Segmentation
Lightweight retinal vessel segmentation is important for the early diagnosis of vision-threatening and systemic diseases, especially in a real-world clinical environment with limited computational resources. Although seg…
Retinal Vessel Segmentation