arXiv (All)
open access
U-PEN Mamba: Progressive Expansion with Selective State-Space Modeling for Efficient Retinal Vessel Segmentation
Accurate retinal vessel segmentation is important for computer-aided ophthalmic analysis, yet thin vessels, low contrast, and severe foreground-background imbalance remain challenging for encoder-decoder networks. This paper presents U-PEN Mamba, a U-shaped retinal vessel segmentation architecture t
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Morphology-aware distillation for lightweight retinal vessel segmentation across fundus photography and OCT angiography.#275624
- Clinical application of automated optical coherence tomography angiography for retinal fluid segmentation: a study of real-world data.#199167
- ReG-SAM: Reference Graph-Driven SAM for 2D Foundational Vessel Segmentation#1105718
- Segmentation of the aorta in 4D flow MRI using 4D convolutional kernels and learning from sparse annotations#927728
- Deep Learning for Fluorescein Angiography and Optical Coherence Tomography Macular Thickness Map Image Translation#888423
Record · ID 1050235
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive