arXiv (OAI Expanded)
open access
Automated Volumetric Segmentation of Microaneurysms on OCT Using Artificial Intelligence
Purpose: To develop and validate a deep learning-based method for the automated identification and volumetric segmentation of microaneurysms (MAs) in diabetic retinopathy (DR) using OCT. Participants: A total of 125 participants were enrolled, including 20 healthy eyes, 27 with mild NPDR, 30 with mo
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
- Research of Automated Maculopathy Screening Based on AI Techniques Using OCT Images#897337
- Multimodal Machine Learning for Auxiliary Diagnosis of Eye Diseases#1100618
- Validation of the Utility of Strabismus Intelligent Diagnostic System#966130
- Artificial Intelligence-based Techniques to Characterize KIdney Microstructure on Histological ImagEs#836277
- MedShapeNet - a large-scale dataset of 3D medical shapes for computer vision.#342522
Record · ID 1071292
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