# AutoMorph: Automated Retinal Vascular Morphology Quantification Via a Deep Learning Pipeline

**Type:** Papers  
**Canonical URL:** https://scholariq.org/papers/automorph-automated-retinal-vascular-morphology-quantification-via-a-deep/

## Facts

| Field | Value |
| --- | --- |
| Author Names | Yukun Zhou,Siegfried K. Wagner,Mark A. Chia,An Zhao,Peter Woodward-Court,Moucheng Xu,Robbert Struyven,Daniel C. Alexander,Pearse A. Keane |
| Citations | 139 |
| DOI | 10.1167/tvst.11.7.12 |
| Fields | Engineering,Medicine |
| Open Access | true |
| OA Status | gold |
| OA URL | https://doi.org/10.1167/tvst.11.7.12 |
| OpenAlex ID | https://openalex.org/W4285387118 |
| PMID | 35833885 |
| Type | article |
| Year | 2022 |

## Paper authors

- [Mark A. Chia](https://scholariq.org/researchers/mark-a-chia/)

## Paper primary topic

- [Retinal Imaging and Analysis](https://scholariq.org/topics/retinal-imaging-and-analysis/)

## Paper topics

- [Retinal Imaging and Analysis](https://scholariq.org/topics/retinal-imaging-and-analysis/)
- [Retinal Diseases and Treatments](https://scholariq.org/topics/retinal-diseases-and-treatments/)
- [Optical Coherence Tomography Applications](https://scholariq.org/topics/optical-coherence-tomography-applications/)

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Source: ScholarIQ — public research metadata, principally OpenAlex. See https://scholariq.org/sources/ for provenance and https://scholariq.org/methodology/ for what these figures mean.