<?xml version='1.0' encoding='utf-8'?>
<?xml-stylesheet type="text/xsl" href="/v2/static/oai2.xsl"?>
<OAI-PMH xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/ http://www.openarchives.org/OAI/2.0/OAI-PMH.xsd">
  <responseDate>2026-10-14T10:41:13Z</responseDate>
  <request identifier="oai:figshare.com:article/33438577" metadataPrefix="oai_dc" verb="GetRecord">https://api.figshare.com/v2/oai</request>
  <GetRecord>
    <record>
      <header>
        <identifier>oai:figshare.com:article/33438577</identifier>
        <datestamp>2026-09-15T08:23:16Z</datestamp>
        <setSpec>category_24559</setSpec>
        <setSpec>item_type_3</setSpec>
        <setSpec>month_year_09_2026</setSpec>
      </header>
      <metadata>
        <oai_dc:dc xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"  xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
          <dc:title>AV-RetVasc: an ultra-wide-field retinal vascular segmentation dataset from real-world retinal vascular disease scenarios</dc:title>
          <dc:creator>Jing Cao (24710860)</dc:creator>
          <dc:creator>Huimin Li (24710876)</dc:creator>
          <dc:creator>Jiawei Wang (24710878)</dc:creator>
          <dc:creator>Peifang Xu (22024614)</dc:creator>
          <dc:creator>Yingcheng He (14268626)</dc:creator>
          <dc:creator>Jingxin Zhou (11784179)</dc:creator>
          <dc:creator>Zhichu Chen (13758913)</dc:creator>
          <dc:creator>Kun You (6584474)</dc:creator>
          <dc:creator>Juan Ye (12484401)</dc:creator>
          <dc:subject>Clinical sciences not elsewhere classified</dc:subject>
          <dc:subject>retinal vascular segmentation, ultra-wide-field fundus, diabetic retinopathy, retinal vein occlusion</dc:subject>
          <dc:description>&lt;p dir="ltr"&gt;Automated retinal vessel segmentation is fundamental for objective characterization of retinal vascular structures and supports quantitative vascular analysis and artificial intelligence (AI)-based retinal disease assessment. However, existing retinal vessel segmentation datasets are mainly derived from conventional color fundus photographs of healthy populations or eyes without prominent vascular abnormalities, limiting their applicability to real-world pathological conditions. Ultra-wide-field (UWF) imaging provides a broader retinal view of approximately 200 degrees and enables comprehensive visualization of peripheral vascular abnormalities, but pathological UWF vessel segmentation remains challenging due to complex vascular morphology, vessel scale variation, image distortion, and interference from retinal lesions. Here, we present AV-RetVasc, an ultra-wide-field retinal vessel segmentation dataset derived from patients with retinal vascular diseases. The dataset includes 100 UWF fundus images and clinical information from patients with diabetic retinopathy, central retinal vein occlusion, and branch retinal vein occlusion. Each image provides pixel-level vessel segmentation annotations and arteriovenous (A/V) classification labels. AV-RetVasc offers a valuable resource for developing robust AI models for retinal vascular analysis and automated assessment of retinal vascular diseases.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-15T08:23:16Z</dc:date>
          <dc:type>Dataset</dc:type>
          <dc:type>Dataset</dc:type>
          <dc:identifier>10.6084/m9.figshare.33438577.v2</dc:identifier>
          <dc:relation>https://figshare.com/articles/dataset/AV-RetVasc_an_ultra-wide-field_retinal_vascular_segmentation_dataset_from_real-world_retinal_vascular_disease_scenarios/33438577</dc:relation>
          <dc:rights>CC BY 4.0</dc:rights>
        </oai_dc:dc>
      </metadata>
    </record>
  </GetRecord>
</OAI-PMH>
