Soul: An OCTA dataset based on Human Machine Collaborative Annotation Framework.
Sci Data
; 11(1): 838, 2024 Aug 02.
Article
en En
| MEDLINE
| ID: mdl-39095383
ABSTRACT
Branch retinal vein occlusion (BRVO) is the most prevalent retinal vascular disease that constitutes a threat to vision due to increased venous pressure caused by venous effluent in the space, leading to impaired visual function. Optical Coherence Tomography Angiography (OCTA) is an innovative non-invasive technique that offers high-resolution three-dimensional structures of retinal blood vessels. Most publicly available datasets are collected from single visits with different patients, encompassing various eye diseases for distinct tasks and areas. Moreover, due to the intricate nature of eye structure, professional labeling not only relies on the expertise of doctors but also demands considerable time and effort. Therefore, we have developed a BRVO-focused dataset named Soul (Source of ocular vascular) and propose a human machine collaborative annotation framework (HMCAF) using scrambled retinal blood vessels data. Soul is categorized into 6 subsets based on injection frequency and follow-up duration. The dataset comprises original images, corresponding blood vessel labels, and clinical text information sheets which can be effectively utilized when combined with machine learning.
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1
Base de datos:
MEDLINE
Asunto principal:
Vasos Retinianos
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Oclusión de la Vena Retiniana
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Tomografía de Coherencia Óptica
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Aprendizaje Automático
Idioma:
En
Revista:
Sci Data
Año:
2024
Tipo del documento:
Article