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MSHF: A Multi-Source Heterogeneous Fundus (MSHF) Dataset for Image Quality Assessment

Scientific data(2023)SCI 2区

Eye Center

Cited 22|Views15
Abstract
Image quality assessment (IQA) is significant for current techniques of image-based computer-aided diagnosis, and fundus imaging is the chief modality for screening and diagnosing ophthalmic diseases. However, most of the existing IQA datasets are single-center datasets, disregarding the type of imaging device, eye condition, and imaging environment. In this paper, we collected a multi-source heterogeneous fundus (MSHF) database. The MSHF dataset consisted of 1302 high-resolution normal and pathologic images from color fundus photography (CFP), images of healthy volunteers taken with a portable camera, and ultrawide-field (UWF) images of diabetic retinopathy patients. Dataset diversity was visualized with a spatial scatter plot. Image quality was determined by three ophthalmologists according to its illumination, clarity, contrast and overall quality. To the best of our knowledge, this is one of the largest fundus IQA datasets and we believe this work will be beneficial to the construction of a standardized medical image database.
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Eye diseases,Medical imaging,Science,Humanities and Social Sciences,multidisciplinary
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要点】:本文提出了一种多源异构眼底图像质量评估数据集(MSHF),旨在提高眼底图像质量评估的准确性和泛化能力。

方法】:通过收集来自不同中心、不同成像设备、不同眼病状态和不同成像环境的1302张高分辨率正常和病理眼底图像,构建了MSHF数据集。

实验】:数据集的多样性通过空间散点图进行可视化,图像质量由三位眼科医生根据图像的照明、清晰度、对比度和整体质量进行评估,实验使用的数据集名称为MSHF,该数据集的构建有助于标准化医学图像数据库的建设。