Feasibility of smartphone colorimetry of the face as an anaemia screening tool for infants and young children in Ghana.
Feasibility of smartphone colorimetry of the face as an anaemia screening tool for infants and young children in Ghana.
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DOI：
10.1371/journal.pone.0281736
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发表时间：
2023
期刊：
影响因子：
3.7
通讯作者：
中科院分区：
文献类型：
--
作者：
贫血影响着全球大约四分之一的人口。当贫血发生在儿童时期时，它会增加对传染病的易感性并损害认知发育。本研究使用基于智能手机的比色法开发了一种非侵入性技术，用于筛查加纳以前研究不足的婴儿和幼儿人群中的贫血症。我们提出了一种筛选贫血的比色算法，该算法使用了三个感兴趣区域的新组合：下眼睑（眼睑结膜），巩膜和靠近下唇的粘膜。这些区域选择有最小的皮肤色素沉着阻塞血液色度。作为算法开发的一部分，对不同的方法进行了比较(1)考虑不同的环境光照，(2)为每个感兴趣的区域选择色度度量。与之前的一些工作相比，图像采集不需要专门的硬件（如彩色参考卡）。在加纳Korle Bu教学医院招募了62名4岁以下的患者作为方便的临床样本。其中43个对所有感兴趣的区域都有高质量的图像。使用naïve贝叶斯分类器，该方法能够筛查贫血（<11.0g/dL血红蛋白浓度）与健康血液血红蛋白浓度（≥11.0g/dL），灵敏度为92.9% (95% CI 66.1%至99.8%)，特异性为89.7%(72.7%至97.8%)，仅使用价格合理的智能手机，无需额外硬件。这些结果增加了大量证据，表明智能手机比色法可能是一种有用的工具，可以更广泛地进行贫血筛查。然而，对于图像预处理或特征提取的最佳方法，特别是在不同的患者群体中，仍然没有达成共识。
Anaemia affects approximately a quarter of the global population. When anaemia occurs during childhood, it can increase susceptibility to infectious diseases and impair cognitive development. This research uses smartphone-based colorimetry to develop a non-invasive technique for screening for anaemia in a previously understudied population of infants and young children in Ghana. We propose a colorimetric algorithm for screening for anaemia which uses a novel combination of three regions of interest: the lower eyelid (palpebral conjunctiva), the sclera, and the mucosal membrane adjacent to the lower lip. These regions are chosen to have minimal skin pigmentation occluding the blood chromaticity. As part of the algorithm development, different methods were compared for (1) accounting for varying ambient lighting, and (2) choosing a chromaticity metric for each region of interest. In comparison to some prior work, no specialist hardware (such as a colour reference card) is required for image acquisition. Sixty-two patients under 4 years of age were recruited as a convenience clinical sample in Korle Bu Teaching Hospital, Ghana. Forty-three of these had quality images for all regions of interest. Using a naïve Bayes classifier, this method was capable of screening for anaemia (<11.0g/dL haemoglobin concentration) vs healthy blood haemoglobin concentration (≥11.0g/dL) with a sensitivity of 92.9% (95% CI 66.1% to 99.8%), a specificity of 89.7% (72.7% to 97.8%) when acting on unseen data, using only an affordable smartphone and no additional hardware. These results add to the body of evidence suggesting that smartphone colorimetry is likely to be a useful tool for making anaemia screening more widely available. However, there remains no consensus on the optimal method for image preprocessing or feature extraction, especially across diverse patient populations.
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影响因子：
2.3
作者：
Ephraim RK;Osakunor DN;Cudjoe O;Oduro EA;Asante-Asamani L;Mitchell J;Agbodzakey H;Adoba P
通讯作者：
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