Smartphones provide an ideal platform for colorimetric measurements due to their low cost, portability and image quality. As with any imaging-based colorimetry system, ambient light and device variations introduce error which must be dealt with. We propose a novel processing method consisting of a one-time calibration stage to account for inter-phone variations, and an innovative use of ambient light subtraction with image pairs to account for variation in ambient light. Data collection is kept very simple, making it particularly useful for use in the field, since nothing additional is required in the images. Ambient subtraction is first demonstrated for a range of colors and phones (Samsung S8 and LG Nexus 5X), and the Subtracted Signal to Noise Ratio (SSNR) is defined as a metric for assessing whether an image pair is appropriate at the time of image capture. The experimentally determined SSNR threshold below which to suggest retaking the images is 3.4. The classification accuracy for results using the proposed calibration pipeline is then compared to the simplest image metadata-based alternative and is found to be greatly superior. Finally, a custom colorcard is shown to improve the accuracy of device-independent results for known smaller ranges of colors over a standard colorcard, making this a possible application-specific modification to the overall processing pipeline.
Jaundice is a major cause of mortality and morbidity in the newborn. Globally, early identification and home monitoring are significant challenges in reducing the incidence of jaundicerelated neurological damage. Smartphone cameras are promising as colour-based screening tools as they are low-cost, objective and ubiquitous. We propose a novel smartphone method to screen for neonatal jaundice by imaging the sclera. It does not rely on colour calibration cards or accessories, which may facilitate its adoption at scale and in less economically developed regions. Our approach is to explicitly address three confounding factors in relating colour to jaundice: (1) skin pigmentation, (2) ambient light, and (3) camera spectral response. (1) The variation in skin pigmentation is avoided by imaging the sclera. (2) With the smartphone screen acting as an illuminating flash, a flash/ no-flash image pair is captured using the front-facing camera. The contribution of ambient light is subtracted. (3) In principle, this permits a device-and ambient-independent measure of sclera chromaticity following a one-time calibration. We introduce the concept of Scleral-Conjunctival Bilirubin (SCB), in analogy with Transcutaneous Bilirubin (TcB). The scleral chromaticity is mapped to an SCB value. A pilot study was conducted in the UCL Hospital Neonatal Care Unit (n = 37). Neonates were imaged using a specially developed app concurrently with having a blood test for total serum bilirubin (TSB). The better of two models for SCB based on ambient-subtracted sclera chromaticity achieved r = 0.75 (p<0.01) correlation with TSB. Ambient subtraction improved chromaticity estimates in proof-of-principle laboratory tests and screening performance within our study sample. Using an SCB decision threshold of 190μmol/L, the sensitivity was 100% (specificity 61%) in identifying newborns with TSB>250μmol/L (area under receiver operating characteristic curve, AUROC, 0.86), and 92% (specificity 67%) in identifying newborns with TSB>205μmol/L (AUROC 0.85). These results are comparable to modern transcutaneous bilirubinometers.
The sclera is arguably a better site than the skin to measure jaundice–especially in dark-skinned patients–since it is free of skin pigment (melanin), a major confounding factor. This work aims to show how the yellowness of the sclera can be quantified by digital photography in color spaces including the native RGB and CIE XYZ. We also introduce a new color metric we call “Jaundice Eye Color Index” (JECI) which allows the yellowness of jaundiced sclerae to be predicted for a specific total serum bilirubin level in the neonatal population.
In order for a smartphone-based colorimetry system to be generalizable, it must be possible to account for results from multiple phones. A move from device-specific space to a device independent space such as XYZ space allows results to be compared, and means that the link between XYZ values and the physical parameter of interest needs only be determined once. We compare mapping approaches based on calibration data provided in image metadata, including the widely used open-source software dcraw, to a separate calibration carried out using a colorcard. The current version of dcraw is found to behave suboptimally with smartphones and should be used with care for mapping to XYZ. Other metadata approaches perform better, however the colorcard approach provides the best results. Several phones of the same model are compared and using an xy distance metric it is found that a device-specific calibration is required to maintain the desired precision.
A method to screen for jaundice in neonates using a digital image of the sclera is proposed. e RGB pixel values from a raw format image are used to derive an estimate for the total serum bilirubin (TSB). A study at UCH Neonatal Unit found a correlation of r=0.71 (p<0.01) between measured TSB and TSB estimated by this method. e advantages of using a smartphone camera as a mobile screening device are discussed.
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