2017
DOI: 10.1145/3090085
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BiliScreen

Abstract: Pancreatic cancer has one of the worst survival rates amongst all forms of cancer because its symptoms manifest later into the progression of the disease. One of those symptoms is jaundice, the yellow discoloration of the skin and sclera due to the buildup of bilirubin in the blood. Jaundice is only recognizable to the naked eye in severe stages, but a ubiquitous test using computer vision and machine learning can detect milder forms of jaundice. We propose BiliScreen, a smartphone app that captures pictures o… Show more

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Cited by 35 publications
(17 citation statements)
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“…One smartphone-based technique has used the scleral color to identify jaundiced adult patients with pancreatic cancer [8]. After considering 105 color features with different color spaces, color channels, pixel selection methods and RGB ratios, the study found that the ratio of green to blue channels in the RGB color space is one color metric that best correlates with the data.…”
Section: Discussionmentioning
confidence: 99%
“…One smartphone-based technique has used the scleral color to identify jaundiced adult patients with pancreatic cancer [8]. After considering 105 color features with different color spaces, color channels, pixel selection methods and RGB ratios, the study found that the ratio of green to blue channels in the RGB color space is one color metric that best correlates with the data.…”
Section: Discussionmentioning
confidence: 99%
“…Research interest in smartphone-based jaundice screening is growing, and recent work is promising [15][16][17][18][19][20][21][22]. The most extensively validated system is the BiliCam app that estimates total serum bilirubin (TSB) based on the skin colour of the sternum [15].…”
Section: Plos Onementioning
confidence: 99%
“…The sclera accumulates bilirubin while lacking the melanin and haemoglobin chromophores found in skin. It has been suggested that this permits a more sensitive measure of jaundice [17,23]. Secondly, we introduce a novel ambient subtraction method using the screen of the phone to illuminate the subject.…”
Section: Plos Onementioning
confidence: 99%
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“…Sclera segmentation algorithms have been developed by researchers interested in biometric identification using sclera vasculature [42,43]. Mariakakis et al developed their own segmentation using accessories as fiducials [17].…”
Section: Limitations and Future Workmentioning
confidence: 99%