Rahman Attar, Guillem Hurault, Zihao Wang, Ricardo Mokhtari, Kevin Pan, Bayanne Olabi, Eleanor Earp, Lloyd Steele, Hywel C. Williams, Reiko J. Tanaka
{"title":"可靠的检测湿疹区域,全自动评估湿疹严重程度从数码相机图像","authors":"Rahman Attar, Guillem Hurault, Zihao Wang, Ricardo Mokhtari, Kevin Pan, Bayanne Olabi, Eleanor Earp, Lloyd Steele, Hywel C. Williams, Reiko J. Tanaka","doi":"10.1101/2022.11.05.22281951","DOIUrl":null,"url":null,"abstract":"Assessing the severity of eczema in clinical research requires face-to-face skin examination by trained staff. Such approaches are resource-intensive for participants and staff, challenging during pandemics, and prone to inter- and intra-observer variation. Computer vision algorithms have been proposed to automate the assessment of eczema severity using digital camera images. However, they often require human intervention to detect eczema lesions and cannot automatically assess eczema severity from real-world images in an end-to-end pipeline.","PeriodicalId":501385,"journal":{"name":"medRxiv - Dermatology","volume":"22 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Reliable detection of eczema areas for fully automated assessment of eczema severity from digital camera images\",\"authors\":\"Rahman Attar, Guillem Hurault, Zihao Wang, Ricardo Mokhtari, Kevin Pan, Bayanne Olabi, Eleanor Earp, Lloyd Steele, Hywel C. Williams, Reiko J. Tanaka\",\"doi\":\"10.1101/2022.11.05.22281951\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Assessing the severity of eczema in clinical research requires face-to-face skin examination by trained staff. Such approaches are resource-intensive for participants and staff, challenging during pandemics, and prone to inter- and intra-observer variation. Computer vision algorithms have been proposed to automate the assessment of eczema severity using digital camera images. However, they often require human intervention to detect eczema lesions and cannot automatically assess eczema severity from real-world images in an end-to-end pipeline.\",\"PeriodicalId\":501385,\"journal\":{\"name\":\"medRxiv - Dermatology\",\"volume\":\"22 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-11-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"medRxiv - Dermatology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2022.11.05.22281951\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Dermatology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2022.11.05.22281951","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reliable detection of eczema areas for fully automated assessment of eczema severity from digital camera images
Assessing the severity of eczema in clinical research requires face-to-face skin examination by trained staff. Such approaches are resource-intensive for participants and staff, challenging during pandemics, and prone to inter- and intra-observer variation. Computer vision algorithms have been proposed to automate the assessment of eczema severity using digital camera images. However, they often require human intervention to detect eczema lesions and cannot automatically assess eczema severity from real-world images in an end-to-end pipeline.