https://socictopen.socict.org/files/original/d55a323950c8192a68fa281c765f346d.pdf 6fd54d3282dc74d8a80e72dc687d1703 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Free-Form Deformation Approach for Registration of Visible and Infrared Facial Images in Fever Screening Creator An entity primarily responsible for making the resource Yedukondala Narendra Dwith Chenna, Pejhman Ghassemi, T. Joshua Pfefer, Jon Casamento, Quanzeng Wang Description An account of the resource Fever screening based on infrared (IR) thermographs (IRTs) is an approach that has been implemented during infectious disease pandemics, such as Ebola and Severe Acute Respiratory Syndrome. A recently published international standard indicates that regions medially adjacent to the inner canthi provide accurate estimates of core body temperature and are preferred sites for fever screening. Therefore, rapid, automated identification of the canthi regions within facial IR images may greatly facilitate rapid fever screening of asymptomatic travelers. However, it is more difficult to accurately identify the canthi regions from IR images than from visible images that are rich with exploitable features. In this study, we developed and evaluated techniques for multi-modality image registration (MMIR) of simultaneously captured visible and IR facial images for fever screening. We used free form deformation (FFD) models based on edge maps to improve registration accuracy after an affine transformation. Two widely used FFD models in medical image registration based on the Demons and cubic B-spline algorithms were qualitatively compared. The results showed that the Demons algorithm outperformed the cubic B-spline algorithm, likely due to overfitting of outliers by the latter method. The quantitative measure of registration accuracy, obtained through selected control point correspondence, was within 2.8 ± 1.2 mm, which enables accurate and automatic localization of canthi regions in the IR images for temperature measurement. Date A point or period of time associated with an event in the lifecycle of the resource 2018 Subject The topic of the resource thermal imaging, Fever screening, temperature measurement, canthi detection, multi-modality image registration, Free-form deformation, Demons algorithm, cubic B-spline algorithm Identifier An unambiguous reference to the resource within a given context DOI: 10.3390/s18010125 Source A related resource from which the described resource is derived Sensors Publisher An entity responsible for making the resource available MDPI AG Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Chemical technology Language A language of the resource EN