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10.1007/s10278-016-9932-7 http://scihub22266oqcxt.onion/10.1007/s10278-016-9932-7 C5359214!5359214!28025730     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Digit+Imaging 2017 ; 30 (2): 204-14 Nephropedia Template TP {{tp|p=28025730|t=2017. Automated Facial Recognition of Computed Tomography-Derived Facial Images: Patient Privacy Implications |pdf=|usr=}}{{28025730}} gab.com Text Automated Facial Recognition of Computed Tomography-Derived Facial Images: Patient Privacy Implications JO: J Digit Imaging http://www.kidney.de/pget.php?&tw=1&pmid=28025730 #FOAvip The recognizability of facial images extracted from publically available medical scans raises patient privacy concerns. This study examined how accurately facial images extracted from computed tomography (CT) scans are objectively matched with corresponding photographs of the scanned individuals. The test subjects were 128 adult Americans ranging in age from 18 to 60 years, representing both sexes and three self-identified population (ancestral descent) groups (African, European, and Hispanic). Using facial recognition software, the 2D images of the extracted facial models were compared for matches against five differently sized photo galleries. Depending on the scanning protocol and gallery size, in 6?61 % of the cases, a correct life photo match for a CT-derived facial image was the top ranked image in the generated candidate lists, even when blind searching in excess of 100,000 images. In 31?91 % of the cases, a correct match was located within the top 50 images. Few significant differences (p > 0.05) in match rates were observed between the sexes or across the three age cohorts. Highly significant differences (p < 0.01) were, however, observed across the three ancestral cohorts and between the two CT scanning protocols. Results suggest that the probability of a match between a facial image extracted from a medical scan and a photograph of the individual is moderately high. The facial image data inherent in commonly employed medical imaging modalities may need to consider a potentially identifiable form of ?comparable? facial imagery and protected as such under patient privacy legislation. Twit Text FOAVip Automated Facial Recognition of Computed Tomography-Derived Facial Images: Patient Privacy Implications ????J Digit Imaging http://www.kidney.de/pget.php?&tw=1&pmid=28025730 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28025730 #FOAvip English Wikipedia <ref>{{Cite pmid|28025730}}</ref> Automated Facial Recognition of Computed Tomography-Derived Facial Images: Patient Privacy Implications #MMPMID28025730 Parks CL; Monson KL J Digit Imaging 2017[Apr]; 30 (2): 204-14 PMID28025730show ga The recognizability of facial images extracted from publically available medical scans raises patient privacy concerns. This study examined how accurately facial images extracted from computed tomography (CT) scans are objectively matched with corresponding photographs of the scanned individuals. The test subjects were 128 adult Americans ranging in age from 18 to 60 years, representing both sexes and three self-identified population (ancestral descent) groups (African, European, and Hispanic). Using facial recognition software, the 2D images of the extracted facial models were compared for matches against five differently sized photo galleries. Depending on the scanning protocol and gallery size, in 6?61 % of the cases, a correct life photo match for a CT-derived facial image was the top ranked image in the generated candidate lists, even when blind searching in excess of 100,000 images. In 31?91 % of the cases, a correct match was located within the top 50 images. Few significant differences (p > 0.05) in match rates were observed between the sexes or across the three age cohorts. Highly significant differences (p < 0.01) were, however, observed across the three ancestral cohorts and between the two CT scanning protocols. Results suggest that the probability of a match between a facial image extracted from a medical scan and a photograph of the individual is moderately high. The facial image data inherent in commonly employed medical imaging modalities may need to consider a potentially identifiable form of ?comparable? facial imagery and protected as such under patient privacy legislation. äAutomated Facial Recognition of Computed Tomography-Derived Facial Ima(epmc).pdf DeepDyve Pubget Overpricing