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10.1364/BOE.8.005160 http://scihub22266oqcxt.onion/10.1364/BOE.8.005160 C5695961!5695961!29188111     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Biomed+Opt+Express 2017 ; 8 (11): 5160-78 Nephropedia Template TP {{tp|p=29188111|t=2017. Automatic detection of the foveal center in optical coherence tomography |pdf=|usr=}}{{29188111}} gab.com Text Automatic detection of the foveal center in optical coherence tomography JO: Biomed Opt Express http://www.kidney.de/pget.php?&tw=1&pmid=29188111 #FOAvip We propose a method for automatic detection of the foveal center in optical coherence tomography (OCT). The method is based on a pixel-wise classification of all pixels in an OCT volume using a fully convolutional neural network (CNN) with dilated convolution filters. The CNN-architecture contains anisotropic dilated filters and a shortcut connection and has been trained using a dynamic training procedure where the network identifies its own relevant training samples. The performance of the proposed method is evaluated on a data set of 400 OCT scans of patients affected by age-related macular degeneration (AMD) at different severity levels. For 391 scans (97.75%) the method identified the foveal center with a distance to a human reference less than 750 ?m, with a mean (± SD) distance of 71 ?m ± 107 ?m. Two independent observers also annotated the foveal center, with a mean distance to the reference of 57 ?m ± 84 ?m and 56 ?m ± 80 ?m, respectively. Furthermore, we evaluate variations to the proposed network architecture and training procedure, providing insight in the characteristics that led to the demonstrated performance of the proposed method. Twit Text FOAVip Automatic detection of the foveal center in optical coherence tomography ????Biomed Opt Express http://www.kidney.de/pget.php?&tw=1&pmid=29188111 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=29188111 #FOAvip English Wikipedia <ref>{{Cite pmid|29188111}}</ref> Automatic detection of the foveal center in optical coherence tomography #MMPMID29188111 Liefers B; Venhuizen FG; Schreur V; van Ginneken B; Hoyng C; Fauser S; Theelen T; Sánchez CI Biomed Opt Express 2017[Nov]; 8 (11): 5160-78 PMID29188111show ga We propose a method for automatic detection of the foveal center in optical coherence tomography (OCT). The method is based on a pixel-wise classification of all pixels in an OCT volume using a fully convolutional neural network (CNN) with dilated convolution filters. The CNN-architecture contains anisotropic dilated filters and a shortcut connection and has been trained using a dynamic training procedure where the network identifies its own relevant training samples. The performance of the proposed method is evaluated on a data set of 400 OCT scans of patients affected by age-related macular degeneration (AMD) at different severity levels. For 391 scans (97.75%) the method identified the foveal center with a distance to a human reference less than 750 ?m, with a mean (± SD) distance of 71 ?m ± 107 ?m. Two independent observers also annotated the foveal center, with a mean distance to the reference of 57 ?m ± 84 ?m and 56 ?m ± 80 ?m, respectively. Furthermore, we evaluate variations to the proposed network architecture and training procedure, providing insight in the characteristics that led to the demonstrated performance of the proposed method. äAutomatic detection of the foveal center in optical coherence tomograp(epmc).pdf DeepDyve Pubget Overpricing