BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:Europe/Warsaw BEGIN:DAYLIGHT DTSTART:20140330T030000 TZOFFSETFROM:+0100 TZOFFSETTO:+0200 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=3 TZNAME:CEST END:DAYLIGHT BEGIN:STANDARD DTSTART:20141026T020000 TZOFFSETFROM:+0200 TZOFFSETTO:+0100 RRULE:FREQ=YEARLY;BYDAY=-1SU;BYMONTH=10 TZNAME:CET END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20150115T210036Z UID:F134E20C-E5B6-11E7-833E-0050568D7F66 DTSTART;TZID=Europe/Warsaw:20140331T114500 DTEND;TZID=Europe/Warsaw:20140331T124500 DESCRIPTION:Optical Coherence Tomography (OCT) is a method of non-contact a nd non-invasive imaging of the internal structure of the objects semi-tran sparent to the []infrared light. This method originates from medicine wher e it has been successfully used as a diagnostic tool in ophthalmology sinc e 1991. OCT has been also used in conservation science for about ten years .\n\nThe application of Fourier domain methods led to a significant increa se in the data acquisition speed. However\, relatively complicated data pr ocessing is necessary to generate OCT tomograms in this case and thus the data visualization and analysis usually take more time than the data acqui sition. This is a considerable disadvantage\, especially in applications i n which an immediate evaluation of results is crucial. Recent progress in graphic cards technology gives a promising solution to this problem – th e newest graphics processing units (GPU) allow not only for high speed thr ee dimensional (3D) rendering\, but also for very fast general purpose num erical calculations with efficiency higher than provided by the CPU.\n\nIn this presentation the application of general-purpose computing on graphic s processing units (GPGPU) for optical coherence tomography data processin g and imaging will be presented. Utilisation of GPU and reformulation of a lgorithms towards higher efficiency of data processing allowed for real-ti me imaging of two dimensional tomograms with a best available quality: our software for the OCT data processing is capable of visualization of 2D da ta (2000 A-scans\, 2048 pixels per spectrum) with an image refresh rate hi gher than 120 Hz.\n\nData processing on GPU allows also for 3D imaging in real-time which has not been possible so far: the processing and rendering of the 3D (volume) data comprising 100 2D tomograms built of 100 A-scans each is performed at a rate of about 11 volumes per second.\n\nIn recent y ears\, several extensions to the OCT method have been successfully applied . One of them is Doppler OCT which allows\, among others\, for examination of blood flow velocity in capillary vessels. The other variant is used fo r reduction of speckle noise in the resulting cross sectional image. Both of them are dependent on the scanning protocol parameters which have to be adjusted to the examined object properties and examination conditions. Un til now\, the parameters of the scanning protocol have to be regulated by the user. But if the OCT data processing is fast enough for real-time anal ysis of the image (as it is possible with use of the GPGPU)\, the process of adaptation of the scanning protocol may be done automatically. In this report\, the algorithms for automatic adaptation of the scanning protocols in the Doppler OCT and for the speckle noise reduction method will be pre sented.\n\nPoznan\, Wielkopolskie\, Poland LOCATION:Poznan\, Wielkopolskie\, Poland ORGANIZER: SEQUENCE:0 SUMMARY:[Legacy Report] Data processing in Spectral Optical Coherence Tomog raphy on graphics processing units URL;VALUE=URI:https://events.vtools.ieee.org/m/111506 X-ALT-DESC:Description: <br /><p>Optical Coherence Tomography (OCT) is a me thod of non-contact and non-invasive imaging of the internal structure of the objects semi-transparent to the <a name="_GoBack"></a>infrared light. This method originates from medicine where it has been successfully used a s a diagnostic tool in ophthalmology since 1991. OCT has been also used in conservation science for about ten years.</p>\n<p>The application of Four ier domain methods led to a significant increase in the data acquisition s peed. However\, relatively complicated data processing is necessary to gen erate OCT tomograms in this case and thus the data visualization and analy sis usually take more time than the data acquisition. This is a considerab le disadvantage\, especially in applications in which an immediate evaluat ion of results is crucial. Recent progress in graphic cards technology giv es a promising solution to this problem &ndash\; the newest graphics proce ssing units (GPU) allow not only for high speed three dimensional (3D) ren dering\, but also for very fast general purpose numerical calculations wit h efficiency higher than provided by the CPU.</p>\n<p>In this presentation the application of general-purpose computing on graphics processing units (GPGPU) for optical coherence tomography data processing and imaging will be presented. Utilisation of GPU and reformulation of algorithms towards higher efficiency of data processing allowed for real-time imaging of two dimensional tomograms with a best available quality: our software for the OCT data processing is capable of visualization of 2D data (2000 A-scans\, 2048 pixels per spectrum) with an image refresh rate higher than 120 Hz.< /p>\n<p>Data processing on GPU allows also for 3D imaging in real-time whi ch has not been possible so far: the processing and rendering of the 3D (v olume) data comprising 100 2D tomograms built of 100 A-scans each is perfo rmed at a rate of about 11 volumes per second.</p>\n<p>In recent years\, s everal extensions to the OCT method have been successfully applied. One of them is Doppler OCT which allows\, among others\, for examination of bloo d flow velocity in capillary vessels. The other variant is used for reduct ion of speckle noise in the resulting cross sectional image. Both of them are dependent on the scanning protocol parameters which have to be adjuste d to the examined object properties and examination conditions. Until now\ , the parameters of the scanning protocol have to be regulated by the user . But if the OCT data processing is fast enough for real-time analysis of the image (as it is possible with use of the GPGPU)\, the process of adapt ation of the scanning protocol may be done automatically. In this report\, the algorithms for automatic adaptation of the scanning protocols in the Doppler OCT and for the speckle noise reduction method will be presented.< /p> END:VEVENT END:VCALENDAR