An ultra high resolution spectral-domain optical coherence tomography(SD-OCT)together with an advanced animal restraint and positioning system was built for noninvasive non-contact in vivo three-dimensional imaging of...An ultra high resolution spectral-domain optical coherence tomography(SD-OCT)together with an advanced animal restraint and positioning system was built for noninvasive non-contact in vivo three-dimensional imaging of rodent models of ocular diseases.The animal positioning system allowed the operator to rapidly locate and switch the areas of interest on the retina.This function together with the capability of precise spatial registration provided by the generated OCT fundus image allows the system to locate and compare the same lesion(retinal tumor in the current study)at different time point throughout the entire course of the disease progression.An algorithm for fully automatic segmentation of the tumor boundaries and calculation of tumor volume was developed.The system and algorithm were successfully applied to monitoring retinal tumor growth quantitatively over time in the LHBETATAG mouse model of retinoblastoma.展开更多
基金supported in part by the NIH(NEI grant R01 EY01629)the NEI P30 Core Grant Ey014801 and U.S.Army Medical Research and Materiel Command(USAMRMC)grant W81XWH-07-1-0188.
文摘An ultra high resolution spectral-domain optical coherence tomography(SD-OCT)together with an advanced animal restraint and positioning system was built for noninvasive non-contact in vivo three-dimensional imaging of rodent models of ocular diseases.The animal positioning system allowed the operator to rapidly locate and switch the areas of interest on the retina.This function together with the capability of precise spatial registration provided by the generated OCT fundus image allows the system to locate and compare the same lesion(retinal tumor in the current study)at different time point throughout the entire course of the disease progression.An algorithm for fully automatic segmentation of the tumor boundaries and calculation of tumor volume was developed.The system and algorithm were successfully applied to monitoring retinal tumor growth quantitatively over time in the LHBETATAG mouse model of retinoblastoma.
