2016
DOI: 10.1007/s11548-016-1383-6
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Automatic assessment of time-resolved OCT images for selective retina therapy

Abstract: Purpose In recent years, selective retina laser treatment (SRT), a sub-threshold therapy method, avoids widespread damage to all retinal layers by targeting only a few. While these methods facilitate faster healing, their lack of visual feedback during treatment represents a considerable shortcoming as induced lesions remain invisible with conventional imaging and make clinical use challenging. To overcome this, we present a new strategy to provide location-specific and contact-free automatic feedback of SRT l… Show more

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Cited by 13 publications
(11 citation statements)
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References 18 publications
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“…There are different optical [21][22][23][24] and acoustical 25 techniques to detect microbubbles as indicators of RPE cell damage. One approach is based on the evaluation of pressure waves emitted during the formation and dynamics of microbubbles.…”
Section: Microbubble Detection Techniquesmentioning
confidence: 99%
See 1 more Smart Citation
“…There are different optical [21][22][23][24] and acoustical 25 techniques to detect microbubbles as indicators of RPE cell damage. One approach is based on the evaluation of pressure waves emitted during the formation and dynamics of microbubbles.…”
Section: Microbubble Detection Techniquesmentioning
confidence: 99%
“…Another experimental approach is based on an evaluation of bubble-related tissue displacement through optical coherence tomography. 23,24 A further experimental optical approach makes use of the evaluation of the backscattered light of a scanned laser beam. In this case, an increase in backscattered treatment light, induced by additional Mie-scatterers (microbubbles), is detected.…”
Section: Microbubble Detection Techniquesmentioning
confidence: 99%
“…Optical coherence tomography (OCT), which can provide depth-resolved imaging, was also applied for the SRT monitoring. [15][16][17][18][19] The treatments are considered successful when OCT signal variations, i.e., intensity decrease, are detected, and the results show good agreement with the evaluation of lesions by FFA.…”
Section: Introductionmentioning
confidence: 84%
“…As assumed, features found within the first 100 ms after exposure deliver the highest yield, while later portions of the signal between 100 and 300 ms after the exposure pulse continuously lose their relation to the distortion. Such automated analysis boosts prediction to success rates from initial ~60% beyond 90% when targeting for 95% specificity [93].…”
Section: Future Developments Towards Reliably Detecting the Microbubbmentioning
confidence: 99%