Multi-MHz retinal OCT.
Ontology highlight
ABSTRACT:
SUBMITTER: Klein T
PROVIDER: S-EPMC3799654 | biostudies-other | 2013
REPOSITORIES: biostudies-other
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Project description:Retinal imaging helps to detect retinal and cardiovascular abnormalities. Among these abnormalities, Diabetic Macular Edema (DME) and Age Related Macular Degeneration (AMD), both are frequent retinal degenerative diseases leading to blindness. Content based retinal OCT scan retrieval process makes use of characteristic features to retrieve similar Optical Coherent Tomography (OCT) scans, index-wise, from a database with minimal human intervention. A number of existing methods take care of segmentation and identification of retinal landmarks and pathologies from OCT volumes. As per the literature survey, till date, no papers are there which deal with the retrieval of retinal OCT scans. In this work, we propose a retrieval system for retinal OCT scans which extracts feature maps of both query and database samples from the layer of deep convolutional neural network and compares for their similarity. The Twin network comparison approach exploits deep features without the resource, space and computation exhaustive network training phase. Most of the techniques involving deep network implementation suffer from the drawbacks of data augmentation and resizing. These requirements have been eliminated automatically as part of the Twin network implementation procedure. The system successfully retrieves retinas with similar symptoms from the database of differently affected and unaffected OCT scans. We evaluated different variations of retrieval performances like AMD-Normal, DME-Normal, AMD-DME, AMD-DME-Normal, etc. Execution time optimization has also been achieved as the network used is comparatively shallow and network training is not required. The system retrieves similar scans from a dataset of abnormal and normal OCT scans with a mean average precision of 0.7571 and mean reciprocal rank of 0.9050. Considering all possible variations of retrieval, we achieved overall mean average precision and mean reciprocal rank of 0.631167 and 0.829607, respectively which are also quite notable with rank thresholds of 3, 5 and 7. Experiments show that the method is noticeably successful in retrieving similar OCT volumes. Per image mean average retrieval time is 8.3 sec. Automatic retrieval of retinal OCT volumes for the presence of a particular ailment can help ophthalmologists in the mass screening process. Supplementary Information The online version contains supplementary material available at 10.1007/s12046-021-01701-5.
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Project description:PurposeThis prospective case series is aimed at exploring optical coherence tomographic angiography (OCT-A) as a treatment monitoring tool in patients treated for retinal angiomatous proliferation (RAP).MethodsTwelve treatment-naïve RAP patients were included, with a median age of 79 years (range 65-90). Patients were imaged with an experimental 1,040-nm swept-source phase-resolved OCT-A instrument before and after treatment. Treatment consisted of either intravitreal bevacizumab or triamcinolone injections with or without photodynamic therapy (PDT). Abnormal blood flow after treatment was graded as increased, unchanged, decreased, or resolved.ResultsOCT-A images before and after treatment could be obtained in 9 patients. The median follow-up period was 10 weeks (range 5-19). After various treatments, the RAP lesion resolved in 7 patients, in 1 patient the OCT-A depicted decreased flow in the lesion, and 1 patient showed unchanged abnormal blood flow. Monotherapy with intravitreal bevacizumab injections resolved RAP in 1 out of 2 patients. Combined therapy of bevacizumab with PDT resolved RAP in 6 out of 7 patients.ConclusionsOCT-A visualized resolution of abnormal blood flow in 7 out of 9 RAP patients after various short-term treatment sequences. OCT-A may become an important noninvasive monitoring tool for optimizing treatment strategies in RAP patients.
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