Automatic diagnosis of abnormal macula in retinal optical coherence tomography images using wavelet-based convolutional neural network features and random forests classifier.

scientific article published in March 2018

Automatic diagnosis of abnormal macula in retinal optical coherence tomography images using wavelet-based convolutional neural network features and random forests classifier. is …
instance of (P31):
scholarly articleQ13442814

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P819ADS bibcode2018JBO....23c5005R
P356DOI10.1117/1.JBO.23.3.035005
P698PubMed publication ID29564864

P50authorHossein RabbaniQ40046361
Fedra HajizadehQ84080729
P2093author name stringAlireza Mehridehnavi
Reza Rasti
P2860cites workRandom ForestsQ115707260
P433issue3
P921main subjectautomationQ184199
random forestQ245748
convolutional neural networkQ17084460
P304page(s)1-10
P577publication date2018-03-01
P1433published inJournal of Biomedical OpticsQ15766132
P1476titleAutomatic diagnosis of abnormal macula in retinal optical coherence tomography images using wavelet-based convolutional neural network features and random forests classifier
P478volume23

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cites work (P2860)
Q64108567Automatic detection of retinal regions using fully convolutional networks for diagnosis of abnormal maculae in optical coherence tomography images
Q64266702Convolutional Mixture of Experts Model: A Comparative Study on Automatic Macular Diagnosis in Retinal Optical Coherence Tomography Imaging
Q90056412Deep learning-based single-shot prediction of differential effects of anti-VEGF treatment in patients with diabetic macular edema

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