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Rasti et al., 2018 - Google Patents

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

Rasti et al., 2018

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Document ID
17844859467312484767
Author
Rasti R
Mehridehnavi A
Rabbani H
Hajizadeh F
Publication year
Publication venue
Journal of biomedical optics

External Links

Snippet

The present research intends to propose a fully automatic algorithm for the classification of three-dimensional (3-D) optical coherence tomography (OCT) scans of patients suffering from abnormal macula from normal candidates. The method proposed does not require any …
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Classifications

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    • G06K9/62—Methods or arrangements for recognition using electronic means
    • G06K9/6267—Classification techniques
    • G06K9/6268—Classification techniques relating to the classification paradigm, e.g. parametric or non-parametric approaches
    • G—PHYSICS
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    • G06K9/36—Image preprocessing, i.e. processing the image information without deciding about the identity of the image
    • G06K9/46—Extraction of features or characteristics of the image
    • G06K9/52—Extraction of features or characteristics of the image by deriving mathematical or geometrical properties from the whole image
    • G06K9/527—Scale-space domain transformation, e.g. with wavelet analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06T2207/30004—Biomedical image processing
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    • G06K9/00—Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00221—Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
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