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Python implementation of optical coherence tomography(OCT) data pre-process: 1.retina detection 2. OCT normalization 3. retina flatten

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OCT_preprocess by Weiting Tan

Preprocess of Optical coherence tomography (OCT) includes following steps:

  1. octSpectrailisReader convert OCT image into python processable nd-array and retrieve useful information in the image OCT image in the first layer shown by matlab.pyplot.imshow:

sc1 sc2

  1. retinaDetect find the boundaries of inner limiting membrane(ILM), inner segment(IS), outer segment (OS) and Bruch’s membrane (BM) Three lines on the image shown are the ILM, ISOS(combinatino of IS and OS), and BM boundaries detected by the code:

sc3 sc4

  1. normalizeOCT normalize and reduce noise of the OCT image after normalizing the image, grayscale image looks like: sc5

  2. retinaFlatten calculate the shitfs based on return value in retinaDetect and flatten the image using BM as baseline. The final image in both grayscale and RGB:

sc6 sc7

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Python implementation of optical coherence tomography(OCT) data pre-process: 1.retina detection 2. OCT normalization 3. retina flatten

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