  Optical Coherence Tomography (OCT) is one of the most emerging imaging
modalities that has been used widely in the field of biomedical imaging. From
its emergence in 1990's, plenty of hardware and software improvements have been
made. Its applications range from ophthalmology to dermatology to coronary
imaging etc. Here, the focus is on applications of OCT in ophthalmology and
retinal imaging. OCT is able to non-invasively produce cross-sectional volume
images of the tissues which are further used for analysis of the tissue
structure and its properties. Due to the underlying physics, OCT images usually
suffer from a granular pattern, called speckle noise, which restricts the
process of interpretation, hence requiring specialized noise reduction
techniques to remove the noise while preserving image details. Also, given the
fact that OCT images are in the $\mu m$ -level, further analysis in needed to
distinguish between the different structures in the imaged volume. Therefore
the use of different segmentation techniques are of high importance. The
movement of the tissue under imaging or the progression of disease in the
tissue also imposes further implications both on the quality and the proper
interpretation of the acquired images. Thus, use of image registration
techniques can be very helpful. In this work, an overview of such image
analysis techniques will be given.
