Hierarchical Tissue Segmentation

Using a hierarchical probabilistic framework to identify retinal tissue layers.

Vertical section of retina showing the tissue layers.

The retina, like many other tissues in the human body, is made up of ordered layers of different cell types. These can be distinguished when applying fairly high resolution imaging techniques such as Optical Coherence Tomography. However, currently, image segmentation algorithms that identify tissue layers are not aware of the anatomical structure and ordering of the layers. The aim is to develop a segmentation algorithm that is able to account for this prior information using a hierarchical probabilistic framework (e.g Bayesian framework).

Leads

William Woof

Postdoc Medical Imaging and AI

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