1. Segmentation of mouse skin layers in optical coherence tomography image data using deep convolutional neural networks

    Segmentation of mouse skin layers in optical coherence tomography image data using deep convolutional neural networks

    Optical coherence tomography (OCT) enables the non-invasive acquisition of high-resolution three-dimensional cross-sectional images at micrometer scale and is mainly used in the field of ophthalmology for diagnosis as well as monitoring of eye diseases. Also in other areas, such as dermatology, OCT is already well established. Due to its non-invasive nature, OCT is also employed for research studies involving animal models. Manual evaluation of OCT images of animal models is a challenging task due to the lack of imaging standards and the varying anatomy between models. In this paper, we present a deep learning algorithm for the automatic segmentation of ...

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