1. Deep learning based 2.5D flow field estimation for maximum intensity projections of 4D optical coherence tomography

    Deep learning based 2.5D flow field estimation for maximum intensity projections of 4D optical coherence tomography

    In laser microsurgery, image-based control of the ablation laser can lead to higher accuracy and patient safety. However, camera-based image acquisition lacks the subcutaneous tissue perception. Optical coherence tomography (OCT) as high-resolution imaging modality yields transsectional images of tissue and can provide the missing depth information. Therefore, this paper deals with the tracking of distinctive subcutaneous structures on OCTs for automated control of ablation lasers in microsurgery. We present a deep learning based tracking scheme for concise representations of subsequent 3D OCT volumes. For each of the volume, a compact representation is created by calculating maximum intensity projections and projecting ...

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