Titlebook: Medical Image Computing and Computer-Assisted Intervention ? MICCAI 2017; 20th International C Maxime Descoteaux,Lena Maier-Hein,Simon Duch

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QuaSI: Quantile Sparse Image Prior for?Spatio-Temporal Denoising of Retinal OCT?Data. This paper introduces a spatio-temporal denoising algorithm for OCT data on a B-scan level using a novel quantile sparse image (QuaSI) prior. To remove speckle noise while preserving image structures of diagnostic relevance, we implement our QuaSI prior via median filter regularization coupled wit

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Fast Background Removal Method for 3D Multi-channel Deep Tissue Fluorescence Imagingver, the severe background noise remains a major obstacle. In addition, there is an urgent need for fast background ground correction methods. In this paper, we present a fast background removal method for 3D multi-channel deep tissue fluorescence images, in which the objectives of different channel

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Fast Estimation of Haemoglobin Concentration in Tissue Via Wavelet Decompositionof tissue perfusion and oxygen saturation. Multispectral imaging is an optical modality that can inspect tissue perfusion in wide field images without contact. In this paper, we present a novel, fast method for using RGB images for MSI, which while limiting the spectral resolution of the modality al

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Efficient Reconstruction of Holographic Lens-Free Images by Sparse Phase Recoverye recorded diffraction pattern to reconstruct an image of the specimen. If the full, complex-valued wave-front of the diffraction pattern could be recorded then the image reconstruction process would be straight-forward, but unfortunately image sensors typically only record the amplitude of the diff

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Isotropic Reconstruction of 3D Fluorescence Microscopy Images Using Convolutional Neural Networksic extraction of quantitative biological data. While deconvolution methods and other techniques to address this problem exist, they are either time consuming to apply or limited in their ability to remove anisotropy. We propose a method to recover isotropic resolution from readily acquired anisotrop

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Deep Learning for Isotropic Super-Resolution from Non-isotropic 3D Electron Microscopyd dictionaries. Unfortunately, none of the existing methods generate practically satisfying results. For 2D natural images, recently developed super-resolution methods that use deep learning have been shown to significantly outperform the previous state of the art. We have adapted one of the most su

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Accurate Correspondence of Cone Photoreceptor Neurons in the Human Eye Using Graph Matching Applied s now feasible using adaptive optics scanning light ophthalmoscopy (AOSLO). However, it remains challenging to monitor the state of specific cells across multiple visits, due to inherent eye-motion-based distortions that arise during data acquisition, artifacts when overlapping images are montaged,

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Benjamin D. Haeffele,Richard Stahl,Geert Vanmeerbeeck,René Vidalven becomes life threatening [Suda et al. Circulation 123(17):1836–1842, 2011]. According to the literature, a quarter of untreated patients developed coronary artery aneurysms (CAA) [McCrindle et al. Circulation 135(17):e927–e999, 2017]. As to the retrospective diagnosis, usually CAA was discovered