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

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Endoscopic Depth Measurement and Super-Spectral-Resolution Imaginghereby the RGB images and sparse hyperspectral data were integrated to recover dense pixel-level hyperspectral stacks, by using convolutional neural networks to upscale the wavelength dimension. Validation and demonstration of this system is reported on ./. animal/human experiments.
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Refocusing Phase Contrast Microscopy Imagese proposed algorithm is both qualitatively and quantitatively evaluated on a dataset of 500 phase contrast microscopy images, showing its superior performance for visualizing specimens and facilitating microscopy image analysis.
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QuaSI: Quantile Sparse Image Prior for Spatio-Temporal Denoising of Retinal OCT Datautive B-scans, to gain volumetric OCT data with enhanced signal-to-noise ratio. Our algorithm based on 4 B-scans only achieved comparable performance to averaging 13 B-scans and outperformed other current denoising methods.
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Fast Background Removal Method for 3D Multi-channel Deep Tissue Fluorescence Imaginghe whole images by interpolation. Experiments on real 3D datasets of mouse stomach show our method has superior performance and efficiency comparing with the current state-of-the-art background correction methods.
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Efficient Reconstruction of Holographic Lens-Free Images by Sparse Phase Recoveryity over existing techniques, allows for the possibility of reconstructing images over a 3D volume of focal-depths simultaneously from a single recorded hologram, provides a robust estimate of the missing phase information in the hologram, and automatically identifies the focal depths of the imaged objects in a robust manner.
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Histological Detection of High-Risk Benign Breast Lesions from Whole Slide Imagesisk benign lesions based on pathology reports and collected ground truth annotations from three different pathologists for the ductal ROIs segmented by our pipeline. Our method has comparable performance to a pool of expert pathologists.
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Medical Image Computing and Computer-Assisted Intervention − MICCAI 201720th International C
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