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Robust Phase Unwrapping via Deep Image Prior for Quantitative Phase Imaging
Related publications (43)
Multiscale light-sheet organoid imaging framework
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Live imaging of organoid growth remains a challenge: it requires long-term imaging of several samples simultaneously and dedicated analysis pipelines. Here the authors report an experimental and image processing framework to turn long-term light-sheet imag ...
NATURE PORTFOLIO2022Ultrasound Imaging: From Physical Modeling to Deep Learning
Among the medical imaging modalities, ultrasound (US) imaging is one of the safest, most widespread, and least expensive method used in medical diagnosis. In the past decades, several technological advances enabled the advent of ultrafast US imaging, an ac ...
EPFL2021Deep Learning Approaches for Auditory Perception in Robotics
Auditory perception is an essential part of a robotic system in Human-Robot Interaction (HRI), and creating an artificial auditory perception system that is on par with human has been a long-standing goal for researchers. In fact, this is a challenging res ...
EPFL2021Deep Learning Building on Prior Ischemic Core Segmentation Improves Prediction of Infarction After Stroke
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Introduction: Imaging studies are used to guide patient selection for acute stroke treatment. Perfusion CT (pCT) is widely used to identify the acute ischemic core and penumbra, but the prediction of the final infarct remains challenging. With the advent o ...
LIPPINCOTT WILLIAMS & WILKINS2021Context-Aware Image Super-Resolution Using Deep Neural Networks
Image super-resolution is a classic ill-posed computer vision and image processing problem, addressing the question of how to reconstruct a high-resolution image from its low-resolution counterpart. Current state-of-the-art methods have improved the perfor ...
EPFL2021Efficient Depth-based Deep Learning Methods for Multi-Party Pose Estimation
Human detection and pose estimation are essential components for any artificial system responsive to the presence of humans and that react according to human-centered tasks. Robotic systems are typical examples, for which the body pose represents fine grai ...
EPFL2021A Plug-and-Play Deep Image Prior
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Deep image priors (DIP) offer a novel approach for the regularization that leverages the inductive bias of a deep convolutional architecture in inverse problems. However, the quality of DIP approaches often degrades when the number of iterations exceeds a ...
IEEE2021Social media and deep learning capture the aesthetic quality of the landscape
Peoples’ recreation and well-being are closely related to their aesthetic enjoyment of the landscape. Ecosystem service (ES) assessments record the aesthetic contributions of landscapes to peoples’ well-being in support of sustainable policy goals. However ...
2021Deep Learning‐based Semantic Segmentation in Remote Sensing
Semantic segmentation consists of the generation of a categorical map, given an image in which each pixel of the image is automatically assigned a class. Deep learning allows the influence of the pixel's context to be learned by capturing the non-linear re ...
Wiley2021Brain micro-vasculature imaging: An unsupervised deep learning algorithm for segmenting mouse brain volume probed by high-resolution phase-contrast X-ray tomography
Alessandra Patera, Anne Bonnin, Marco Stampanoni
High-throughput synchrotron-based tomographic microscopy at third generation light sources allows to probe cm-sized samples at micrometer-resolution. In this work, we present an approach to image a full mouse brain. With Indian-ink as a contrast agent, it ...
WILEY2020