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Boltzmann Machines for Image Denoising [PDF]
, 2013 Image denoising based on a probabilistic model of local image patches has been employed by various researchers, and recently a deep denoising autoencoder has been proposed in [2] and [17] as a good model for this. In this paper, we propose that another popular family of models in the field of deep learning, called Boltzmann machines, can perform image ...
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Multiwedgelets in Image Denoising
2013In this paper the definition of a multiwedgelet is introduced. The multiwedgelet is defined as a vector of wedgelets. In order to use a multiwedgelet in image approximation its visualization and computation methods are also proposed. The application of multiwedgelets in image denoising is presented, as well.
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Automated molecular-image cytometry and analysis in modern oncology
Nature Reviews Materials, 2020Ralph Weissleder, Hakho Lee
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nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation
Nature Methods, 2020Fabian Isensee +2 more
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Ultrafast machine vision with 2D material neural network image sensors
Nature, 2020Lukas Mennel +2 more
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Image-based profiling for drug discovery: due for a machine-learning upgrade?
Nature Reviews Drug Discovery, 2020Srinivas Niranj Chandrasekaran +2 more
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DENOISING OF MULTICHANNEL IMAGES WITH REFERENCES [PDF]
Telecommunications and Radio Engineering, 2017 Sergey K. Abramov +4 more
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Image-guided cancer surgery using near-infrared fluorescence
Nature Reviews Clinical Oncology, 2013Alexander L Vahrmeijer +1 more
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A survey on deep learning in medical image analysis
Medical Image Analysis, 2017Geert Js Litjens +2 more
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