Výsledky vyhledávání - "Gutjahr, Ralf"

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Multi-Layer Gaussian Splatting for Immersive Anatomy Visualization

Autor: Kleinbeck, Constantin, Schieber, Hannah, Engel, Klaus, Gutjahr, Ralf, Roth, Daniel

In medical image visualization, path tracing of volumetric medical data like CT scans produces lifelike three-dimensional visualizations. Immersive VR displays can further enhance the understanding of complex anatomies. Going beyond the diagnostic qu

Externí odkaz: http://arxiv.org/abs/2410.16978

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Limited Parameter Denoising for Low-dose X-ray Computed Tomography Using Deep Reinforcement Learning

Autor: Patwari, Mayank, Gutjahr, Ralf, Raupach, Rainer, Maier, Andreas

The use of deep learning has successfully solved several problems in the field of medical imaging. Deep learning has been applied to the CT denoising problem successfully. However, the use of deep learning requires large amounts of data to train deep

Externí odkaz: http://arxiv.org/abs/2203.14794

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Low Dose CT Denoising via Joint Bilateral Filtering and Intelligent Parameter Optimization

Autor: Patwari, Mayank, Gutjahr, Ralf, Raupach, Rainer, Maier, Andreas

Denoising of clinical CT images is an active area for deep learning research. Current clinically approved methods use iterative reconstruction methods to reduce the noise in CT images. Iterative reconstruction techniques require multiple forward and

Externí odkaz: http://arxiv.org/abs/2007.04768

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JBFnet -- Low Dose CT Denoising by Trainable Joint Bilateral Filtering

Autor: Patwari, Mayank, Gutjahr, Ralf, Raupach, Rainer, Maier, Andreas

Deep neural networks have shown great success in low dose CT denoising. However, most of these deep neural networks have several hundred thousand trainable parameters. This, combined with the inherent non-linearity of the neural network, makes the de

Externí odkaz: http://arxiv.org/abs/2007.04754

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