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Philips Healthcare deep learning algorithm
Deep Learning Algorithm, supplied by Philips Healthcare, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/deep+learning/algorithm+learning+machine+multi+step/pm42275855-41-9-12
Average 86 stars, based on 1 article reviews
deep learning algorithm - by Bioz Stars, 2026-10
86/100 stars

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Related Articles

other:

Article Title: Impact of a deep-learning image reconstruction algorithm on image quality and detection of solid lung lesions
Article Snippet: In 2021, another CT vendor (Philips Healthcare) developed a new deep-learning image reconstruction algorithm.

Article Title: Deep learning-enhanced super-resolution diffusion-weighted liver MRI: improved image quality, diagnostic performance, and acceleration
Article Snippet: The deep learning super-resolution algorithm was provided by Philips Healthcare, which aims to accelerate scanning and enhance image resolution.

Article Title: Impact of a deep-learning image reconstruction algorithm on image quality and detection of solid lung lesions
Article Snippet: In the present study, we compared the quality of chest CT images obtained with the new deep-learning image reconstruction algorithm, developed by Philips Healthcare (Precise Image) and with an iterative reconstruction algorithm.

Article Title: Comparison of methods for intravoxel incoherent motion parameter estimation in the brain from flow-compensated and non-flow-compensated diffusion-encoded data.
Article Snippet: The authors thank the Philips Clinical Science Group for implementation support and Oliver Gurney-Champion for making the deep learning-based code publicly available.

Article Title: Deep learning-enhanced super-resolution diffusion-weighted liver MRI: improved image quality, diagnostic performance, and acceleration.
Article Snippet: The deep learning super-resolution algorithm was provided by Philips Healthcare, which aims to accelerate scanning and enhance image resolution.

Article Title: Clinical feasibility of a commercially available MRI-only method for radiotherapy treatment planning of the brain.
Article Snippet: The sCT images were generated using a commercially available, deep-learning based algorithm (magnetic resonance for calculating attenuation, MRCAT Brain, version 4.0; Philips Oy, Vantaa, Finland).

Software:

Article Title: Comparison of precise imaging and iterative reconstruction techniques at low doses using the dose right index in 100-kVp cerebral CT angiography.
Article Snippet: .. They were subsequently reconstructed using the Precise Image deep-learning algorithm (Philips CT Smart Workflow, 2024 build) on a Philips Incisive CT system (software version 5.01, Philips Healthcare, Best) with a standard kernel, 0.8 mm slice thickness, 0.4 mm slice increment, and default denoising and sharpness settings, enabling a direct comparison of image quality and quantitative metrics between the two reconstruction methods. ..

Comparison:

Article Title: Comparison of precise imaging and iterative reconstruction techniques at low doses using the dose right index in 100-kVp cerebral CT angiography.
Article Snippet: .. They were subsequently reconstructed using the Precise Image deep-learning algorithm (Philips CT Smart Workflow, 2024 build) on a Philips Incisive CT system (software version 5.01, Philips Healthcare, Best) with a standard kernel, 0.8 mm slice thickness, 0.4 mm slice increment, and default denoising and sharpness settings, enabling a direct comparison of image quality and quantitative metrics between the two reconstruction methods. ..



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