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Radiation Dosage

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EDRAM-Net: Encoder-Decoder with Residual Attention Module Network for Low-dose Computed Tomography Reconstruction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
The medical application of Computed Tomography (CT) is to provide detailed anatomical structures of patients without the need for invasive procedures like surgery, which is very useful for clinicians in disease diagnosis. Excessive radiation exposure...

Effectiveness of AI for Enhancing Computed Tomography Image Quality and Radiation Protection in Radiology: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: Artificial intelligence (AI) presents a promising approach to balancing high image quality with reduced radiation exposure in computed tomography (CT) imaging.

Radiotherapy dose prediction using off-the-shelf segmentation networks: A feasibility study with GammaPod planning.

Medical physics
BACKGROUND: Radiotherapy requires precise, patient-specific treatment planning to achieve high-quality dose distributions that improve patient outcomes. Traditional manual planning is time-consuming and clinically impractical for performing necessary...

The feasibility and cost-effectiveness of implementing mobile low-dose computed tomography with an AI-based diagnostic system in underserved populations.

BMC cancer
BACKGROUND: Low-dose computed tomography (LDCT) significantly increases early detection rates of lung cancer and reduces lung cancer-related mortality by 20%. However, many significant screening barriers remain. This study conduct an initial feasibil...

Estimating patient-specific organ doses from head and abdominal CT scans via machine learning with optimized regulation strength and feature quantity.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
PURPOSE: This study aims to investigate estimation of patient-specific organ doses from CT scans via radiomics feature-based SVR models with training parameter optimization, and maximize SVR models' predictive accuracy and robustness via fine-tuning ...

Asymmetric Convolution-based GAN Framework for Low-Dose CT Image Denoising.

Computers in biology and medicine
Noise reduction is essential to improve the diagnostic quality of low-dose CT (LDCT) images. In this regard, data-driven denoising methods based on generative adversarial networks (GAN) have shown promising results. However, custom designs with 2D co...

Deep learning techniques for proton dose prediction across multiple anatomical sites and variable beam configurations.

Physics in medicine and biology
To evaluate the impact of beam mask implementation and data aggregation on artificial intelligence-based dose prediction accuracy in proton therapy, with a focus on scenarios involving limited or highly heterogeneous datasets.In this study, 541 prost...

CDAF-Net: A Contextual Contrast Detail Attention Feature Fusion Network for Low-Dose CT Denoising.

IEEE journal of biomedical and health informatics
Low-dose computed tomography (LDCT) is a specialized CT scan with a lower radiation dose than normal-dose CT. However, the reduced radiation dose can introduce noise and artifacts, affecting diagnostic accuracy. To enhance the LDCT image quality, we ...

KBA-PDNet: A primal-dual unrolling network with kernel basis attention for low-dose CT reconstruction.

Journal of X-ray science and technology
Computed tomography (CT) image reconstruction is faced with challenge of balancing image quality and radiation dose. Recent unrolled optimization methods address low-dose CT image quality issues using convolutional neural networks or self-attention m...

Low-dose CT reconstruction using cross-domain deep learning with domain transfer module.

Physics in medicine and biology
. X-ray computed tomography employing low-dose x-ray source is actively researched to reduce radiation exposure. However, the reduced photon count in low-dose x-ray sources leads to severe noise artifacts in analytic reconstruction methods like filte...