AIMC Topic: Radiation Dosage

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Pulmonary nodule visualization and evaluation of AI-based detection at various ultra-low-dose levels using photon-counting detector CT.

Acta radiologica (Stockholm, Sweden : 1987)
BACKGROUND: Radiation dose should be as low as reasonably achievable. With the invention of photon-counting detector computed tomography (PCD-CT), the radiation dose may be considerably reduced.

A Novel Network for Low-Dose CT Denoising Based on Dual-Branch Structure and Multi-Scale Residual Attention.

Journal of imaging informatics in medicine
Deep learning-based denoising of low-dose medical CT images has received great attention both from academic researchers and physicians in recent years, and has shown important application value in clinical practice. In this work, a novel two-branch a...

Deep learning-based techniques for estimating high-quality full-dose positron emission tomography images from low-dose scans: a systematic review.

BMC medical imaging
This systematic review aimed to evaluate the potential of deep learning algorithms for converting low-dose Positron Emission Tomography (PET) images to full-dose PET images in different body regions. A total of 55 articles published between 2017 and ...

Low-dose computed tomography perceptual image quality assessment.

Medical image analysis
In computed tomography (CT) imaging, optimizing the balance between radiation dose and image quality is crucial due to the potentially harmful effects of radiation on patients. Although subjective assessments by radiologists are considered the gold s...

Unsupervised and Self-supervised Learning in Low-Dose Computed Tomography Denoising: Insights from Training Strategies.

Journal of imaging informatics in medicine
In recent years, X-ray low-dose computed tomography (LDCT) has garnered widespread attention due to its significant reduction in the risk of patient radiation exposure. However, LDCT images often contain a substantial amount of noises, adversely affe...

Artificial intelligence assisted automatic screening of opportunistic osteoporosis in computed tomography images from different scanners.

European radiology
OBJECTIVES: It is feasible to evaluate bone mineral density (BMD) and detect osteoporosis through an artificial intelligence (AI)-assisted system by using quantitative computed tomography (QCT) as a reference without additional radiation exposure or ...

Robotic MR-guided high dose rate brachytherapy needle implantation in the prostate (ROBiNSon)-a proof-of-concept study.

Physics in medicine and biology
A robotic needle implant device for MR-guided high-dose-rate (HDR) prostate brachytherapy was developed. This study aimed to assess the feasibility and spatial accuracy of HDR brachytherapy using the robotic device, for a single intraprostatic target...

Fast prediction of personalized abdominal organ doses from CT examinations by radiomics feature-based machine learning models.

Scientific reports
The X-rays emitted during CT scans can increase solid cancer risks by damaging DNA, with the risk tied to patient-specific organ doses. This study aims to establish a new method to predict patient specific abdominal organ doses from CT examinations u...

Large-scale pretrained frame generative model enables real-time low-dose DSA imaging: An AI system development and multi-center validation study.

Med (New York, N.Y.)
BACKGROUND: Digital subtraction angiography (DSA) devices are commonly used in numerous interventional procedures across various parts of the body, necessitating multiple scans per procedure, which results in significant radiation exposure for both d...