AIMC Topic: X-Rays

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Machine learning-based modeling of the anode heel effect in x-ray Beam Monte Carlo simulations.

Physics in medicine and biology
To develop a machine learning-based framework for accurately modeling the anode heel effect in Monte Carlo(MC) simulations of x-ray imaging systems, enabling realistic beam intensity profiles with minimal experimental calibration.Multiple regression ...

Fast operating room scattered radiation calculation in x-ray guided interventions by using deep learning.

Journal of radiological protection : official journal of the Society for Radiological Protection
Protecting medical personnel from the harmful effects of scattered ionising radiation during x-ray-guided procedures is a critical concern. Due to the complex and invisible nature of x-rays, monitoring radiation exposure has been challenging. Existin...

Deep‑learning based osteoporosis classification in knee X‑rays using transfer‑learning approach.

Scientific reports
Bone deterioration from osteoporosis creates fractures that primarily affect females who have reached menopause and older adults. Early detection of osteoporosis requires affordable methods because current diagnostic systems are both expensive and ch...

TomoGRAF: An X-ray physics-driven generative radiance field framework for extremely sparse view CT reconstruction.

PloS one
OBJECTIVES: Computed tomography (CT) provides high spatial-resolution visualization of 3D structures for various applications. Traditional analytical/iterative CT reconstruction algorithms require hundreds of angular samplings, a condition may not be...

Novel transfer learning based bone fracture detection using radiographic images.

BMC medical imaging
A bone fracture is a medical condition characterized by a partial or complete break in the continuity of the bone. Fractures are primarily caused by injuries and accidents, affecting millions of people worldwide. The healing process for a fracture ca...

X-ray irradiation as a potential postharvest treatment for maintaining the quality of lily (Lilium davidii var. unicolor) bulbs and predicting shelf life using an artificial neural network.

Food research international (Ottawa, Ont.)
This study aimed to investigate the impact of X-ray irradiation pretreatment at varying doses (0.5, 1.0, 1.5, 2.0 kGy) on the preservation quality of lily bulbs and to elucidate its potential regulatory mechanisms. The findings revealed that X-ray ir...

Tunable and real-time automatic interventional x-ray collimation from semi-supervised deep feature extraction.

Medical physics
BACKGROUND: The use of endovascular procedures is becoming increasingly popular across multiple clinical domains. These procedures are generally performed under image guidance using an interventional c-arm x-ray system. Radiation exposure to both pat...

Comparative efficacy of anteroposterior and lateral X-ray based deep learning in the detection of osteoporotic vertebral compression fracture.

Scientific reports
Magnetic resonance imaging remains the gold standard for diagnosing osteoporotic vertebral compression fractures (OVCF), but the use of X-ray imaging, particularly anteroposterior (AP) and lateral views, is prevalent due to its accessibility and cost...

Convolutional neural network-based classification of craniosynostosis and suture lines from multi-view cranial X-rays.

Scientific reports
Early and precise diagnosis of craniosynostosis (CSO), which involves premature fusion of cranial sutures in infants, is crucial for effective treatment. Although computed topography offers detailed imaging, its high radiation poses risks, especially...

Deep Learning-Based Estimation of Radiographic Position to Automatically Set Up the X-Ray Prime Factors.

Journal of imaging informatics in medicine
Radiation dose and image quality in radiology are influenced by the X-ray prime factors: KVp, mAs, and source-detector distance. These parameters are set by the X-ray technician prior to the acquisition considering the radiographic position. A wrong ...