AIMC Topic: Radiation Exposure

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CycleGAN for interpretable online EMT compensation.

International journal of computer assisted radiology and surgery
PURPOSE: Electromagnetic tracking (EMT) can partially replace X-ray guidance in minimally invasive procedures, reducing radiation in the OR. However, in this hybrid setting, EMT is disturbed by metallic distortion caused by the X-ray device. We plan ...

Artificial intelligence enables whole-body positron emission tomography scans with minimal radiation exposure.

European journal of nuclear medicine and molecular imaging
PURPOSE: To generate diagnostic F-FDG PET images of pediatric cancer patients from ultra-low-dose F-FDG PET input images, using a novel artificial intelligence (AI) algorithm.

Robot-assisted S2 screw fixation for posterior pelvic ring injury.

Injury
BACKGROUND: Percutaneous sacroiliac screw is one of the main methods to treat unstable posterior pelvic ring injury. However, complexity of pelvic anatomical structure increases the difficulty and risk with freehand operation. Besides, S2 screw fixat...

Leveraging spatial uncertainty for online error compensation in EMT.

International journal of computer assisted radiology and surgery
PURPOSE: Electromagnetic tracking (EMT) can potentially complement fluoroscopic navigation, reducing radiation exposure in a hybrid setting. Due to the susceptibility to external distortions, systematic error in EMT needs to be compensated algorithmi...

Precise pulmonary scanning and reducing medical radiation exposure by developing a clinically applicable intelligent CT system: Toward improving patient care.

EBioMedicine
BACKGROUND: Interstitial lung disease requires frequent re-examination, which directly causes excessive cumulative radiation exposure. To date, AI has not been applied to CT for enhancing clinical care; thus, we hypothesize AI may empower CT with int...

Overlooked pitfalls in multi-class machine learning classification in radiation oncology and how to avoid them.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
In radiation oncology, Machine Learning classification publications are typically related to two outcome classes, e.g. the presence or absence of distant metastasis. However, multi-class classification problems also have great clinical relevance, e.g...

Cath Lab Robotics: Paradigm Change in Interventional Cardiology?

Current cardiology reports
PURPOSE OF REVIEW: To review the contemporary evidence for robotic-assisted percutaneous coronary and vascular interventions, discussing its current capabilities, limitations, and potential future applications.

Imaging Quality Control in the Era of Artificial Intelligence.

Journal of the American College of Radiology : JACR
The advent of artificial intelligence (AI) promises to have a transformational impact on quality in medicine, including in radiology. However, experience has shown that quality tools alone are often not sufficient to bring about consistent excellent ...

Development of a deep neural network for generating synthetic dual-energy chest x-ray images with single x-ray exposure.

Physics in medicine and biology
Dual-energy chest radiography (DECR) is a medical imaging technology that can improve diagnostic accuracy. This technique can decompose single-energy chest radiography (SECR) images into separate bone- and soft tissue-only images. This can, however, ...

Reduction of operator radiation exposure using a passive robotic device during fluoroscopy-guided arterial puncture: an experimental study in a swine model.

European radiology experimental
BACKGROUND: Vascular interventions imply radiation exposure to the operating physician (OP). To reduce radiation exposure, we propose a novel passive robotic device for fluoroscopy-guided arterial puncturing.