AIMC Topic: Fluoroscopy

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Toward automatic C-arm positioning for standard projections in orthopedic surgery.

International journal of computer assisted radiology and surgery
PURPOSE: Guidance and quality control in orthopedic surgery increasingly rely on intra-operative fluoroscopy using a mobile C-arm. The accurate acquisition of standardized and anatomy-specific projections is essential in this process. The correspondi...

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...

A machine learning-based real-time tumor tracking system for fluoroscopic gating of lung radiotherapy.

Physics in medicine and biology
To improve respiratory-gated radiotherapy accuracy, we developed a machine learning approach for markerless tumor tracking and evaluated it using lung cancer patient data. Digitally reconstructed radiography (DRR) datasets were generated using planni...

Catheter segmentation in X-ray fluoroscopy using synthetic data and transfer learning with light U-nets.

Computer methods and programs in biomedicine
Background and objectivesAutomated segmentation and tracking of surgical instruments and catheters under X-ray fluoroscopy hold the potential for enhanced image guidance in catheter-based endovascular procedures. This article presents a novel method ...

Real-time markerless tumour tracking with patient-specific deep learning using a personalised data generation strategy: proof of concept by phantom study.

The British journal of radiology
OBJECTIVE: For real-time markerless tumour tracking in stereotactic lung radiotherapy, we propose a different approach which uses patient-specific deep learning (DL) using a personalised data generation strategy, avoiding the need for collection of a...

Dynamic coronary roadmapping via catheter tip tracking in X-ray fluoroscopy with deep learning based Bayesian filtering.

Medical image analysis
Percutaneous coronary intervention (PCI) is typically performed with image guidance using X-ray angiograms in which coronary arteries are opacified with X-ray opaque contrast agents. Interventional cardiologists typically navigate instruments using n...

Adaptive weighted log subtraction based on neural networks for markerless tumor tracking using dual-energy fluoroscopy.

Medical physics
PURPOSE: To present a novel method, based on convolutional neural networks (CNN), to automate weighted log subtraction (WLS) for dual-energy (DE) fluoroscopy to be used in conjunction with markerless tumor tracking (MTT).

Physics-driven learning of x-ray skin dose distribution in interventional procedures.

Medical physics
PURPOSE: Radiation doses accumulated during very complicated image-guided x-ray procedures have the potential to cause stochastic, but also deterministic effects, such as skin rashes or even hair loss. To monitor and reduce radiation-related risks to...

Enabling machine learning in X-ray-based procedures via realistic simulation of image formation.

International journal of computer assisted radiology and surgery
PURPOSE: Machine learning-based approaches now outperform competing methods in most disciplines relevant to diagnostic radiology. Image-guided procedures, however, have not yet benefited substantially from the advent of deep learning, in particular b...