AIMC Topic: Tomography, X-Ray Computed

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ADMM-based deep reconstruction for limited-angle CT.

Physics in medicine and biology
In the real applications of computed tomography (CT) imaging, the projection data of the scanned objects are usually acquired within a limited-angle range because of the limitation of the scanning condition. Under these circumstances, conventional an...

Natural Language Processing for Identification of Incidental Pulmonary Nodules in Radiology Reports.

Journal of the American College of Radiology : JACR
PURPOSE: To develop natural language processing (NLP) to identify incidental lung nodules (ILNs) in radiology reports for assessment of management recommendations.

IILS: Intelligent imaging layout system for automatic imaging report standardization and intra-interdisciplinary clinical workflow optimization.

EBioMedicine
BACKGROUND: To achieve imaging report standardization and improve the quality and efficiency of the intra-interdisciplinary clinical workflow, we proposed an intelligent imaging layout system (IILS) for a clinical decision support system-based ubiqui...

Preliminary study on the application of deep learning system to diagnosis of Sjögren's syndrome on CT images.

Dento maxillo facial radiology
OBJECTIVES: This study estimated the diagnostic performance of a deep learning system for detection of Sjögren's syndrome (SjS) on CT, and compared it with the performance of radiologists.

Learning-based automatic segmentation of arteriovenous malformations on contrast CT images in brain stereotactic radiosurgery.

Medical physics
PURPOSE: Stereotactic radiosurgery (SRS) is widely used to obliterate arteriovenous malformations (AVMs). Its performance relies on the accuracy of delineating the target AVM. Manual segmentation during a framed SRS procedure is time consuming and su...

End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography.

Nature medicine
With an estimated 160,000 deaths in 2018, lung cancer is the most common cause of cancer death in the United States. Lung cancer screening using low-dose computed tomography has been shown to reduce mortality by 20-43% and is now included in US scree...

Domain Progressive 3D Residual Convolution Network to Improve Low-Dose CT Imaging.

IEEE transactions on medical imaging
The wide applications of X-ray computed tomography (CT) bring low-dose CT (LDCT) into a clinical prerequisite, but reducing the radiation exposure in CT often leads to significantly increased noise and artifacts, which might lower the judgment accura...

Prediction of pathologic stage in non-small cell lung cancer using machine learning algorithm based on CT image feature analysis.

BMC cancer
PURPOSE: To explore imaging biomarkers that can be used for diagnosis and prediction of pathologic stage in non-small cell lung cancer (NSCLC) using multiple machine learning algorithms based on CT image feature analysis.

Artificial Neural Network Computer Tomography Perfusion Prediction of Ischemic Core.

Stroke
Background and Purpose- Computed tomography perfusion (CTP) is a useful tool in the evaluation of acute ischemic stroke, where it can provide an estimate of the ischemic core and the ischemic penumbra. The optimal CTP parameters to identify the ische...