x-ray computed tomography

Minimizing acquisition-related radiomics variability by image resampling and batch effect correction to allow for large-scale data analysis

Medical imaging encodes information of underlying tissues and can provide a comprehensive view of the entire body repeatedly throughout the course of disease....

Raquel Perez-Lopez

1 week ago

Minimizing acquisition-related radiomics variability by image resampling and batch effect correction to allow for large-scale data analysis

Radiomics in predicting treatment response in non-small-cell lung cancer: current status, challenges and future perspectives

This literature review summarizes the current status and evaluates the scientific reporting quality of radiomics research in the prediction of treatment...

European Radiology

2 months ago

Radiomics in predicting treatment response in non-small-cell lung cancer: current status, challenges and future perspectives

Motion-corrected coronary calcium scores by a CNN: a robotic simulating study

The authors of this study aimed to classify motion-induced blurred images of calcified coronary plaques, in order to correct coronary calcium scored on...

European Radiology

1 year ago

Motion-corrected coronary calcium scores by a CNN: a robotic simulating study

Deep learning to convert unstructured CT pulmonary angiography reports into structured reports

We believe that the possibilities for artificial intelligence (AI) over the coming years will be limited only by our imagination. While there is a tremendous...

John Nance

1 year ago

Deep learning to convert unstructured CT pulmonary angiography reports into structured reports

Radiomic feature reproducibility in contrast-enhanced CT of the pancreas is affected by variabilities in scan parameters and manual segmentation

The goal of this study was to measure the reproducibility of radiomic features in pancreatic parenchyma and ductal adenocarcinomas in patients who underwent...

Richard Do

1 year ago

x-ray computed tomography

Minimizing acquisition-related radiomics variability by image resampling and batch effect correction to allow for large-scale data analysis

Radiomics in predicting treatment response in non-small-cell lung cancer: current status, challenges and future perspectives

Motion-corrected coronary calcium scores by a CNN: a robotic simulating study

Deep learning to convert unstructured CT pulmonary angiography reports into structured reports

Radiomic feature reproducibility in contrast-enhanced CT of the pancreas is affected by variabilities in scan parameters and manual segmentation

Welcome to the blog on Artificial Intelligence of the European Society of Radiology

Latest posts

Minimizing acquisition-related radiomics variability by image resampling and batch effect correction to allow for large-scale data analysis

Radiomics in predicting treatment response in non-small-cell lung cancer: current status, challenges and future perspectives

Motion-corrected coronary calcium scores by a CNN: a robotic simulating study

Deep learning to convert unstructured CT pulmonary angiography reports into structured reports

Radiomic feature reproducibility in contrast-enhanced CT of the pancreas is affected by variabilities in scan parameters and manual segmentation

Welcome to the blog on Artificial Intelligence of the European Society of Radiology

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