x-ray computed tomography

Evaluating the impact of a novel denoising algorithm on image quality in dual-energy abdominal CT of obese patients

In the ever-evolving landscape of radiology, the quest for enhanced image quality and reduced noise, particularly in obese patients, remains an enduring...

Fides Regina Schwartz

4 days ago

Evaluation of techniques to improve a deep learning algorithm for the automatic detection of intracranial haemorrhage on CT head imaging

This study evaluates deep learning (DL) algorithms that are playing an increasingly important role in automatic medical image analysis. The DL algorithm used...

European Radiology Experimental

3 weeks ago

Evaluating a deep learning software for lung parenchyma characterization in COVID-19 pneumonia

The aim of this study was to evaluate the performance of the LungQuant system, which is a deep learning-based software for quantitative analysis of chest CT....

European Radiology Experimental

1 month ago

Robustness of pulmonary nodule radiomic features on CT as a function of varying radiation dose levels

The aim of this study was to present an in vivo stability analysis of radiomic features for pulmonary nodules against varying radiation dose levels. The...

European Radiology

1 month ago

Enhanced CT-based radiomics predicts pathological complete response for advanced adenocarcinoma

This study shows that the combination of CT imaging and clinical factors pre-neoadjuvant chemotherapy (NAC) for advanced adenocarcinoma of the esophagogastric...

Insights into Imaging

5 months ago

Using parametric feature maps to enhance the stability of CT radiomics

It is known that the reproducibility of radiomic features is influenced by myriad factors, one of which is the size of the segmented volume. We hypothesized...

Laura Jensen

9 months ago

The role of radiomics in the detection of lymph node metastases

The authors of this retrospective analysis looked at the role that radiomics played when applied to contrast-enhanced computed tomography (CT) in detecting...

European Radiology Experimental

9 months ago

The potential of texture analysis for breast density classification

Breast cancer continues to be the most commonly diagnosed cancer among women with over 2 million new cases per year worldwide. One important independent risk...

European Radiology Experimental

1 year ago

Can radiomics signatures predict tumor reponse of patients treated with chemotherapy and targeted therapy?

The authors of this retrospective study had the goal of evaluating the effectiveness of radiomics signatures in order to predict the tumor response of...

European Radiology

1 year ago

Can machine learning predict the WHO/ISUP nuclear grade of clear cell renal cell carcinomas?

In this retrospective study, the authors investigated if radiomics features extracted from nephrographic-phase (NP) CT images combined with...

Insights into Imaging

1 year ago