Radiomics in medical imaging—“how-to” guide and critical reflection
JE Van Timmeren, D Cester, S Tanadini-Lang… - Insights into …, 2020 - Springer
Radiomics is a quantitative approach to medical imaging, which aims at enhancing the
existing data available to clinicians by means of advanced mathematical analysis. Through …
existing data available to clinicians by means of advanced mathematical analysis. Through …
Understanding sources of variation to improve the reproducibility of radiomics
B Zhao - Frontiers in oncology, 2021 - frontiersin.org
Radiomics is the method of choice for investigating the association between cancer imaging
phenotype, cancer genotype and clinical outcome prediction in the era of precision …
phenotype, cancer genotype and clinical outcome prediction in the era of precision …
Comprehensive investigation on controlling for CT imaging variabilities in radiomics studies
Radiomics has shown promise in improving models for predicting patient outcomes.
However, to maximize the information gain of the radiomics features, especially in larger …
However, to maximize the information gain of the radiomics features, especially in larger …
[HTML][HTML] The impact of the variation of imaging parameters on the robustness of Computed Tomography radiomic features: A review
The field of radiomics is at the forefront of personalized medicine. However, there is concern
that high variation in imaging parameters will impact robustness of radiomic features and …
that high variation in imaging parameters will impact robustness of radiomic features and …
CT-based radiomics for preoperative prediction of early recurrent hepatocellular carcinoma: Technical reproducibility of acquisition and scanners
Purpose To test the technical reproducibility of acquisition and scanners of CT image-based
radiomics model for early recurrent hepatocellular carcinoma (HCC). Methods We included …
radiomics model for early recurrent hepatocellular carcinoma (HCC). Methods We included …
[HTML][HTML] Learning from scanners: Bias reduction and feature correction in radiomics
Purpose Radiomics are quantitative features extracted from medical images. Many radiomic
features depend not only on tumor properties, but also on non-tumor related factors such as …
features depend not only on tumor properties, but also on non-tumor related factors such as …
Reinventing radiation therapy with machine learning and imaging bio-markers (radiomics): State-of-the-art, challenges and perspectives
Radiation therapy is a pivotal cancer treatment that has significantly progressed over the last
decade due to numerous technological breakthroughs. Imaging is now playing a critical role …
decade due to numerous technological breakthroughs. Imaging is now playing a critical role …
Sinogram-based deep learning image reconstruction technique in abdominal CT: image quality considerations
Objectives To investigate the image quality and perception of a sinogram-based deep
learning image reconstruction (DLIR) algorithm for single-energy abdominal CT compared …
learning image reconstruction (DLIR) algorithm for single-energy abdominal CT compared …
Review of the influence of noise in X-ray computed tomography measurement uncertainty
Á Rodríguez-Sánchez, A Thompson, L Körner… - Precision …, 2020 - Elsevier
Different aspects of noise in X-ray computed tomography (XCT) for industrial purposes are
examined. An overview of the most common noise metrics is given, together with a …
examined. An overview of the most common noise metrics is given, together with a …
Stable and discriminating radiomic predictor of recurrence in early stage non-small cell lung cancer: Multi-site study
Objectives To evaluate whether combining stability and discriminability criteria in building
radiomic classifiers will improve the prognosis of cancer recurrence in early stage non-small …
radiomic classifiers will improve the prognosis of cancer recurrence in early stage non-small …