Machine and deep learning methods for radiomics
Radiomics is an emerging area in quantitative image analysis that aims to relate large‐scale
extracted imaging information to clinical and biological endpoints. The development of …
extracted imaging information to clinical and biological endpoints. The development of …
[HTML][HTML] Radiomics with artificial intelligence: a practical guide for beginners
Radiomics is a relatively new word for the field of radiology, meaning the extraction of a high
number of quantitative features from medical images. Artificial intelligence (AI) is broadly a …
number of quantitative features from medical images. Artificial intelligence (AI) is broadly a …
Beyond imaging: the promise of radiomics
The domain of investigation of radiomics consists of large-scale radiological image analysis
and association with biological or clinical endpoints. The purpose of the present study is to …
and association with biological or clinical endpoints. The purpose of the present study is to …
[HTML][HTML] Artificial intelligence: Deep learning in oncological radiomics and challenges of interpretability and data harmonization
Over the last decade there has been an extensive evolution in the Artificial Intelligence (AI)
field. Modern radiation oncology is based on the exploitation of advanced computational …
field. Modern radiation oncology is based on the exploitation of advanced computational …
Quantitative radiomics studies for tissue characterization: a review of technology and methodological procedures
RTHM Larue, G Defraene… - The British journal of …, 2017 - academic.oup.com
Quantitative analysis of tumour characteristics based on medical imaging is an emerging
field of research. In recent years, quantitative imaging features derived from CT, positron …
field of research. In recent years, quantitative imaging features derived from CT, positron …
Reliability and prognostic value of radiomic features are highly dependent on choice of feature extraction platform
I Fornacon-Wood, H Mistry, CJ Ackermann… - European …, 2020 - Springer
Objective To investigate the effects of Image Biomarker Standardisation Initiative (IBSI)
compliance, harmonisation of calculation settings and platform version on the statistical …
compliance, harmonisation of calculation settings and platform version on the statistical …
Precision medicine and radiogenomics in breast cancer: new approaches toward diagnosis and treatment
Precision medicine is medicine optimized to the genotypic and phenotypic characteristics of
an individual and, when present, his or her disease. It has a host of targets, including genes …
an individual and, when present, his or her disease. It has a host of targets, including genes …
ibex: An open infrastructure software platform to facilitate collaborative work in radiomics
Purpose: Radiomics, which is the high‐throughput extraction and analysis of quantitative
image features, has been shown to have considerable potential to quantify the tumor …
image features, has been shown to have considerable potential to quantify the tumor …
Radiomics in neuro-oncology: Basics, workflow, and applications
P Lohmann, N Galldiks, M Kocher, A Heinzel, CP Filss… - Methods, 2021 - Elsevier
Over the last years, the amount, variety, and complexity of neuroimaging data acquired in
patients with brain tumors for routine clinical purposes and the resulting number of imaging …
patients with brain tumors for routine clinical purposes and the resulting number of imaging …
Clear cell renal cell carcinoma: machine learning-based quantitative computed tomography texture analysis for prediction of fuhrman nuclear grade
CT Bektas, B Kocak, AH Yardimci, MH Turkcanoglu… - European …, 2019 - Springer
Objective To evaluate the performance of quantitative computed tomography (CT) texture
analysis using different machine learning (ML) classifiers for discriminating low and high …
analysis using different machine learning (ML) classifiers for discriminating low and high …