Radiomics: from qualitative to quantitative imaging
W Rogers, S Thulasi Seetha… - The British journal of …, 2020 - academic.oup.com
Historically, medical imaging has been a qualitative or semi-quantitative modality. It is
difficult to quantify what can be seen in an image, and to turn it into valuable predictive …
difficult to quantify what can be seen in an image, and to turn it into valuable predictive …
Artificial intelligence, machine (deep) learning and radio (geno) mics: definitions and nuclear medicine imaging applications
D Visvikis, C Cheze Le Rest, V Jaouen… - European journal of …, 2019 - Springer
Techniques from the field of artificial intelligence, and more specifically machine (deep)
learning methods, have been core components of most recent developments in the field of …
learning methods, have been core components of most recent developments in the field of …
Deep learning in head & neck cancer outcome prediction
Traditional radiomics involves the extraction of quantitative texture features from medical
images in an attempt to determine correlations with clinical endpoints. We hypothesize that …
images in an attempt to determine correlations with clinical endpoints. We hypothesize that …
[HTML][HTML] Radiomics and artificial intelligence for biomarker and prediction model development in oncology
Advanced cross-sectional and functional imaging techniques enable non-invasive
visualization of tumor extent and functional metabolic activity and play a central role in the …
visualization of tumor extent and functional metabolic activity and play a central role in the …
Radiomics of liver metastases: a systematic review
Simple Summary Patients with liver metastases can be scheduled for different therapies (eg,
chemotherapy, surgery, radiotherapy, and ablation). The choice of the most appropriate …
chemotherapy, surgery, radiotherapy, and ablation). The choice of the most appropriate …
Integrated models incorporating radiologic and radiomic features predict meningioma grade, local failure, and overall survival
Background We investigated prognostic models based on clinical, radiologic, and radiomic
feature to preoperatively identify meningiomas at risk for poor outcomes. Methods …
feature to preoperatively identify meningiomas at risk for poor outcomes. Methods …
External validation of an MRI-derived radiomics model to predict biochemical recurrence after surgery for high-risk prostate cancer
Adjuvant radiotherapy after prostatectomy was recently challenged by early salvage
radiotherapy, which highlighted the need for biomarkers to improve risk stratification …
radiotherapy, which highlighted the need for biomarkers to improve risk stratification …
Artificial intelligence and the medical physicist: welcome to the machine
Artificial intelligence (AI) is a branch of computer science dedicated to giving machines or
computers the ability to perform human-like cognitive functions, such as learning, problem …
computers the ability to perform human-like cognitive functions, such as learning, problem …
Radiomics and dosiomics for predicting local control after carbon-ion radiotherapy in skull-base chordoma
G Buizza, C Paganelli, E D'Ippolito, G Fontana… - Cancers, 2021 - mdpi.com
Simple Summary Skull-base chordomas (SBC) are rare tumours with unfavourable
outcomes, even when undergoing advanced treatments such as carbon-ion radiotherapy …
outcomes, even when undergoing advanced treatments such as carbon-ion radiotherapy …
Fused feature signatures to probe tumour radiogenomics relationships
Radiogenomics relationships (RRs) aims to identify statistically significant correlations
between medical image features and molecular characteristics from analysing tissue …
between medical image features and molecular characteristics from analysing tissue …