Deep learning with radiomics for disease diagnosis and treatment: challenges and potential
The high-throughput extraction of quantitative imaging features from medical images for the
purpose of radiomic analysis, ie, radiomics in a broad sense, is a rapidly develo** and …
purpose of radiomic analysis, ie, radiomics in a broad sense, is a rapidly develo** and …
Radiomics in nuclear medicine: robustness, reproducibility, standardization, and how to avoid data analysis traps and replication crisis
A Zwanenburg - European journal of nuclear medicine and molecular …, 2019 - Springer
Radiomics in nuclear medicine is rapidly expanding. Reproducibility of radiomics studies in
multicentre settings is an important criterion for clinical translation. We therefore performed a …
multicentre settings is an important criterion for clinical translation. We therefore performed a …
[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 …
Artificial intelligence and radiomics in evaluation of kidney lesions: a comprehensive literature review
M Ferro, F Crocetto, B Barone… - Therapeutic …, 2023 - journals.sagepub.com
Radiomics and artificial intelligence (AI) may increase the differentiation of benign from
malignant kidney lesions, differentiation of angiomyolipoma (AML) from renal cell carcinoma …
malignant kidney lesions, differentiation of angiomyolipoma (AML) from renal cell carcinoma …
Harmonization strategies for multicenter radiomics investigations
Carrying out large multicenter studies is one of the key goals to be achieved towards a faster
transfer of the radiomics approach in the clinical setting. This requires large-scale radiomics …
transfer of the radiomics approach in the clinical setting. This requires large-scale radiomics …
Performance comparison of modified ComBat for harmonization of radiomic features for multicenter studies
Multicenter studies are needed to demonstrate the clinical potential value of radiomics as a
prognostic tool. However, variability in scanner models, acquisition protocols and …
prognostic tool. However, variability in scanner models, acquisition protocols and …
External validation of a combined PET and MRI radiomics model for prediction of recurrence in cervical cancer patients treated with chemoradiotherapy
Purpose The aim of this study was to validate previously developed radiomics models
relying on just two radiomics features from 18 F-fluorodeoxyglucose positron emission …
relying on just two radiomics features from 18 F-fluorodeoxyglucose positron emission …
Machine (deep) learning methods for image processing and radiomics
Methods from the field of machine (deep) learning have been successful in tackling a
number of tasks in medical imaging, from image reconstruction or processing to predictive …
number of tasks in medical imaging, from image reconstruction or processing to predictive …
[HTML][HTML] Radiomics in prostate cancer imaging for a personalized treatment approach-current aspects of methodology and a systematic review on validated studies
SKB Spohn, AS Bettermann, F Bamberg… - Theranostics, 2021 - ncbi.nlm.nih.gov
Prostate cancer (PCa) is one of the most frequently diagnosed malignancies of men in the
world. Due to a variety of treatment options in different risk groups, proper diagnostic and …
world. Due to a variety of treatment options in different risk groups, proper diagnostic and …
Radiomics: data are also images
The aim of this review is to provide readers with an update on the state of the art, pitfalls,
solutions for those pitfalls, future perspectives, and challenges in the quickly evolving field of …
solutions for those pitfalls, future perspectives, and challenges in the quickly evolving field of …