Introduction to Radiomics
Marius E. Mayerhoefer,Marius E. Mayerhoefer,Andrzej Materka,Georg Langs,Ida Häggström,Piotr M. Szczypiński,Peter Gibbs,Gary Cook,Gary Cook +8 more
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TLDR
Radiomics is a rapidly evolving field of research concerned with the extraction of quantitative metrics-the so-called radiomic features-within medical images as discussed by the authors, which capture tissue and lesion characteristics such as heterogeneity and shape and may, alone or in combination with demographic, histologic, genomic, or proteomic data, be used for clinical problem solving.Abstract:
Radiomics is a rapidly evolving field of research concerned with the extraction of quantitative metrics-the so-called radiomic features-within medical images. Radiomic features capture tissue and lesion characteristics such as heterogeneity and shape and may, alone or in combination with demographic, histologic, genomic, or proteomic data, be used for clinical problem solving. The goal of this continuing education article is to provide an introduction to the field, covering the basic radiomics workflow: feature calculation and selection, dimensionality reduction, and data processing. Potential clinical applications in nuclear medicine that include PET radiomics-based prediction of treatment response and survival will be discussed. Current limitations of radiomics, such as sensitivity to acquisition parameter variations, and common pitfalls will also be covered.read more
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Radiomics in prostate cancer: an up-to-date review
Matteo Ferro,Ottavio De Cobelli,Gennaro Musi,Francesco Del Giudice,Giuseppe Carrieri,G. Busetto,Ugo Falagario,Alessandro Sciarra,Martina Maggi,Felice Crocetto,Biagio Barone,Vincenzo Caputo,Michele Marchioni,Giuseppe Lucarelli,Ciro Imbimbo,Francesco A. Mistretta,Stefano Luzzago,Mihai Dorin Vartolomei,Luigi Cormio,Riccardo Autorino,Octavian Sabin Tătaru +20 more
TL;DR: An overview on the current evidence of methodology and the available literature on radiomics in PCa patients is reviewed, highlighting its potential for personalized treatment and future applications.
Journal ArticleDOI
Pre-Treatment T2-WI Based Radiomics Features for Prediction of Locally Advanced Rectal Cancer Non-Response to Neoadjuvant Chemoradiotherapy: A Preliminary Study.
Bianca Petresc,Andrei Lebovici,Cosmin Caraiani,Diana Feier,Florin Graur,Mircea Marian Buruian +5 more
TL;DR: The results indicate that MRI radiomics features could be considered as potential imaging biomarkers for early prediction of LARC non-response to neoadjuvant treatment.
Journal ArticleDOI
Application of radiomics and machine learning in head and neck cancers.
TL;DR: In this paper, the authors introduce the concepts and workflow of radiomics and machine learning and their current applications in head and neck cancers, as well as the directions and applications of artificial intelligence in the treatment and diagnosis of HNC.
Journal ArticleDOI
A Novel Machine Learning-derived Radiomic Signature of the Whole Lung Differentiates Stable From Progressive COVID-19 Infection: A Retrospective Cohort Study.
TL;DR: The radiomics signature of the whole lung based on machine learning may reveal the changes of lung microstructure in the early stage and help to indicate the progression of the disease.
Journal ArticleDOI
The Role of Artificial Intelligence in Early Cancer Diagnosis
TL;DR: In this paper , an overview of the main artificial intelligence approaches, including historical models such as logistic regression, as well as deep learning and neural networks, and highlight their early diagnosis applications.
References
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TL;DR: This report describes the process of radiomics, its challenges, and its potential power to facilitate better clinical decision making, particularly in the care of patients with cancer.
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