AI applications to medical images: From machine learning to deep learning
Purpose Artificial intelligence (AI) models are playing an increasing role in biomedical
research and healthcare services. This review focuses on challenges points to be clarified …
research and healthcare services. This review focuses on challenges points to be clarified …
Artificial intelligence and machine learning in cancer imaging
An increasing array of tools is being developed using artificial intelligence (AI) and machine
learning (ML) for cancer imaging. The development of an optimal tool requires …
learning (ML) for cancer imaging. The development of an optimal tool requires …
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 …
Criteria for the translation of radiomics into clinically useful tests
EP Huang, JPB O'Connor, LM McShane… - Nature reviews Clinical …, 2023 - nature.com
Computer-extracted tumour characteristics have been incorporated into medical imaging
computer-aided diagnosis (CAD) algorithms for decades. With the advent of radiomics, an …
computer-aided diagnosis (CAD) algorithms for decades. With the advent of radiomics, an …
A review in radiomics: making personalized medicine a reality via routine imaging
J Guiot, A Vaidyanathan, L Deprez… - Medicinal research …, 2022 - Wiley Online Library
Radiomics is the quantitative analysis of standard‐of‑care medical imaging; the information
obtained can be applied within clinical decision support systems to create diagnostic …
obtained can be applied within clinical decision support systems to create diagnostic …
Photon-counting x-ray detectors for CT
The introduction of photon-counting detectors is expected to be the next major breakthrough
in clinical x-ray computed tomography (CT). During the last decade, there has been …
in clinical x-ray computed tomography (CT). During the last decade, there has been …
The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping
Background Radiomic features may quantify characteristics present in medical imaging.
However, the lack of standardized definitions and validated reference values have …
However, the lack of standardized definitions and validated reference values have …
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 developing and …
purpose of radiomic analysis, ie, radiomics in a broad sense, is a rapidly developing and …
Radiogenomics in renal cancer management—current evidence and future prospects
M Ferro, G Musi, M Marchioni, M Maggi… - International journal of …, 2023 - mdpi.com
Renal cancer management is challenging from diagnosis to treatment and follow-up. In
cases of small renal masses and cystic lesions the differential diagnosis of benign or …
cases of small renal masses and cystic lesions the differential diagnosis of benign or …
Radiomics in breast cancer classification and prediction
Breast Cancer (BC) is the common form of cancer in women. Its diagnosis and screening are
usually performed through different imaging modalities such as mammography, magnetic …
usually performed through different imaging modalities such as mammography, magnetic …