Current applications and future impact of machine learning in radiology
Recent advances and future perspectives of machine learning techniques offer promising
applications in medical imaging. Machine learning has the potential to improve different …
applications in medical imaging. Machine learning has the potential to improve different …
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 …
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 …
From handcrafted to deep-learning-based cancer radiomics: challenges and opportunities
Recent advancements in signal processing (SP) and machine learning, coupled with
electronic medical record keeping in hospitals and the availability of extensive sets of …
electronic medical record keeping in hospitals and the availability of extensive sets of …
Radiomic versus convolutional neural networks analysis for classification of contrast-enhancing lesions at multiparametric breast MRI
Purpose To compare the diagnostic performance of radiomic analysis (RA) and a
convolutional neural network (CNN) to radiologists for classification of contrast agent …
convolutional neural network (CNN) to radiologists for classification of contrast agent …
[HTML][HTML] Overview of radiomics in breast cancer diagnosis and prognostication
Diagnosis of early invasive breast cancer relies on radiology and clinical evaluation,
supplemented by biopsy confirmation. At least three issues burden this approach: a) …
supplemented by biopsy confirmation. At least three issues burden this approach: a) …
Rapid review: radiomics and breast cancer
F Valdora, N Houssami, F Rossi, M Calabrese… - Breast cancer research …, 2018 - Springer
Purpose To perform a rapid review of the recent literature on radiomics and breast cancer
(BC). Methods A rapid review, a streamlined approach to systematically identify and …
(BC). Methods A rapid review, a streamlined approach to systematically identify and …
[HTML][HTML] Tracking tumor biology with radiomics: a systematic review utilizing a radiomics quality score
S Sanduleanu, HC Woodruff, EEC De Jong… - Radiotherapy and …, 2018 - Elsevier
Introduction: In this review we describe recent developments in the field of radiomics along
with current relevant literature linking it to tumor biology. We furthermore explore the …
with current relevant literature linking it to tumor biology. We furthermore explore the …
Radiomics in breast MRI: Current progress toward clinical application in the era of artificial intelligence
H Satake, S Ishigaki, R Ito, S Naganawa - La radiologia medica, 2022 - Springer
Breast magnetic resonance imaging (MRI) is the most sensitive imaging modality for breast
cancer diagnosis and is widely used clinically. Dynamic contrast-enhanced MRI is the basis …
cancer diagnosis and is widely used clinically. Dynamic contrast-enhanced MRI is the basis …
Preoperative prediction of sentinel lymph node metastasis in breast cancer by radiomic signatures from dynamic contrast‐enhanced MRI
Background Sentinel lymph node (SLN) status is an important prognostic factor for patients
with breast cancer, which is currently determined in clinical practice by invasive SLN biopsy …
with breast cancer, which is currently determined in clinical practice by invasive SLN biopsy …