Radiomics: a new application from established techniques
The increasing use of biomarkers in cancer have led to the concept of personalized
medicine for patients. Personalized medicine provides better diagnosis and treatment …
medicine for patients. Personalized medicine provides better diagnosis and treatment …
Radiomics in breast MRI: Current progress toward clinical application in the era of artificial intelligence
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 …
Rectal cancer: assessment of neoadjuvant chemoradiation outcome based on radiomics of multiparametric MRI
K Nie, L Shi, Q Chen, X Hu, SK Jabbour, N Yue… - Clinical cancer …, 2016 - AACR
Purpose: To evaluate multiparametric MRI features in predicting pathologic response after
preoperative chemoradiation therapy (CRT) for locally advanced rectal cancer (LARC) …
preoperative chemoradiation therapy (CRT) for locally advanced rectal cancer (LARC) …
Automated critical test findings identification and online notification system using artificial intelligence in imaging
Purpose To evaluate the performance of an artificial intelligence (AI) tool using a deep
learning algorithm for detecting hemorrhage, mass effect, or hydrocephalus (HMH) at non …
learning algorithm for detecting hemorrhage, mass effect, or hydrocephalus (HMH) at non …
Machine learning in breast MRI
Machine‐learning techniques have led to remarkable advances in data extraction and
analysis of medical imaging. Applications of machine learning to breast MRI continue to …
analysis of medical imaging. Applications of machine learning to breast MRI continue to …
Integrated radiomic framework for breast cancer and tumor biology using advanced machine learning and multiparametric MRI
Radiomics deals with the high throughput extraction of quantitative textural information from
radiological images that not visually perceivable by radiologists. However, the biological …
radiological images that not visually perceivable by radiologists. However, the biological …
[HTML][HTML] Radiomics in breast imaging from techniques to clinical applications: a review
Recent advances in computer technology have generated a new area of research known as
radiomics. Radiomics is defined as the high throughput extraction and analysis of …
radiomics. Radiomics is defined as the high throughput extraction and analysis of …
Deep learning radiomics model of dynamic contrast‐enhanced MRI for evaluating vessels encapsulating tumor clusters and prognosis in hepatocellular carcinoma
X Dong, J Yang, B Zhang, Y Li, G Wang… - Journal of Magnetic …, 2024 - Wiley Online Library
Background Vessels encapsulating tumor cluster (VETC) is a critical prognostic factor and
therapeutic predictor of hepatocellular carcinoma (HCC). However, noninvasive evaluation …
therapeutic predictor of hepatocellular carcinoma (HCC). However, noninvasive evaluation …
Quantification of heterogeneity as a biomarker in tumor imaging: a systematic review
Background Many techniques are proposed for the quantification of tumor heterogeneity as
an imaging biomarker for differentiation between tumor types, tumor grading, response …
an imaging biomarker for differentiation between tumor types, tumor grading, response …
Breast cancer molecular subtype classifier that incorporates MRI features
EJ Sutton, BZ Dashevsky, JH Oh… - Journal of Magnetic …, 2016 - Wiley Online Library
Purpose To use features extracted from magnetic resonance (MR) images and a machine‐
learning method to assist in differentiating breast cancer molecular subtypes. Materials and …
learning method to assist in differentiating breast cancer molecular subtypes. Materials and …