Radiomics: the facts and the challenges of image analysis
S Rizzo, F Botta, S Raimondi, D Origgi… - European radiology …, 2018 - Springer
Radiomics is an emerging translational field of research aiming to extract mineable high-
dimensional data from clinical images. The radiomic process can be divided into distinct …
dimensional data from clinical images. The radiomic process can be divided into distinct …
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 and deep learning in lung cancer
Lung malignancies have been extensively characterized through radiomics and deep
learning. By providing a three-dimensional characterization of the lesion, models based on …
learning. By providing a three-dimensional characterization of the lesion, models based on …
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 …
Histologic subtype classification of non-small cell lung cancer using PET/CT images
Y Han, Y Ma, Z Wu, F Zhang, D Zheng, X Liu… - European journal of …, 2021 - Springer
Purposes To evaluate the capability of PET/CT images for differentiating the histologic
subtypes of non-small cell lung cancer (NSCLC) and to identify the optimal model from …
subtypes of non-small cell lung cancer (NSCLC) and to identify the optimal model from …
MR imaging of rectal cancer: radiomics analysis to assess treatment response after neoadjuvant therapy
N Horvat, H Veeraraghavan, M Khan, I Blazic, J Zheng… - Radiology, 2018 - pubs.rsna.org
Purpose To investigate the value of T2-weighted–based radiomics compared with
qualitative assessment at T2-weighted imaging and diffusion-weighted (DW) imaging for …
qualitative assessment at T2-weighted imaging and diffusion-weighted (DW) imaging for …
Radiogenomics: bridging imaging and genomics
From diagnostics to prognosis to response prediction, new applications for radiomics are
rapidly being developed. One of the fastest evolving branches involves linking imaging …
rapidly being developed. One of the fastest evolving branches involves linking imaging …
[HTML][HTML] Radiomics and artificial intelligence for precision medicine in lung cancer treatment
Lung cancer is the leading cause of cancer-related deaths worldwide. It exhibits, at the
mesoscopic scale, phenotypic characteristics that are generally indiscernible to the human …
mesoscopic scale, phenotypic characteristics that are generally indiscernible to the human …
Radiomics for survival risk stratification of clinical and pathologic stage IA pure-solid non–small cell lung cancer
Background Radiomics-based biomarkers enable the prognostication of resected non–small
cell lung cancer (NSCLC), but their effectiveness in clinical stage and pathologic stage IA …
cell lung cancer (NSCLC), but their effectiveness in clinical stage and pathologic stage IA …
Clinical applications of artificial intelligence and radiomics in neuro-oncology imaging
This article is a comprehensive review of the basic background, technique, and clinical
applications of artificial intelligence (AI) and radiomics in the field of neuro-oncology. A …
applications of artificial intelligence (AI) and radiomics in the field of neuro-oncology. A …