A deep look into radiomics

C Scapicchio, M Gabelloni, A Barucci, D Cioni… - La radiologia …, 2021 - Springer
Radiomics is a process that allows the extraction and analysis of quantitative data from
medical images. It is an evolving field of research with many potential applications in …

[HTML][HTML] Promises and challenges for the implementation of computational medical imaging (radiomics) in oncology

EJ Limkin, R Sun, L Dercle, EI Zacharaki, C Robert… - Annals of …, 2017 - Elsevier
Medical image processing and analysis (also known as Radiomics) is a rapidly growing
discipline that maps digital medical images into quantitative data, with the end goal of …

Radiomic analysis of contrast-enhanced CT predicts microvascular invasion and outcome in hepatocellular carcinoma

X Xu, HL Zhang, QP Liu, SW Sun, J Zhang, FP Zhu… - Journal of …, 2019 - Elsevier
Background & Aims Microvascular invasion (MVI) impairs surgical outcomes in patients with
hepatocellular carcinoma (HCC). As there is no single highly reliable factor to preoperatively …

Radiomics: images are more than pictures, they are data

RJ Gillies, PE Kinahan, H Hricak - Radiology, 2016 - pubs.rsna.org
In the past decade, the field of medical image analysis has grown exponentially, with an
increased number of pattern recognition tools and an increase in data set sizes. These …

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 …

Prostate cancer detection using deep convolutional neural networks

S Yoo, I Gujrathi, MA Haider, F Khalvati - Scientific reports, 2019 - nature.com
Prostate cancer is one of the most common forms of cancer and the third leading cause of
cancer death in North America. As an integrated part of computer-aided detection (CAD) …

Radiomic profiling of glioblastoma: identifying an imaging predictor of patient survival with improved performance over established clinical and radiologic risk models

P Kickingereder, S Burth, A Wick, M Götz, O Eidel… - Radiology, 2016 - pubs.rsna.org
Purpose To evaluate whether radiomic feature–based magnetic resonance (MR) imaging
signatures allow prediction of survival and stratification of patients with newly diagnosed …

Repeatability of multiparametric prostate MRI radiomics features

M Schwier, J Van Griethuysen, MG Vangel, S Pieper… - Scientific reports, 2019 - nature.com
In this study we assessed the repeatability of radiomics features on small prostate tumors
using test-retest Multiparametric Magnetic Resonance Imaging (mpMRI). The premise of …

The global research of artificial intelligence on prostate cancer: a 22-year bibliometric analysis

Z Shen, H Wu, Z Chen, J Hu, J Pan, J Kong… - Frontiers in …, 2022 - frontiersin.org
Background With the rapid development of technology, artificial intelligence (AI) has been
widely used in the diagnosis and prognosis prediction of a variety of diseases, including …

Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging

E Sala, E Mema, Y Himoto, H Veeraraghavan… - Clinical radiology, 2017 - Elsevier
Tumour heterogeneity in cancers has been observed at the histological and genetic levels,
and increased levels of intra-tumour genetic heterogeneity have been reported to be …