[HTML][HTML] The applications of radiomics in precision diagnosis and treatment of oncology: opportunities and challenges

Z Liu, S Wang, D Dong, J Wei, C Fang, X Zhou… - Theranostics, 2019 - ncbi.nlm.nih.gov
Medical imaging can assess the tumor and its environment in their entirety, which makes it
suitable for monitoring the temporal and spatial characteristics of the tumor. Progress in …

Radiomics and its emerging role in lung cancer research, imaging biomarkers and clinical management: State of the art

G Lee, HY Lee, H Park, ML Schiebler… - European journal of …, 2017 - Elsevier
With the development of functional imaging modalities we now have the ability to study the
microenvironment of lung cancer and its genomic instability. Radiomics is defined as the use …

Fusion-based tensor radiomics using reproducible features: application to survival prediction in head and neck cancer

MR Salmanpour, M Hosseinzadeh, SM Rezaeijo… - Computer Methods and …, 2023 - Elsevier
Background Numerous features are commonly generated in radiomics applications as
applied to medical imaging, and identification of robust radiomics features (RFs) can be an …

Robust radiomics feature quantification using semiautomatic volumetric segmentation

C Parmar, E Rios Velazquez, R Leijenaar… - PloS one, 2014 - journals.plos.org
Due to advances in the acquisition and analysis of medical imaging, it is currently possible
to quantify the tumor phenotype. The emerging field of Radiomics addresses this issue by …

[HTML][HTML] Radiomics in breast imaging from techniques to clinical applications: a review

SH Lee, H Park, ES Ko - Korean journal of radiology, 2020 - ncbi.nlm.nih.gov
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 …

MRI-based radiomics in breast cancer: feature robustness with respect to inter-observer segmentation variability

RWY Granzier, NMH Verbakel, A Ibrahim… - scientific reports, 2020 - nature.com
Radiomics is an emerging field using the extraction of quantitative features from medical
images for tissue characterization. While MRI-based radiomics is still at an early stage, it …

Deep learning driven segmentation of maxillary impacted canine on cone beam computed tomography images

A Swaity, BM Elgarba, N Morgan, S Ali, S Shujaat… - Scientific Reports, 2024 - nature.com
The process of creating virtual models of dentomaxillofacial structures through three-
dimensional segmentation is a crucial component of most digital dental workflows. This …

Radiomics in oncology, part 1: technical principles and gastrointestinal application in CT and MRI

D Caruso, M Polici, M Zerunian, F Pucciarelli, G Guido… - Cancers, 2021 - mdpi.com
Simple Summary Part I is an overview aimed to investigate some technical principles and
the main fields of radiomic application in gastrointestinal oncologic imaging (CT and MRI) …

[HTML][HTML] New imaging techniques for liver diseases

BE Van Beers, JL Daire, P Garteiser - Journal of hepatology, 2015 - Elsevier
Newly developed or advanced methods of ultrasonography and MR imaging provide
combined anatomical and quantitative functional information about diffuse and focal liver …

Radiomics: data mining using quantitative medical image features

MPA Starmans, SR van der Voort, JMC Tovar… - Handbook of medical …, 2020 - Elsevier
Radiomics uses multiple image features from medical imaging data to predict clinical
variables. Various features can be constructed to describe the properties of the full image, or …