The potential of radiomic-based phenotyping in precision medicine: a review

HJWL Aerts - JAMA oncology, 2016 - jamanetwork.com
Importance Advances in genomics have led to the recognition that tumors are populated by
distinct genotypic subgroups that drive tumor development and progression. The spatial and …

Radiomics: the process and the challenges

V Kumar, Y Gu, S Basu, A Berglund, SA Eschrich… - Magnetic resonance …, 2012 - Elsevier
“Radiomics” refers to the extraction and analysis of large amounts of advanced quantitative
imaging features with high throughput from medical images obtained with computed …

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 …

Quantitative imaging in cancer evolution and ecology

RA Gatenby, O Grove, RJ Gillies - Radiology, 2013 - pubs.rsna.org
Cancer therapy, even when highly targeted, typically fails because of the remarkable
capacity of malignant cells to evolve effective adaptations. These evolutionary dynamics are …

Automatic scoring of multiple semantic attributes with multi-task feature leverage: a study on pulmonary nodules in CT images

S Chen, J Qin, X Ji, B Lei, T Wang, D Ni… - IEEE transactions on …, 2016 - ieeexplore.ieee.org
The gap between the computational and semantic features is the one of major factors that
bottlenecks the computer-aided diagnosis (CAD) performance from clinical usage. To bridge …

Lung nodule malignancy classification using only radiologist-quantified image features as inputs to statistical learning algorithms: probing the Lung Image Database …

MC Hancock, JF Magnan - Journal of Medical Imaging, 2016 - spiedigitallibrary.org
In the assessment of nodules in CT scans of the lungs, a number of image-derived features
are diagnostically relevant. Currently, many of these features are defined only qualitatively …

Magnetic resonance imaging-based radiomic profiles predict patient prognosis in newly diagnosed glioblastoma before therapy

SD McGarry, SL Hurrell, AL Kaczmarowski… - …, 2016 - pmc.ncbi.nlm.nih.gov
Magnetic resonance imaging (MRI) is used to diagnose and monitor brain tumors. Extracting
additional information from medical imaging and relating it to a clinical variable of interest is …

Imaging in the age of precision medicine: summary of the proceedings of the 10th Biannual Symposium of the International Society for Strategic Studies in Radiology

CJ Herold, JS Lewin, AG Wibmer, JH Thrall, GP Krestin… - Radiology, 2016 - pubs.rsna.org
During the past decade, with its breakthroughs in systems biology, precision medicine (PM)
has emerged as a novel health-care paradigm. Challenging reductionism and broad-based …

Integrating pathology and radiology disciplines: an emerging opportunity?

J Sorace, DR Aberle, D Elimam, S Lawvere, O Tawfik… - BMC medicine, 2012 - Springer
Pathology and radiology form the core of cancer diagnosis, yet the workflows of both
specialties remain ad hoc and occur in separate" silos," with no direct linkage between their …

An inception module CNN classifiers fusion method on pulmonary nodule diagnosis by signs

G Zheng, G Han, NQ Soomro - Tsinghua Science and …, 2019 - ieeexplore.ieee.org
A “sign” on a lung CT image refers to a radiologic finding that suggests a pathological
progression of some specific disease. Analysis of CT signs is helpful to understand the …