Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer

Diffusion-weighted MRI for Early Response Assessment in the Treatment of Bladder Cancer

(2018) R. Pearson et al.   CLINICAL ONCOLOGY

Radiomic feature robustness and reproducibility in quantitative bone radiography: A study on radiologic parameter changes

(2018) Ehsan Saeedi et al.   JOURNAL OF CLINICAL DENSITOMETRY

Cochlea CT radiomics predicts chemoradiotherapy induced sensorineural hearing loss in head and neck cancer patients: A machine learning and multi-variable modelling study

(2018) Hamid Abdollahi et al.   Physica Medica-European Journal of Medical Physics

Multiparametric (mp) MRI of prostate cancer

(2018) Virendra Kumar et al.   PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY

Prediction of outcome using pretreatment 18F-FDG PET/CT and MRI radiomics in locally advanced cervical cancer treated with chemoradiotherapy

(2017) François Lucia et al.   EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING

The impact of image reconstruction settings on 18F-FDG PET radiomic features: multi-scanner phantom and patient studies

(2017) Isaac Shiri et al.   EUROPEAN RADIOLOGY

Prostate-specific membrane antigen PET/MRI validation of MR textural analysis for detection of transition zone prostate cancer

(2017) Anthony Bates et al.   EUROPEAN RADIOLOGY

Test-Retest Reproducibility and Robustness Analysis of Recurrent Glioblastoma MRI Radiomics Texture Features

(2017) Isaac Shiri et al.   Iranian Journal of Radiology

Delta-radiomics features for the prediction of patient outcomes in non–small cell lung cancer

(2017) Xenia Fave et al.   Scientific Reports

T2-weighted MRI-derived textural features reflect prostate cancer aggressiveness: preliminary results

(2016) Gabriel Nketiah et al.   EUROPEAN RADIOLOGY

Haralick textural features onT2-weighted MRI are associated with biochemical recurrence following radiotherapy for peripheral zone prostate cancer

(2016) Khémara Gnep et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Radiomic phenotype features predict pathological response in non-small cell lung cancer

(2016) Thibaud P. Coroller et al.   RADIOTHERAPY AND ONCOLOGY

Association of multiparametric MRI quantitative imaging features with prostate cancer gene expression in MRI-targeted prostate biopsies

(2016) Radka Stoyanova et al.   Oncotarget

Prostate cancer radiomics and the promise of radiogenomics

(2016) Radka Stoyanova et al.   Translational Cancer Research

Defining a Radiomic Response Phenotype: A Pilot Study using targeted therapy in NSCLC

(2016) Hugo J. W. L. Aerts et al.   Scientific Reports

Haralick texture analysis of prostate MRI: utility for differentiating non-cancerous prostate from prostate cancer and differentiating prostate cancers with different Gleason scores

(2015) Andreas Wibmer et al.   EUROPEAN RADIOLOGY

Lung Texture in Serial Thoracic Computed Tomography Scans: Correlation of Radiomics-based Features With Radiation Therapy Dose and Radiation Pneumonitis Development

(2015) Alexandra Cunliffe et al.   INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS

Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images

(2015) Duc Fehr et al.   PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA

Radiomic feature clusters and Prognostic Signatures specific for Lung and Head & Neck cancer

(2015) Chintan Parmar et al.   Scientific Reports

Radiomic Machine-Learning Classifiers for Prognostic Biomarkers of Head and Neck Cancer

(2015) Chintan Parmar et al.   Frontiers in Oncology

Machine Learning methods for Quantitative Radiomic Biomarkers

(2015) Chintan Parmar et al.   Scientific Reports

Early prediction of tumor recurrence based on CT texture changes after stereotactic ablative radiotherapy (SABR) for lung cancer

(2014) Sarah A. Mattonen et al.   MEDICAL PHYSICS

Intensity-modulated radiotherapy of the prostate: Dynamic ADC monitoring by DWI at 3.0T

(2014) Georges Decker et al.   RADIOTHERAPY AND ONCOLOGY

Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

(2014) Hugo J. W. L. Aerts et al.   Nature Communications

Current Approaches, Challenges and Future Directions for Monitoring Treatment Response in Prostate Cancer

(2014) T.J. Wallace et al.   Journal of Cancer

Predicting Outcomes of Nonsmall Cell Lung Cancer Using CT Image Features

(2014) Samuel H. Hawkins et al.   IEEE Access

Residual 18F-FDG-PET Uptake 12 Weeks After Stereotactic Ablative Radiotherapy for Stage I Non-Small-Cell Lung Cancer Predicts Local Control

(2012) Vikram Rao Bollineni et al.   INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS

Diffusion-weighted Imaging in Evaluating the Response to Neoadjuvant Breast Cancer Treatment

(2011) Paolo Belli et al.   Breast Journal

Assessment of Response to Radiotherapy for Prostate Cancer: Value of Diffusion-Weighted MRI at 3 T

(2010) Inyoung Song et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

Predicting and monitoring cancer treatment response with diffusion-weighted MRI

(2010) Harriet C. Thoeny et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Challenges in Clinical Prostate Cancer: Role of Imaging

(2009) Gary J. Kelloff et al.   AMERICAN JOURNAL OF ROENTGENOLOGY