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The Radiation Planning Assistant: addressing the global gap in radiotherapy services

The lancet oncology, 2024-03, Vol.25 (3), p.277-278

Court, Laurence E

2024

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Advances in Auto-Segmentation

Seminars in radiation oncology, 2019-07, Vol.29 (3), p.185-197

2019

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Prognostic Value and Reproducibility of Pretreatment CT Texture Features in Stage III Non-Small Cell Lung Cancer

International journal of radiation oncology, biology, physics, 2014-11, Vol.90 (4), p.834-842

2014

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ibex: An open infrastructure software platform to facilitate collaborative work in radiomics

Medical physics (Lancaster), 2015-03, Vol.42 (3), p.1341-1353

2015

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Lung tumor segmentation methods: Impact on the uncertainty of radiomics features for non-small cell lung cancer

PloS one, 2018-10, Vol.13 (10), p.e0205003-e0205003

2018

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The utility of quantitative CT radiomics features for improved prediction of radiation pneumonitis

Medical physics (Lancaster), 2018-11, Vol.45 (11), p.5317-5324

2018

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Radiomics features of the primary tumor fail to improve prediction of overall survival in large cohorts of CT- and PET-imaged head and neck cancer patients

PloS one, 2019-09, Vol.14 (9), p.e0222509

2019

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Radiomics feature robustness as measured using an MRI phantom

Scientific reports, 2021-02, Vol.11 (1), p.3973-3973, Article 3973

2021

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Measuring Computed Tomography Scanner Variability of Radiomics Features

Investigative radiology, 2015-11, Vol.50 (11), p.757-765

2015

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

Scientific reports, 2017-04, Vol.7 (1), p.588-588, Article 588

2017

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Technical Note: Dose prediction for head and neck radiotherapy using a three‐dimensional dense dilated U‐net architecture

Medical physics (Lancaster), 2021-09, Vol.48 (9), p.5567-5573

2021

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Training deep‐learning segmentation models from severely limited data

Medical physics (Lancaster), 2021-04, Vol.48 (4), p.1697-1706

2021

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Automatic detection of contouring errors using convolutional neural networks

Medical physics (Lancaster), 2019-11, Vol.46 (11), p.5086-5097

2019

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Motion of the esophagus due to cardiac motion

PloS one, 2014-02, Vol.9 (2), p.e89126-e89126

2014

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The Incremental Value of Subjective and Quantitative Assessment of 18F-FDG PET for the Prediction of Pathologic Complete Response to Preoperative Chemoradiotherapy in Esophageal Cancer

The Journal of nuclear medicine (1978), 2016-05, Vol.57 (5), p.691-700

2016

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Compensation cycle consistent generative adversarial networks (Comp‐GAN) for synthetic CT generation from MR scans with truncated anatomy

Medical physics (Lancaster), 2023-07, Vol.50 (7), p.4399-4414

2023

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A predictive model for distinguishing radiation necrosis from tumour progression after gamma knife radiosurgery based on radiomic features from MR images

European radiology, 2018-06, Vol.28 (6), p.2255-2263

2018

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Development and Validation of a Predictive Radiomics Model for Clinical Outcomes in Stage I Non-small Cell Lung Cancer

International journal of radiation oncology, biology, physics, 2018-11, Vol.102 (4), p.1090-1097

2018

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Stage III Non-Small Cell Lung Cancer: Prognostic Value of FDG PET Quantitative Imaging Features Combined with Clinical Prognostic Factors

Radiology, 2016-01, Vol.278 (1), p.214-222

2016

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Harmonizing the pixel size in retrospective computed tomography radiomics studies

PloS one, 2017-09, Vol.12 (9), p.e0178524-e0178524

2017

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The Emergence of Artificial Intelligence within Radiation Oncology Treatment Planning

Oncology, 2021-02, Vol.99 (2), p.124-134

2021

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Effects of alterations in positron emission tomography imaging parameters on radiomics features

PloS one, 2019-09, Vol.14 (9), p.e0221877-e0221877

2019

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Experience in commissioning the halcyon linac

Medical physics (Lancaster), 2019-10, Vol.46 (10), p.4304-4313

2019

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Auto-delineation of oropharyngeal clinical target volumes using 3D convolutional neural networks

Physics in medicine & biology, 2018-11, Vol.63 (21), p.215026-215026

2018

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Deep Learning Algorithm for Auto-Delineation of High-Risk Oropharyngeal Clinical Target Volumes With Built-In Dice Similarity Coefficient Parameter Optimization Function

International journal of radiation oncology, biology, physics, 2018-06, Vol.101 (2), p.468-478

2018

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The Radiation Planning Assistant: addressing the global gap in radiotherapy services

Advances in Auto-Segmentation

Prognostic Value and Reproducibility of Pretreatment CT Texture Features in Stage III Non-Small Cell Lung Cancer

ibex: An open infrastructure software platform to facilitate collaborative work in radiomics

Lung tumor segmentation methods: Impact on the uncertainty of radiomics features for non-small cell lung cancer

The utility of quantitative CT radiomics features for improved prediction of radiation pneumonitis

Radiomics features of the primary tumor fail to improve prediction of overall survival in large cohorts of CT- and PET-imaged head and neck cancer patients

Radiomics feature robustness as measured using an MRI phantom

Measuring Computed Tomography Scanner Variability of Radiomics Features

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

Technical Note: Dose prediction for head and neck radiotherapy using a three‐dimensional dense dilated U‐net architecture

Training deep‐learning segmentation models from severely limited data

Automatic detection of contouring errors using convolutional neural networks

Motion of the esophagus due to cardiac motion

The Incremental Value of Subjective and Quantitative Assessment of 18F-FDG PET for the Prediction of Pathologic Complete Response to Preoperative Chemoradiotherapy in Esophageal Cancer

Compensation cycle consistent generative adversarial networks (Comp‐GAN) for synthetic CT generation from MR scans with truncated anatomy

A predictive model for distinguishing radiation necrosis from tumour progression after gamma knife radiosurgery based on radiomic features from MR images

Development and Validation of a Predictive Radiomics Model for Clinical Outcomes in Stage I Non-small Cell Lung Cancer

Stage III Non-Small Cell Lung Cancer: Prognostic Value of FDG PET Quantitative Imaging Features Combined with Clinical Prognostic Factors

Harmonizing the pixel size in retrospective computed tomography radiomics studies

The Emergence of Artificial Intelligence within Radiation Oncology Treatment Planning

Effects of alterations in positron emission tomography imaging parameters on radiomics features

Experience in commissioning the halcyon linac

Auto-delineation of oropharyngeal clinical target volumes using 3D convolutional neural networks

Deep Learning Algorithm for Auto-Delineation of High-Risk Oropharyngeal Clinical Target Volumes With Built-In Dice Similarity Coefficient Parameter Optimization Function

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