Browsing ICR Divisions by author "Blackledge, Matthew"
Now showing items 1-20 of 42
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A comparison of machine learning methods for predicting recurrence and death after curative-intent radiotherapy for non-small cell lung cancer: Development and validation of multivariable clinical prediction models.
Hindocha, S; Charlton, TG; Linton-Reid, K; Hunter, B; Chan, C; et al. (ELSEVIER, 2022-03-03)BACKGROUND: Surveillance is universally recommended for non-small cell lung cancer (NSCLC) patients treated with curative-intent radiotherapy. High-quality evidence to inform optimal surveillance strategies is lacking. ... -
Accelerating Whole-Body Diffusion-weighted MRI with Deep Learning-based Denoising Image Filters.
Zormpas-Petridis, K; Tunariu, N; Curcean, A; Messiou, C; Curcean, S; et al. (RADIOLOGICAL SOC NORTH AMERICA (RSNA), 2021-09-01)PURPOSE: To use deep learning to improve the image quality of subsampled images (number of acquisitions = 1 [NOA1]) to reduce whole-body diffusion-weighted MRI (WBDWI) acquisition times. MATERIALS AND METHODS: Both ... -
Assessment of treatment response by total tumor volume and global apparent diffusion coefficient using diffusion-weighted MRI in patients with metastatic bone disease: a feasibility study.
Blackledge, MD; Collins, DJ; Tunariu, N; Orton, MR; Padhani, AR; et al. (PUBLIC LIBRARY SCIENCE, 2014-04-07)We describe our semi-automatic segmentation of whole-body diffusion-weighted MRI (WBDWI) using a Markov random field (MRF) model to derive tumor total diffusion volume (tDV) and associated global apparent diffusion coefficient ... -
Automatic Segmentation of Pelvic Cancers Using Deep Learning: State-of-the-Art Approaches and Challenges.
Kalantar, R; Lin, G; Winfield, JM; Messiou, C; Lalondrelle, S; et al. (MDPI, 2021-10-22)The recent rise of deep learning (DL) and its promising capabilities in capturing non-explicit detail from large datasets have attracted substantial research attention in the field of medical image processing. DL provides ... -
Capturing Global Spatial Context for Accurate Cell Classification in Skin Cancer Histology
Zormpas-Petridis, K; Failmezger, H; Roxanis, I; Blackledge, M; Jamin, Y; et al. (SPRINGER INTERNATIONAL PUBLISHING AG, 2018-01-01) -
Capturing Global Spatial Context for Accurate Cell Classification in Skin Cancer Histology
Zormpas-Petridis, K; Failmezger, H; Roxanis, I; Blackledge, M; Jamin, Y; et al. (SPRINGER INTERNATIONAL PUBLISHING AG, 2018-01-01) -
CT-Based Pelvic T1-Weighted MR Image Synthesis Using UNet, UNet++ and Cycle-Consistent Generative Adversarial Network (Cycle-GAN).
Kalantar, R; Messiou, C; Winfield, JM; Renn, A; Latifoltojar, A; et al. (FRONTIERS MEDIA SA, 2021-07-30)BACKGROUND: Computed tomography (CT) and magnetic resonance imaging (MRI) are the mainstay imaging modalities in radiotherapy planning. In MR-Linac treatment, manual annotation of organs-at-risk (OARs) and clinical volumes ... -
Deep Learning Framework with Multi-Head Dilated Encoders for Enhanced Segmentation of Cervical Cancer on Multiparametric Magnetic Resonance Imaging.
Kalantar, R; Curcean, S; Winfield, JM; Lin, G; Messiou, C; et al. (MDPI, 2023-11-03)T2-weighted magnetic resonance imaging (MRI) and diffusion-weighted imaging (DWI) are essential components of cervical cancer diagnosis. However, combining these channels for the training of deep learning models is challenging ... -
Deep-learned estimation of uncertainty in measurements of apparent diffusion coefficient from whole-body diffusion-weighted MRI.
Zormpas-Petridis, K; Tunariu, N; Collins, DJ; Messiou, C; Koh, D-M; et al. (PERGAMON-ELSEVIER SCIENCE LTD, 2022-10-01)PURPOSE: To use deep learning to calculate the uncertainty in apparent diffusion coefficient (σADC) voxel-wise measurements to clinically impact the monitoring of treatment response and improve the quality of ADC maps. ... -
Diffusion-weighted (DW) MRI in lung cancers: ADC test-retest repeatability.
Weller, A; Papoutsaki, MV; Waterton, JC; Chiti, A; Stroobants, S; et al. (SPRINGER, 2017-11-01)PURPOSE: To determine the test-retest repeatability of Apparent Diffusion Coefficient (ADC) measurements across institutions and MRI vendors, plus investigate the effect of post-processing methodology on measurement ... -
Diffusion-weighted Imaging as a Treatment Response Biomarker for Evaluating Bone Metastases in Prostate Cancer: A Pilot Study.
Perez-Lopez, R; Mateo, J; Mossop, H; Blackledge, MD; Collins, DJ; et al. (RADIOLOGICAL SOC NORTH AMERICA, 2017-04-01)Purpose To determine the usefulness of whole-body diffusion-weighted imaging (DWI) to assess the response of bone metastases to treatment in patients with metastatic castration-resistant prostate cancer (mCRPC). Materials ... -
Extracranial Soft-Tissue Tumors: Repeatability of Apparent Diffusion Coefficient Estimates from Diffusion-weighted MR Imaging.
Winfield, JM; Tunariu, N; Rata, M; Miyazaki, K; Jerome, NP; et al. (RADIOLOGICAL SOC NORTH AMERICA, 2017-07-01)Purpose To assess the repeatability of apparent diffusion coefficient (ADC) estimates in extracranial soft-tissue diffusion-weighted magnetic resonance imaging across a wide range of imaging protocols and patient populations. ... -
Fracture Risk in Men with Metastatic Prostate Cancer Treated With Radium-223.
Hijab, A; Curcean, S; Tunariu, N; Tovey, H; Alonzi, R; et al. (CIG MEDIA GROUP, LP, 2021-10-01)BACKGROUND: Radium-223 is a bone-seeking, alpha-emitting radionuclide used in metastatic castration-resistant prostate cancer (mCRPC). Radium-223 increases the risk of fracture when used in combination with abiraterone and ... -
Gross tumour volume radiomics for prognostication of recurrence & death following radical radiotherapy for NSCLC.
Hindocha, S; Charlton, TG; Linton-Reid, K; Hunter, B; Chan, C; et al. (NATURE PORTFOLIO, 2022-10-27)Recurrence occurs in up to 36% of patients treated with curative-intent radiotherapy for NSCLC. Identifying patients at higher risk of recurrence for more intensive surveillance may facilitate the earlier introduction of ... -
Guidelines for Acquisition, Interpretation, and Reporting of Whole-Body MRI in Myeloma: Myeloma Response Assessment and Diagnosis System (MY-RADS).
Messiou, C; Hillengass, J; Delorme, S; Lecouvet, FE; Moulopoulos, LA; et al. (RADIOLOGICAL SOC NORTH AMERICA, 2019-04-01)Acknowledging the increasingly important role of whole-body MRI for directing patient care in myeloma, a multidisciplinary, international, and expert panel of radiologists, medical physicists, and hematologists with specific ... -
Implementation of Whole-Body MRI (MY-RADS) within the OPTIMUM/MUKnine multi-centre clinical trial for patients with myeloma.
Rata, M; Blackledge, M; Scurr, E; Winfield, J; Koh, D-M; et al. (SPRINGER, 2022-07-28)BACKGROUND: Whole-body (WB) MRI, which includes diffusion-weighted imaging (DWI) and T1-w Dixon, permits sensitive detection of marrow disease in addition to qualitative and quantitative measurements of disease and response ... -
Inter- and Intra-Observer Repeatability of Quantitative Whole-Body, Diffusion-Weighted Imaging (WBDWI) in Metastatic Bone Disease.
Blackledge, MD; Tunariu, N; Orton, MR; Padhani, AR; Collins, DJ; et al. (PUBLIC LIBRARY SCIENCE, 2016-04-28)Quantitative whole-body diffusion-weighted MRI (WB-DWI) is now possible using semi-automatic segmentation techniques. The method enables whole-body estimates of global Apparent Diffusion Coefficient (gADC) and total Diffusion ... -
Inter-observer agreement of baseline whole body MRI in multiple myeloma.
Croft, J; Riddell, A; Koh, D-M; Downey, K; Blackledge, M; et al. (BMC, 2020-07-14)BACKGROUND: Whole body magnetic resonance imaging (MRI) is now incorporated into international guidance for imaging patients with multiple myeloma. The aim of this study was to investigate inter-observer agreement of triple ... -
MRI Imaging of the Hemodynamic Vasculature of Neuroblastoma Predicts Response to Antiangiogenic Treatment.
Zormpas-Petridis, K; Jerome, NP; Blackledge, MD; Carceller, F; Poon, E; et al. (AMER ASSOC CANCER RESEARCH, 2019-06)Childhood neuroblastoma is a hypervascular tumor of neural origin, for which antiangiogenic drugs are currently being evaluated; however, predictive biomarkers of treatment response, crucial for successful delivery of ... -
MRI texture feature repeatability and image acquisition factor robustness, a phantom study and in silico study.
Shur, J; Blackledge, M; D'Arcy, J; Collins, DJ; Bali, M; et al. (SPRINGERNATURE, 2021-01-19)PURPOSE: To evaluate robustness and repeatability of magnetic resonance imaging (MRI) texture features in water and tissue phantom test-retest study. MATERIALS AND METHODS: Separate water and tissue phantoms were imaged ...