Research graph
References from Impact of multisequence MRI on deep learning–based dose prediction for glioblastoma radiotherapy: A comparative evaluation of CT-only and CT+MRI models. Local targets link to admitted publications; unresolved targets remain external evidence.
Effects of radiotherapy with concomitant and adjuvant temozolomide versus radiotherapy alone on survival in glioblastoma in a randomised phase III study: 5-Year analysis of the EORTC-NCIC trial
10.1016/s1470-2045(09)70025-7 · 2009 · External reference
EANO guidelines on the diagnosis and treatment of diffuse gliomas of adulthood
10.1038/s41571-020-00447-z · 2021 · External reference
Isocitrate dehydrogenase-mutant glioma: evolving clinical and therapeutic implications
10.1002/cncr.31039 · 2017 · External reference
Deep learning in MRI-guided radiation therapy: a systematic review
10.1002/acm2.14155 · 2023 · External reference
Deep-learning-based dose predictor for glioblastoma–assessing the sensitivity and robustness for dose awareness in contouring
10.3390/cancers15174226 · 2023 · External reference
Deep learning-powered radiotherapy dose prediction: clinical insights from 622 patients across multiple sites tumor at a single institution
10.1186/s13014-025-02634-7 · 2025 · External reference
Unresolved reference
2023 · External reference
Multi-organ segmentation of organ-at-risk (OAR's) of head and neck site using ensemble learning technique
10.1016/j.radi.2024.02.001 · 2024 · External reference
A combined loss-driven framework for automated parotid segmentation in head-and-neck computed tomography
10.4103/jmp.jmp_169_25 · 2025 · External reference
ESTRO-EANO guideline on target delineation and radiotherapy details for glioblastoma
10.1016/j.radonc.2023.109663 · 2023 · External reference
Magnetic resonance imaging image-based segmentation of brain tumor using the modified transfer learning method
10.4103/jmp.jmp_52_22 · 2022 · External reference
Tumor segmentation for brain tumor using combination of deep learning and machine learning algorithms
2024 · External reference
Ensemble learning for three-dimensional medical image segmentation of organ at risk in brachytherapy using double U-Net, Bi-directional ConvLSTM U-Net, and transformer network
10.4103/jmp.jmp_160_24 · 2024 · External reference
Analysis of hybrid feature optimization techniques based on the classification accuracy of brain tumor regions using machine learning and further evaluation based on the institute test data
10.4103/jmp.jmp_77_23 · 2024 · External reference
Bridge CP. A review of deep learning for brain tumor analysis in MRI
10.1038/s41698-024-00789-2 · 2025 · External reference
Advances in artificial intelligence for glioblastoma radiotherapy planning and treatment
10.3390/cancers17233762 · 2025 · External reference
MRI transformer deep learning and radiomics for predicting IDH wild type TERT promoter mutant gliomas
10.1038/s41698-025-00884-y · 2025 · External reference
Systematic review of synthetic computed tomography generation methodologies for use in magnetic resonance imaging-only radiation therapy
10.1016/j.ijrobp.2017.08.043 · 2018 · External reference
Decomposition of the mean absolute error (MAE) into systematic and unsystematic components
10.1371/journal.pone.0279774 · 2023 · External reference
Structural similarity index family for image quality assessment in radiological images
10.1117/1.jmi.4.3.035501 · 2017 · External reference
A comprehensive survey on gait analysis: history, parameters, approaches, pose estimation, and future work
10.1016/j.artmed.2022.102314 · 2022 · External reference
Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method
10.1088/1361-6560/aa71f8 · 2017 · External reference
A feasibility study for predicting optimal radiation therapy dose distributions of prostate cancer patients from patient anatomy using deep learning
10.1038/s41598-018-37741-x · 2019 · External reference
Knowledge-based automated planning with three-dimensional generative adversarial networks
10.1002/mp.13896 · 2020 · External reference
Rano 2.0: update to the response assessment in neuro-oncology criteria for High- and low-grade gliomas in adults
10.1200/jco.23.01059 · 2023 · External reference
Modified criteria for radiographic response assessment in glioblastoma clinical trials
10.1007/s13311-016-0507-6 · 2017 · External reference
The potential for an enhanced role for MRI in radiation-therapy treatment planning
10.7785/tcrt.2012.500342 · 2013 · External reference
Radiomic profiling of glioblastoma: identifying an imaging predictor of patient survival with improved performance over established clinical and radiologic risk models
10.1148/radiol.2016160845 · 2016 · External reference
Conventional and advanced magnetic resonance imaging assessment of non-enhancing peritumoral area in brain tumor
10.3390/cancers15112992 · 2023 · External reference
Predicting dose-volume histograms for organs-at-risk in IMRT planning
10.1118/1.4761864 · 2012 · External reference
ESTRO-EANO guideline on target delineation and radiotherapy details for glioblastoma
10.1016/j.radonc.2023.109663 · 2023 · External reference
Automatic treatment planning for radiation therapy: a cross-modality and protocol study
2024 · External reference
Automation in intensity modulated radiotherapy treatment planning-a review of recent innovations
10.1259/bjr.20180270 · 2018 · External reference
Artificial intelligence (AI) and interventional radiotherapy (brachytherapy): state of art and future perspectives
10.5114/jcb.2020.100384 · 2020 · External reference
The application and development of deep learning in radiotherapy: a systematic review
10.1177/15330338211016386 · 2021 · External reference
Radiomics: the bridge between medical imaging and personalized medicine
10.1038/nrclinonc.2017.141 · 2017 · External reference
