Related references
Note: Only part of the references are listed.Clinical and Molecular Features of Patients with Gliomas Harboring IDH1 Non-canonical Mutations: A Systematic Review and Meta-Analysis
Vincenzo Di Nunno et al.
ADVANCES IN THERAPY (2022)
Improved breast cancer histological grading using deep learning
Y. Wang et al.
ANNALS OF ONCOLOGY (2022)
Automatic segmentation of magnetic resonance images for high-dose-rate cervical cancer brachytherapy using deep learning
S. A. Yoganathan et al.
MEDICAL PHYSICS (2022)
Development and validation of a deep-learning model for detecting brain metastases on 3D post-contrast MRI: a multi-center multi-reader evaluation study
Shaohan Yin et al.
NEURO-ONCOLOGY (2022)
A pilot study of machine-learning based automated planning for primary brain tumours
Derek S. Tsang et al.
RADIATION ONCOLOGY (2022)
Radiomics outperforms semantic features for prediction of response to stereotactic radiosurgery in brain metastases
Robin Gutsche et al.
RADIOTHERAPY AND ONCOLOGY (2022)
Molecular Targeted Therapies: Time for a Paradigm Shift in Medulloblastoma Treatment?
Lidia Gatto et al.
CANCERS (2022)
Developing and validating a deep learning and radiomic model for glioma grading using multiplanar reconstructed magnetic resonance contrast-enhanced T1-weighted imaging: a robust, multi-institutional study
Jialin Ding et al.
QUANTITATIVE IMAGING IN MEDICINE AND SURGERY (2022)
Deep learning-based automatic tumor burden assessment of pediatric high-grade gliomas, medulloblastomas, and other leptomeningeal seeding tumors
Jian Peng et al.
NEURO-ONCOLOGY (2022)
Integrating morphologic and molecular histopathological features through whole slide image registration and deep learning
Kevin Faust et al.
NEURO-ONCOLOGY ADVANCES (2022)
Artificial intelligence neuropathologist for glioma classification using deep learning on hematoxylin and eosin stained slide images and molecular markers
Lei Jin et al.
NEURO-ONCOLOGY (2021)
Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics
Yoon Seong Choi et al.
NEURO-ONCOLOGY (2021)
BISON: Brain tissue segmentation pipeline using T1-weighted magnetic resonance images and a random forest classifier
Mahsa Dadar et al.
MAGNETIC RESONANCE IN MEDICINE (2021)
Meningioma: not always a benign tumor. A review of advances in the treatment of meningiomas
Ilaria Maggio et al.
CNS oncology (2021)
La classification de l’OMS 2021 des tumeurs du système nerveux central
Dominique Figarella-Branger et al.
ANNALES DE PATHOLOGIE (2021)
MR-Guided Radiotherapy for Brain and Spine Tumors
Danilo Maziero et al.
FRONTIERS IN ONCOLOGY (2021)
Machine learning revealed stemness features and a novel stemness-based classification with appealing implications in discriminating the prognosis, immunotherapy and temozolomide responses of 906 glioblastoma patients
Zihao Wang et al.
BRIEFINGS IN BIOINFORMATICS (2021)
Randomized multi-reader evaluation of automated detection and segmentation of brain tumors in stereotactic radiosurgery with deep neural networks
Shao-Lun Lu et al.
NEURO-ONCOLOGY (2021)
Artificial Intelligence in magnetic Resonance guided Radiotherapy: Medical and physical considerations on state of art and future perspectives
Davide Cusumano et al.
PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS (2021)
Deep Neural Network for Differentiation of Brain Tumor Tissue Displayed by Confocal Laser Endomicroscopy
Andreas Ziebart et al.
FRONTIERS IN ONCOLOGY (2021)
Brain and other central nervous system tumor statistics, 2021
Kimberly D. Miller et al.
CA-A CANCER JOURNAL FOR CLINICIANS (2021)
IDH Inhibitors and Beyond: The Cornerstone of Targeted Glioma Treatment
Lidia Gatto et al.
MOLECULAR DIAGNOSIS & THERAPY (2021)
The 2021 WHO Classification of Tumors of the Central Nervous System: a summary
David N. Louis et al.
NEURO-ONCOLOGY (2021)
Machine Learning-Based Prediction of Early Recurrence in Glioblastoma Patients: A Glance Towards Precision Medicine
Giuseppe Maria Della Pepa et al.
NEUROSURGERY (2021)
Deep learning methods to generate synthetic CT from MRI in radiotherapy: A literature review
M. Boulanger et al.
PHYSICA MEDICA-EUROPEAN JOURNAL OF MEDICAL PHYSICS (2021)
Combining multi-site magnetic resonance imaging with machine learning predicts survival in pediatric brain tumors
James T. Grist et al.
SCIENTIFIC REPORTS (2021)
Deep Neural Network Analysis of Pathology Images With Integrated Molecular Data for Enhanced Glioma Classification and Grading
Linmin Pei et al.
FRONTIERS IN ONCOLOGY (2021)
Label-free imaging of human brain tissue at subcellular resolution for potential rapid intra-operative assessment of glioma surgery
Defu Chen et al.
THERANOSTICS (2021)
Imaging-Based Algorithm for the Local Grading of Glioma
E. D. H. Gates et al.
AMERICAN JOURNAL OF NEURORADIOLOGY (2020)
Artificial intelligence in digital breast pathology: Techniques and applications
Asmaa Ibrahim et al.
BREAST (2020)
Efficient identification of novel anti-glioma lead compounds by machine learning models
Bruno Junior Neves et al.
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY (2020)
Technical Note: A feasibility study on deep learning-based radiotherapy dose calculation
Yixun Xing et al.
MEDICAL PHYSICS (2020)
Near real-time intraoperative brain tumor diagnosis using stimulated Raman histology and deep neural networks
Todd C. Hollon et al.
NATURE MEDICINE (2020)
Deep learning-based detection and segmentation-assisted management of brain metastases
Jie Xue et al.
NEURO-ONCOLOGY (2020)
Segmentation and Classification in Digital Pathology for Glioma Research: Challenges and Deep Learning Approaches
Tahsin Kurc et al.
FRONTIERS IN NEUROSCIENCE (2020)
Synthesized 7T MRI from 3T MRI via deep learning in spatial and wavelet domains
Liangqiong Qu et al.
MEDICAL IMAGE ANALYSIS (2020)
Mechanisms and therapeutic implications of hypermutation in gliomas
Mehdi Touat et al.
NATURE (2020)
Discrimination between pituitary adenoma and craniopharyngioma using MRI-based image features and texture features
Yang Zhang et al.
JAPANESE JOURNAL OF RADIOLOGY (2020)
Machine Learning-Based Models for Prediction of Toxicity Outcomes in Radiotherapy
Lars J. Isaksson et al.
FRONTIERS IN ONCOLOGY (2020)
Histopathological grading affects survival in patients with IDH-mutant grade II and grade III diffuse gliomas
Enrico Franceschi et al.
EUROPEAN JOURNAL OF CANCER (2020)
Artificial intelligence in radiation oncology
Elizabeth Huynh et al.
NATURE REVIEWS CLINICAL ONCOLOGY (2020)
An introduction to deep learning in medical physics: advantages, potential, and challenges
Chenyang Shen et al.
PHYSICS IN MEDICINE AND BIOLOGY (2020)
Incorporating diffusion- and perfusion-weighted MRI into a radiomics model improves diagnostic performance for pseudoprogression in glioblastoma patients
Jung Youn Kim et al.
NEURO-ONCOLOGY (2019)
MR-based treatment planning in radiation therapy using a deep learning approach
Fang Liu et al.
JOURNAL OF APPLIED CLINICAL MEDICAL PHYSICS (2019)
Radiomics of Brain MRI: Utility in Prediction of Metastatic Tumor Type
Helge C. Kniep et al.
RADIOLOGY (2019)
MRI-only based synthetic CT generation using dense cycle consistent generative adversarial networks
Yang Lei et al.
MEDICAL PHYSICS (2019)
A deep learning radiomics model for preoperative grading in meningioma
Yongbei Zhu et al.
EUROPEAN JOURNAL OF RADIOLOGY (2019)
Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer
Jakob Nikolas Kather et al.
NATURE MEDICINE (2019)
Automatic assessment of glioma burden: a deep learning algorithm for fully automated volumetric and bidimensional measurement
Ken Chang et al.
NEURO-ONCOLOGY (2019)
Radiomics approach for prediction of recurrence in skull base meningiomas
Yang Zhang et al.
NEURORADIOLOGY (2019)
Confocal-Assisted Multispectral Fluorescent Microscopy for Brain Tumor Surgery
Patra Charalampaki et al.
FRONTIERS IN ONCOLOGY (2019)
Personalized oncology with artificial intelligence: The case of temozolomide
Nicolas Houy et al.
ARTIFICIAL INTELLIGENCE IN MEDICINE (2019)
Automated brain histology classification using machine learning
Justin Ker et al.
JOURNAL OF CLINICAL NEUROSCIENCE (2019)
Prediction of high proliferative index in pituitary macroadenomas using MRI-based radiomics and machine learning
Lorenzo Ugga et al.
NEURORADIOLOGY (2019)
Deep Learning: A Review for the Radiation Oncologist
Luca Boldrini et al.
FRONTIERS IN ONCOLOGY (2019)
Molecular targeted therapy of glioblastoma
Emilie Le Rhun et al.
CANCER TREATMENT REVIEWS (2019)
Differentiation of Recurrence from Radiation Necrosis in Gliomas Based on the Radiomics of Combinational Features and Multimodality MRI Images
Quan Zhang et al.
COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE (2019)
Brain tissue segmentation using improved kernelized rough-fuzzy C-means with spatio-contextual information from MRI
Anindya Halder et al.
MAGNETIC RESONANCE IMAGING (2019)
MR Imaging-Based Radiomic Signatures of Distinct Molecular Subgroups of Medulloblastoma
M. Iv et al.
AMERICAN JOURNAL OF NEURORADIOLOGY (2019)
Radiomics and machine learning may accurately predict the grade and histological subtype in meningiomas using conventional and diffusion tensor imaging
Yae Won Park et al.
EUROPEAN RADIOLOGY (2019)
Deep learning in medical imaging and radiation therapy
Berkman Sahiner et al.
MEDICAL PHYSICS (2019)
An overview of deep learning in medical imaging focusing on MRI
Alexander Selvikvag Lundervold et al.
ZEITSCHRIFT FUR MEDIZINISCHE PHYSIK (2019)
Integrated models incorporating radiologic and radiomic features predict meningioma grade, local failure, and overall survival
Olivier Morin et al.
NEURO-ONCOLOGY ADVANCES (2019)
Rise of the Machines: Advances in Deep Learning for Cancer Diagnosis
Adrian B. Levine et al.
TRENDS IN CANCER (2019)
Deep Learning in Neuroradiology
G. Zaharchuk et al.
AMERICAN JOURNAL OF NEURORADIOLOGY (2018)
Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas
P. Chang et al.
AMERICAN JOURNAL OF NEURORADIOLOGY (2018)
Survey on deep learning for radiotherapy
Philippe Meyer et al.
COMPUTERS IN BIOLOGY AND MEDICINE (2018)
MR-Only Brain Radiation Therapy: Dosimetric Evaluation of Synthetic CTs Generated by a Dilated Convolutional Neural Network
Anna M. Dinkla et al.
INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS (2018)
Generating synthetic CTs from magnetic resonance images using generative adversarial networks
Hajar Emami et al.
MEDICAL PHYSICS (2018)
In vivo evaluation of EGFRvIII mutation in primary glioblastoma patients via complex multiparametric MRI signature
Named Akbari et al.
NEURO-ONCOLOGY (2018)
Artificial intelligence in radiation oncology: A specialty-wide disruptive transformation?
Reid F. Thompson et al.
RADIOTHERAPY AND ONCOLOGY (2018)
Deep learning for undersampled MRI reconstruction
Chang Min Hyun et al.
PHYSICS IN MEDICINE AND BIOLOGY (2018)
MR-based synthetic CT generation using a deep convolutional neural network method
Xiao Han
MEDICAL PHYSICS (2017)
Neuroscience-Inspired Artificial Intelligence
Demis Hassabis et al.
NEURON (2017)
Fully automatic acute ischemic lesion segmentation in DWI using convolutional neural networks
Liang Chen et al.
NEUROIMAGE-CLINICAL (2017)
Whole Brain Volume Measured from 1.5T versus 3T MRI in Healthy Subjects and Patients with Multiple Sclerosis
Renxin Chu et al.
JOURNAL OF NEUROIMAGING (2016)
Big Data and machine learning in radiation oncology: State of the art and future prospects
Jean-Emmanuel Bibault et al.
CANCER LETTERS (2016)
Radiogenomics of Glioblastoma: Machine Learning-based Classification of Molecular Characteristics by Using Multiparametric and Multiregional MR Imaging Features
Philipp Kickingereder et al.
RADIOLOGY (2016)
Consenting for Molecular Diagnostics
Robert Klitzman
CLINICAL CHEMISTRY (2015)
Canadian Licensure for the Use of Digital Pathology for Routine Diagnoses One More Step Toward a New Era of Pathology Practice Without Borders
Bernard Tetu et al.
ARCHIVES OF PATHOLOGY & LABORATORY MEDICINE (2014)
Application of Quantitative MRI for Brain Tissue Segmentation at 1.5 T and 3.0 T Field Strengths
Janne West et al.
PLOS ONE (2013)
CT substitute derived from MRI sequences with ultrashort echo time
Adam Johansson et al.
MEDICAL PHYSICS (2011)