Brain tumor detection and classification using machine learning: a comprehensive survey
J Amin, M Sharif, A Haldorai, M Yasmin… - Complex & intelligent …, 2022 - Springer
Brain tumor occurs owing to uncontrolled and rapid growth of cells. If not treated at an initial
phase, it may lead to death. Despite many significant efforts and promising outcomes in this …
phase, it may lead to death. Despite many significant efforts and promising outcomes in this …
Artificial intelligence in cancer imaging: clinical challenges and applications
Judgement, as one of the core tenets of medicine, relies upon the integration of multilayered
data with nuanced decision making. Cancer offers a unique context for medical decisions …
data with nuanced decision making. Cancer offers a unique context for medical decisions …
Residual Convolutional Neural Network for the Determination of IDH Status in Low- and High-Grade Gliomas from MR Imaging
Purpose: Isocitrate dehydrogenase (IDH) mutations in glioma patients confer longer survival
and may guide treatment decision making. We aimed to predict the IDH status of gliomas …
and may guide treatment decision making. We aimed to predict the IDH status of gliomas …
Fully automated hybrid approach to predict the IDH mutation status of gliomas via deep learning and radiomics
YS Choi, S Bae, JH Chang, SG Kang, SH Kim… - Neuro …, 2021 - academic.oup.com
Background Glioma prognosis depends on isocitrate dehydrogenase (IDH) mutation status.
We aimed to predict the IDH status of gliomas from preoperative MR images using a fully …
We aimed to predict the IDH status of gliomas from preoperative MR images using a fully …
Machine learning–based radiomics for molecular subtyping of gliomas
Purpose: The new classification announced by the World Health Organization in 2016
recognized five molecular subtypes of diffuse gliomas based on isocitrate dehydrogenase …
recognized five molecular subtypes of diffuse gliomas based on isocitrate dehydrogenase …
MRI features predict survival and molecular markers in diffuse lower-grade gliomas
Background. Previous studies have shown that MR imaging features can be used to predict
survival and molecular profile of glioblastoma. However, no study of a similar type has been …
survival and molecular profile of glioblastoma. However, no study of a similar type has been …
Automatic assessment of glioma burden: a deep learning algorithm for fully automated volumetric and bidimensional measurement
Background Longitudinal measurement of glioma burden with MRI is the basis for treatment
response assessment. In this study, we developed a deep learning algorithm that …
response assessment. In this study, we developed a deep learning algorithm that …
Natural and artificial intelligence in neurosurgery: a systematic review
JT Senders, O Arnaout, AV Karhade… - …, 2018 - journals.lww.com
BACKGROUND Machine learning (ML) is a domain of artificial intelligence that allows
computer algorithms to learn from experience without being explicitly programmed …
computer algorithms to learn from experience without being explicitly programmed …
Retracted: A novel fully automated MRI-based deep-learning method for classification of IDH mutation status in brain gliomas
CG Bangalore Yogananda, BR Shah… - Neuro …, 2020 - academic.oup.com
Background. Isocitrate dehydrogenase (IDH) mutation status has emerged as an important
prognostic marker in gliomas. Currently, reliable IDH mutation determination requires …
prognostic marker in gliomas. Currently, reliable IDH mutation determination requires …
[HTML][HTML] Molecular pathology of tumors of the central nervous system
BW Kristensen, LP Priesterbach-Ackley, JK Petersen… - Annals of oncology, 2019 - Elsevier
Since the update of the 4th edition of the WHO Classification of Central Nervous System
(CNS) Tumors published in 2016, particular molecular characteristics are part of the …
(CNS) Tumors published in 2016, particular molecular characteristics are part of the …