Introduction to radiomics and radiogenomics in neuro-oncology: implications and challenges
Neuro-oncology largely consists of malignancies of the brain and central nervous system
including both primary as well as metastatic tumors. Currently, a significant clinical …
including both primary as well as metastatic tumors. Currently, a significant clinical …
RadioTransformer: A cascaded global-focal transformer for visual attention–guided disease classification
In this work, we present RadioTransformer, a novel student-teacher transformer framework,
that leverages radiologists' gaze patterns and models their visuo-cognitive behavior for …
that leverages radiologists' gaze patterns and models their visuo-cognitive behavior for …
Radiomics for glioblastoma survival analysis in pre-operative MRI: exploring feature robustness, class boundaries, and machine learning techniques
Background This study aims to identify robust radiomic features for Magnetic Resonance
Imaging (MRI), assess feature selection and machine learning methods for overall survival …
Imaging (MRI), assess feature selection and machine learning methods for overall survival …
Gazeradar: A gaze and radiomics-guided disease localization framework
We present GazeRadar, a novel radiomics and eye gaze-guided deep learning architecture
for disease localization in chest radiographs. GazeRadar combines the representation of …
for disease localization in chest radiographs. GazeRadar combines the representation of …
Predicting survival of glioblastoma from automatic whole-brain and tumor segmentation of MR images
Survival prediction models can potentially be used to guide treatment of glioblastoma
patients. However, currently available MR imaging biomarkers holding prognostic …
patients. However, currently available MR imaging biomarkers holding prognostic …
Novel MRI deformation-heterogeneity radiomic features are associated with molecular subgroups and overall survival in pediatric medulloblastoma: Preliminary …
Introduction Medulloblastoma (MB) is a malignant, heterogenous brain tumor. Advances in
molecular profiling have led to identifying four molecular subgroups of MB (WNT, SHH …
molecular profiling have led to identifying four molecular subgroups of MB (WNT, SHH …
Radiomics-based convolutional neural network for brain tumor segmentation on multiparametric magnetic resonance imaging
Accurate segmentation of gliomas on routine magnetic resonance image (MRI) scans plays
an important role in disease diagnosis, prognosis, and patient treatment planning. We …
an important role in disease diagnosis, prognosis, and patient treatment planning. We …
Radiomic deformation and textural heterogeneity (r-depth) descriptor to characterize tumor field effect: Application to survival prediction in glioblastoma
The concept of tumor field effect implies that cancer is a systemic disease with its impact way
beyond the visible tumor confines. For instance, in Glioblastoma (GBM), an aggressive brain …
beyond the visible tumor confines. For instance, in Glioblastoma (GBM), an aggressive brain …
Interpretable Survival Risk Prediction for High-Grade Glioma Patients via Radiomic Features from Peritumoral Region
R Dhamdhere, S Bharadwaj… - 2024 46th Annual …, 2024 - ieeexplore.ieee.org
Peritumoral edema regions carry prognostic value in patients with high-grade glioma (HGG),
the most invasive type of brain cancer. Recent findings have established the association of …
the most invasive type of brain cancer. Recent findings have established the association of …
Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI
Medulloblastoma (MB) is the most common malignant brain tumor in children. Currently,"
one-size-fits-all" radiation and chemotherapy treatment regimen is employed for treating MB …
one-size-fits-all" radiation and chemotherapy treatment regimen is employed for treating MB …