Introduction to radiomics and radiogenomics in neuro-oncology: implications and challenges

N Beig, K Bera, P Tiwari - Neuro-Oncology Advances, 2020 - academic.oup.com
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 …

RadioTransformer: A cascaded global-focal transformer for visual attention–guided disease classification

M Bhattacharya, S Jain, P Prasanna - European Conference on Computer …, 2022 - Springer
In this work, we present RadioTransformer, a novel student-teacher transformer framework,
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

Y Suter, U Knecht, M Alão, W Valenzuela, E Hewer… - Cancer Imaging, 2020 - Springer
Background This study aims to identify robust radiomic features for Magnetic Resonance
Imaging (MRI), assess feature selection and machine learning methods for overall survival …

Gazeradar: A gaze and radiomics-guided disease localization framework

M Bhattacharya, S Jain, P Prasanna - International Conference on Medical …, 2022 - Springer
We present GazeRadar, a novel radiomics and eye gaze-guided deep learning architecture
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

S Pálsson, S Cerri, HS Poulsen, T Urup, I Law… - Scientific Reports, 2022 - nature.com
Survival prediction models can potentially be used to guide treatment of glioblastoma
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 …

S Iyer, M Ismail, B Tamrazi, R Salloum… - Frontiers in …, 2022 - frontiersin.org
Introduction Medulloblastoma (MB) is a malignant, heterogenous brain tumor. Advances in
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

P Prasanna, A Karnawat, M Ismail… - Journal of Medical …, 2019 - spiedigitallibrary.org
Accurate segmentation of gliomas on routine magnetic resonance image (MRI) scans plays
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

M Ismail, P Prasanna, K Bera… - IEEE transactions on …, 2022 - ieeexplore.ieee.org
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 …

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 …

Deformation heterogeneity radiomics to predict molecular subtypes of pediatric Medulloblastoma on routine MRI

S Iyer, M Ismail, B Tamrazi, A Margol… - Medical Imaging …, 2019 - spiedigitallibrary.org
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 …