Brain Cancer Imaging Phenomics Toolkit (brain-CaPTk): An Interactive Platform for Quantitative Analysis of Glioblastoma

Textural Features for Image Classification

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Textural features corresponding to textural properties

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Identification of noninvasive imaging surrogates for brain tumor gene-expression modules

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Radiogenomic Mapping of Edema/Cellular Invasion MRI-Phenotypes in Glioblastoma Multiforme

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An image-driven parameter estimation problem for a reaction–diffusion glioma growth model with mass effects

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Outcome Prediction in Patients with Glioblastoma by Using Imaging, Clinical, and Genomic Biomarkers: Focus on the Nonenhancing Component of the Tumor

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SHAPE AND TEXTURE INDEXES APPLICATION TO CELL NUCLEI CLASSIFICATION

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Imaging Surrogates of Infiltration Obtained Via Multiparametric Imaging Pattern Analysis Predict Subsequent Location of Recurrence of Glioblastoma

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Radiogenomics and Imaging Phenotypes in Glioblastoma: Novel Observations and Correlation with Molecular Characteristics

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GLISTRboost: Combining Multimodal MRI Segmentation, Registration, and Biophysical Tumor Growth Modeling with Gradient Boosting Machines for Glioma Segmentation

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Pattern Analysis of Dynamic Susceptibility Contrast-enhanced MR Imaging Demonstrates Peritumoral Tissue Heterogeneity

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In Vivo Detection of EGFRvIII in Glioblastoma via Perfusion Magnetic Resonance Imaging Signature Consistent with Deep Peritumoral Infiltration: The ϕ -Index

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Population-based MRI atlases of spatial distribution are specific to patient and tumor characteristics in glioblastoma

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Robust texture features for response monitoring of glioblastoma multiforme on T1-weighted and T2-FLAIR MR images: A preliminary investigation in terms of identification and segmentation

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Brain Lesions, Introduction

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Automated Tumor Volumetry Using Computer-Aided Image Segmentation

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Individualized Map of White Matter Pathways

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Automated tract extraction via atlas based Adaptive Clustering

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Fast semi-automatic segmentation of focal liver lesions in contrast-enhanced ultrasound, based on a probabilistic model

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NIMG-20. IMAGING PATTERN ANALYSIS REVEALS THREE DISTINCT PHENOTYPIC SUBTYPES OF GBM WITH DIFFERENT SURVIVAL RATES

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Addressing the Challenge of Edema in Fiber Tracking

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MPTH-02. EXTRACELLULAR EGFR289 ACTIVATING MUTATIONS CONFER POORER SURVIVAL AND SUGGEST ENHANCED MOTILITY IN PRIMARY GBMs

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Improving White Matter Tractography by Resolving the Challenges of Edema

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NIMG-05IDENTIFICATION OF IMAGING SIGNATURES OF THE EPIDERMAL GROWTH FACTOR RECEPTOR VARIANT III (EGFRvIII) IN GLIOBLASTOMA

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NIMG-11. HIGHLY-EXPRESSED WILD-TYPE EGFR AND EGFRvIII MUTANT GLIOBLASTOMAS HAVE SIMILAR MRI SIGNATURE, CONSISTENT WITH DEEP PERITUMORAL INFILTRATION

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The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic ClassificationPreprint

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Federated learning enables big data for rare cancer boundary detection

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Radiomics in nuclear medicine: robustness, reproducibility, standardization, and how to avoid data analysis traps and replication crisis

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Emerging Applications of Artificial Intelligence in Neuro-Oncology

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The University of Pennsylvania glioblastoma (UPenn-GBM) cohort: advanced MRI, clinical, genomics, & radiomics

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The Cancer Imaging Phenomics Toolkit (CaPTk): Technical Overview

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Radiogenomic classification for MGMT promoter methylation status using multi-omics fused feature space for least invasive diagnosis through mpMRI scans

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Integrated Biophysical Modeling and Image Analysis: Application to Neuro-Oncology

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Within-Modality Synthesis and Novel Radiomic Evaluation of Brain MRI Scans

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The Federated Tumor Segmentation (FeTS) ChallengePreprint

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Radiomics

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Overall survival prediction in glioblastoma patients using structural magnetic resonance imaging (MRI): advanced radiomic features may compensate for lack of advanced MRI modalities

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GaNDLF: the generally nuanced deep learning framework for scalable end-to-end clinical workflows

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Reproducibility analysis of multi‐institutional paired expert annotations and radiomic features of the Ivy Glioblastoma Atlas Project (Ivy GAP) dataset

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Fused deep learning paradigm for the prediction of o6-methylguanine-DNA methyltransferase genotype in glioblastoma patients: A neuro-oncological investigation

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Standardization of imaging methods for machine learning in neuro-oncology

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Cancer Imaging Phenomics via CaPTk: Multi-Institutional Prediction of Progression-Free Survival and Pattern of Recurrence in Glioblastoma

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CT texture analysis as predictive factor in metastatic lung adenocarcinoma treated with tyrosine kinase inhibitors (TKIs)

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Predicting Short-Term Survival after Gross Total or Near Total Resection in Glioblastomas by Machine Learning-Based Radiomic Analysis of Preoperative MRI

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Skull-Stripping of Glioblastoma MRI Scans Using 3D Deep Learning

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Accurate and Robust Alignment of Differently Stained Histologic Images Based on Greedy Diffeomorphic Registration

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Molecular Subtype Classification in Lower-Grade Glioma with Accelerated DTI

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Development of a robust radiomic biomarker of progression-free survival in advanced non-small cell lung cancer patients treated with first-line immunotherapy

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Federated Learning for Brain Tumor Segmentation Using MRI and Transformers

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MRI-Based Deep Learning Tools for MGMT Promoter Methylation Detection: A Thorough Evaluation

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Expert tumor annotations and radiomics for locally advanced breast cancer in DCE-MRI for ACRIN 6657/I-SPY1

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Enhancing the REMBRANDT MRI collection with expert segmentation labels and quantitative radiomic features

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Towards fair decentralized benchmarking of healthcare AI algorithms with the Federated Tumor Segmentation (FeTS) challenge

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Resampling and harmonization for mitigation of heterogeneity in image parameters of baseline scans

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Synthetic MRI improves radiomics‐based glioblastoma survival prediction

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Comprehensive benchmarking of CNN-based tumor segmentation methods using multimodal MRI data

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Multimodal MRI radiomics based on habitat subregions of the tumor microenvironment for predicting risk stratification in glioblastoma

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Optimization of Deep Learning Based Brain Extraction in MRI for Low Resource Environments

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Increased intratumoral infiltration in IDH wild-type lower-grade gliomas observed with diffusion tensor imaging

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The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn).Preprint

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Repurposing the Public BraTS Dataset for Postoperative Brain Tumour Treatment Response Monitoring

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Estimating Glioblastoma Biophysical Growth Parameters Using Deep Learning Regression

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Accurate and Robust Alignment of Variable-stained Histologic Images Using a General-purpose Greedy Diffeomorphic Registration ToolPreprint

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Author Correction: Predictive equation derived from 6,497 doubly labelled water measurements enables the detection of erroneous self-reported energy intake

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Exploring the Trade-Off between generalist and specialized Models: A center-based comparative analysis for glioblastoma segmentation

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The Brain Tumor Segmentation - Metastases (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI.Preprint

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The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa).Preprint

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Enhancing efficiency in pediatric brain tumor segmentation using a pathologically diverse single-center clinical dataset

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Automatic Classification and Segmentation of Low-Grade Gliomas in Magnetic Resonance Imaging

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Identification of phenomic data in the pathogenesis of cancers of the gastrointestinal (GI) tract in the UK biobank

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Unsupervised Brain Anomaly Detection Using Structure-Preserving Noise Generation and Multi-Scale Dual-Expert Ensembles

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Radiomics analysis to diagnose tumor invasiveness of pulmonary sub-solid nodules from longitudinal pre-surgical CT scans

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Negligible Effect of Brain MRI Data Preprocessing for Tumor SegmentationPreprint

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Leveraging Unlabeled Data for Glioma Molecular Subtype and Survival Prediction

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Resampling and harmonization for mitigation of heterogeneity in imaging parameters: a comparative study

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A radiomics-based model for the outcome prediction in COVID-19 positive patients through deep learning with both longitudinal chest x-ray and chest computed tomography images

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Exploring the prognostic power and biological significance of a robust radiomic biomarker of overall survival in advanced non-small cell lung cancer patients treated with first-line immunotherapy

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Enhancing brain tumor diagnosis with Synthetic MRI

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Enhancing brain tumor diagnosis with Synthetic MRI

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Glioblastoma Multiforme: Exploratory Radiogenomic Analysis by Using Quantitative Image Features

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Radiomics in Brain Tumor: Image Assessment, Quantitative Feature Descriptors, and Machine-Learning Approaches

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Quantitative radiomic profiling of glioblastoma represents transcriptomic expression

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Assessment of brain cancer atlas maps with multimodal imaging features

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Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome

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