Area of research
Radiology, Nuclear Medicine and Imaging · Artificial Intelligence
Research interest
Research interests include Radiomics and Machine Learning in Medical Imaging, Advanced MRI Techniques and Applications, AI in cancer detection, and Ultrasound and Hyperthermia Applications.
BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023
Analysis of the BraTS 2023 Intracranial Meningioma Segmentation Challenge
The Brain Tumor Segmentation (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI
Metrics reloaded: recommendations for image analysis validation
Understanding metric-related pitfalls in image analysis validation
NCI Cancer Research Data Commons: Resources to Share Key Cancer Data
Fair evaluation of federated learning algorithms for automated breast density classification: The results of the 2022 ACR-NCI-NVIDIA federated learning challenge
The Brain Tumor Segmentation - Metastases (BraTS-METS) Challenge 2023: Brain Metastasis Segmentation on Pre-treatment MRI.
PubMed 2024cited by 4position: middle
Operational Ontology for Oncology (O3): A Professional Society-Based, Multistakeholder, Consensus-Driven Informatics Standard Supporting Clinical and Research Use of Real-World Data From Patients Treated for Cancer
A Competition, Benchmark, Code, and Data for Using Artificial Intelligence to Detect Lesions in Digital Breast Tomosynthesis
Reproducibility of Deep Learning Algorithms Developed for Medical Imaging Analysis: A Systematic Review
Understanding metric-related pitfalls in image analysis validation
The Medical Segmentation Decathlon
AAPM Task Group 241: A medical physicist’s guide to MRI‐guided focused ultrasound body systems
Standardization in Quantitative Imaging: A Multicenter Comparison of Radiomic Features from Different Software Packages on Digital Reference Objects and Patient Data Sets
Introduction to special issue on datasets hosted in The Cancer Imaging Archive (TCIA)
Autosegmentation for thoracic radiation treatment planning: A grand challenge at AAPM 2017
PROSTATEx Challenges for computerized classification of prostate lesions from multiparametric magnetic resonance images
Lung Cancer Radiomics: Highlights from the IEEE Video and Image Processing Cup 2018 Student Competition [SP Competitions]
Machine Learning Applications in Head and Neck Radiation Oncology: Lessons From Open-Source Radiomics Challenges
Simulation, Image Processing, and Ultrasound Systems for Assisted Diagnosis and Navigation
Advancing The Cancer Genome Atlas glioma MRI collections with expert segmentation labels and radiomic features
Noninvasive Targeted Transcranial Neuromodulation via Focused Ultrasound Gated Drug Release from Nanoemulsions
Matched computed tomography segmentation and demographic data for oropharyngeal cancer radiomics challenges
LUNGx Challenge for computerized lung nodule classification
Computational Challenges and Collaborative Projects in the NCI Quantitative Imaging Network
Guest Editorial: LUNGx Challenge for computerized lung nodule classification: reflections and lessons learned
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS)
Nanoparticles for cancer imaging: The good, the bad, and the promise