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Showing results (51-60 of 106) with videos related to

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IEEE Transactions on Medical Imaging|December 20, 2021
Geometry-Aware Neural Solver for Fast Bayesian Calibration of Brain Tumor ModelsIvan Ezhov, Tudor Mot, Suprosanna Shit, et al.
Computers in Biology and Medicine|January 31, 2026
PARASIDE: An automatic paranasal sinus segmentation and structure analysis tool for magnetic resonance imagingHendrik Möller, Lukas Krautschick, Robert Graf, et al.
Nature Methods|March 13, 2020
Machine learning analysis of whole mouse brain vasculatureMihail Ivilinov Todorov, Johannes Christian Paetzold, Oliver Schoppe, et al.
Neuroimage|January 18, 2026
Towards contrast- and pathology-agnostic clinical fetal brain MRI segmentation using SynthSegZiyao Shang, Misha Kaandorp, Kelly Payette, et al.
BME Frontiers|October 18, 2023
Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer with Deep LearningHailing Liu, Yu Zhao, Fan Yang, et al.
Arxiv|March 18, 2024
A Learnable Prior Improves Inverse Tumor Growth ModelingJonas Weidner, Ivan Ezhov, Michal Balcerak, et al.
IEEE Transactions on Medical Imaging|November 8, 2024
A Learnable Prior Improves Inverse Tumor Growth ModelingJonas Weidner, Ivan Ezhov, Michal Balcerak, et al.
Journal of Medical Imaging (Bellingham, Wash.)|April 8, 2026
In search of truth: evaluating concordance of AI-based anatomy segmentation modelsLena Giebeler, Deepa Krishnaswamy, David Clunie, et al.
IEEE Transactions on Medical Imaging|March 6, 2019
Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans, and Bayesian InferenceJana Lipkova, Panagiotis Angelikopoulos, Stephen Wu, et al.
Physics in Medicine and Biology|September 22, 2022
The federated tumor segmentation (FeTS) tool: an open-source solution to further solid tumor researchSarthak Pati, Ujjwal Baid, Brandon Edwards, et al.
Pageof 11

Showing results (51-60 of 106) with videos related to

Sort By:
Pageof 11
IEEE Transactions on Medical Imaging|December 20, 2021
Geometry-Aware Neural Solver for Fast Bayesian Calibration of Brain Tumor ModelsIvan Ezhov, Tudor Mot, Suprosanna Shit, et al.
Computers in Biology and Medicine|January 31, 2026
PARASIDE: An automatic paranasal sinus segmentation and structure analysis tool for magnetic resonance imagingHendrik Möller, Lukas Krautschick, Robert Graf, et al.
Nature Methods|March 13, 2020
Machine learning analysis of whole mouse brain vasculatureMihail Ivilinov Todorov, Johannes Christian Paetzold, Oliver Schoppe, et al.
Neuroimage|January 18, 2026
Towards contrast- and pathology-agnostic clinical fetal brain MRI segmentation using SynthSegZiyao Shang, Misha Kaandorp, Kelly Payette, et al.
BME Frontiers|October 18, 2023
Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer with Deep LearningHailing Liu, Yu Zhao, Fan Yang, et al.
Arxiv|March 18, 2024
A Learnable Prior Improves Inverse Tumor Growth ModelingJonas Weidner, Ivan Ezhov, Michal Balcerak, et al.
IEEE Transactions on Medical Imaging|November 8, 2024
A Learnable Prior Improves Inverse Tumor Growth ModelingJonas Weidner, Ivan Ezhov, Michal Balcerak, et al.
Journal of Medical Imaging (Bellingham, Wash.)|April 8, 2026
In search of truth: evaluating concordance of AI-based anatomy segmentation modelsLena Giebeler, Deepa Krishnaswamy, David Clunie, et al.
IEEE Transactions on Medical Imaging|March 6, 2019
Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans, and Bayesian InferenceJana Lipkova, Panagiotis Angelikopoulos, Stephen Wu, et al.
Physics in Medicine and Biology|September 22, 2022
The federated tumor segmentation (FeTS) tool: an open-source solution to further solid tumor researchSarthak Pati, Ujjwal Baid, Brandon Edwards, et al.
Pageof 11