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Katharina V Hoebel

Showing results (1-10 of 9) with videos related to

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IEEE Transactions on Medical Imaging|April 7, 2023
FDU-Net: Deep Learning-Based Three-Dimensional Diffuse Optical Image ReconstructionBin Deng, Hanxue Gu, Hongmin Zhu, et al.
PLOS Digital Health|April 17, 2026
Leveraging deep learning to infer continuous predictions from ordinal labels in medical imagingKatharina V Hoebel, Andréanne Lemay, John Peter Campbell, et al.
Radiology. Artificial Intelligence|April 12, 2021
Radiomics Repeatability Pitfalls in a Scan-Rescan MRI Study of GlioblastomaKatharina V Hoebel, Jay B Patel, Andrew L Beers, et al.
NPJ Precision Oncology|March 7, 2026
Graph neural network modeling of spatial tumor-immune interactions identifies prognostic cellular niches in non‑small cell lung cancerKatharina V Hoebel, James R Lindsay, Jennifer Altreuter, et al.
World Neurosurgery|July 12, 2019
Machine Learning Models can Detect Aneurysm Rupture and Identify Clinical Features Associated with RuptureMichael A Silva, Jay Patel, Vasileios Kavouridis, et al.
NPJ Digital Medicine|April 8, 2020
Siamese neural networks for continuous disease severity evaluation and change detection in medical imagingMatthew D Li, Ken Chang, Ben Bearce, et al.
Academic Radiology|November 11, 2023
Not without Context-A Multiple Methods Study on Evaluation and Correction of Automated Brain Tumor Segmentations by ExpertsKatharina V Hoebel, Christopher P Bridge, Albert Kim, et al.
Radiology. Artificial Intelligence|January 10, 2024
Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor SegmentationKatharina V Hoebel, Christopher P Bridge, Sara Ahmed, et al.
Journal of the American College of Radiology : JACR|June 28, 2020
Multi-Institutional Assessment and Crowdsourcing Evaluation of Deep Learning for Automated Classification of Breast DensityKen Chang, Andrew L Beers, Laura Brink, et al.
Pageof 1

Showing results (1-10 of 9) with videos related to

Sort By:
Pageof 1
IEEE Transactions on Medical Imaging|April 7, 2023
FDU-Net: Deep Learning-Based Three-Dimensional Diffuse Optical Image ReconstructionBin Deng, Hanxue Gu, Hongmin Zhu, et al.
PLOS Digital Health|April 17, 2026
Leveraging deep learning to infer continuous predictions from ordinal labels in medical imagingKatharina V Hoebel, Andréanne Lemay, John Peter Campbell, et al.
Radiology. Artificial Intelligence|April 12, 2021
Radiomics Repeatability Pitfalls in a Scan-Rescan MRI Study of GlioblastomaKatharina V Hoebel, Jay B Patel, Andrew L Beers, et al.
NPJ Precision Oncology|March 7, 2026
Graph neural network modeling of spatial tumor-immune interactions identifies prognostic cellular niches in non‑small cell lung cancerKatharina V Hoebel, James R Lindsay, Jennifer Altreuter, et al.
World Neurosurgery|July 12, 2019
Machine Learning Models can Detect Aneurysm Rupture and Identify Clinical Features Associated with RuptureMichael A Silva, Jay Patel, Vasileios Kavouridis, et al.
NPJ Digital Medicine|April 8, 2020
Siamese neural networks for continuous disease severity evaluation and change detection in medical imagingMatthew D Li, Ken Chang, Ben Bearce, et al.
Academic Radiology|November 11, 2023
Not without Context-A Multiple Methods Study on Evaluation and Correction of Automated Brain Tumor Segmentations by ExpertsKatharina V Hoebel, Christopher P Bridge, Albert Kim, et al.
Radiology. Artificial Intelligence|January 10, 2024
Expert-centered Evaluation of Deep Learning Algorithms for Brain Tumor SegmentationKatharina V Hoebel, Christopher P Bridge, Sara Ahmed, et al.
Journal of the American College of Radiology : JACR|June 28, 2020
Multi-Institutional Assessment and Crowdsourcing Evaluation of Deep Learning for Automated Classification of Breast DensityKen Chang, Andrew L Beers, Laura Brink, et al.
Pageof 1