Russell T. Shinohara
Orcid: 0000-0001-8627-8203Affiliations:
- University of Pennsylvania, Philadelphia, PA, USA
According to our database1,
Russell T. Shinohara
authored at least 58 papers
between 2011 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
PARE: A framework for removal of confounding effects from any distance-based dimension reduction method.
PLoS Comput. Biol., 2024
J. Am. Medical Informatics Assoc., 2024
BraTS-PEDs: Results of the Multi-Consortium International Pediatric Brain Tumor Segmentation Challenge 2023.
CoRR, 2024
CoRR, 2024
2023
Image harmonization: A review of statistical and deep learning methods for removing batch effects and evaluation metrics for effective harmonization.
NeuroImage, July, 2023
NeuroImage, May, 2023
The Brain Tumor Segmentation (BraTS) Challenge 2023: Glioma Segmentation in Sub-Saharan Africa Patient Population (BraTS-Africa).
CoRR, 2023
The Brain Tumor Segmentation (BraTS) Challenge 2023: Focus on Pediatrics (CBTN-CONNECT-DIPGR-ASNR-MICCAI BraTS-PEDs).
CoRR, 2023
The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn).
CoRR, 2023
The Brain Tumor Segmentation (BraTS) Challenge 2023: Local Synthesis of Healthy Brain Tissue via Inpainting.
CoRR, 2023
The ASNR-MICCAI Brain Tumor Segmentation (BraTS) Challenge 2023: Intracranial Meningioma.
CoRR, 2023
Penalized Non-Linear Canonical Correlation Analysis for Ordinal Data with Application to the International Classification of Functioning, Disability and Health.
Proceedings of the 2023 SIAM International Conference on Data Mining, 2023
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.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, San Diego, 2023
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, San Diego, 2023
2022
Spatially-enhanced clusterwise inference for testing and localizing intermodal correspondence.
NeuroImage, 2022
Curation of BIDS (CuBIDS): A workflow and software package for streamlining reproducible curation of large BIDS datasets.
NeuroImage, 2022
NeuroImage, 2022
Medical Image Anal., 2022
Cortical lesions, central vein sign, and paramagnetic rim lesions in multiple sclerosis: emerging machine learning techniques and future avenues.
CoRR, 2022
Resampling and harmonization for mitigation of heterogeneity in imaging parameters: a comparative study.
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, San Diego, 2022
Proceedings of the Medical Imaging 2022: Computer-Aided Diagnosis, San Diego, 2022
2021
J. Comput. Graph. Stat., 2021
The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification.
CoRR, 2021
Radiomic features predict local failure-free survival in stage III NSCLC adenocarcinoma treated with chemoradiation.
Proceedings of the Medical Imaging 2021: Computer-Aided Diagnosis, 2021
2020
Increased power by harmonizing structural MRI site differences with the ComBat batch adjustment method in ENIGMA.
NeuroImage, 2020
Sex-biased trajectories of amygdalo-hippocampal morphology change over human development.
NeuroImage, 2020
Longitudinal ComBat: A method for harmonizing longitudinal multi-scanner imaging data.
NeuroImage, 2020
CoRR, 2020
Integrative radiomic analysis for pre-surgical prognostic stratification of glioblastoma patients: from advanced to basic MRI protocols.
Proceedings of the Medical Imaging 2020: Image-Guided Procedures, 2020
2019
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019
2018
NeuroImage, 2018
On testing for spatial correspondence between maps of human brain structure and function.
NeuroImage, 2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge.
CoRR, 2018
MIMoSA: An Approach to Automatically Segment T2 Hyperintense and T1 Hypointense Lesions in Multiple Sclerosis.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018
2017
Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity.
NeuroImage, 2017
Proceedings of the Machine Learning in Medical Imaging - 8th International Workshop, 2017
Dice Overlap Measures for Objects of Unknown Number: Application to Lesion Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2017
Joint Intensity Fusion Image Synthesis Applied to Multiple Sclerosis Lesion Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2017
Proceedings of the Patch-Based Techniques in Medical Imaging, 2017
2016
Abnormality Detection via Iterative Deformable Registration and Basis-Pursuit Decomposition.
IEEE Trans. Medical Imaging, 2016
Statistical estimation of T<sub>1</sub> relaxation times using conventional magnetic resonance imaging.
NeuroImage, 2016
Control-group feature normalization for multivariate pattern analysis of structural MRI data using the support vector machine.
NeuroImage, 2016
NeuroImage, 2016
2015
Interpreting support vector machine models for multivariate group wise analysis in neuroimaging.
Medical Image Anal., 2015
2014
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014
2013
Proceedings of the International Workshop on Pattern Recognition in Neuroimaging, 2013
2011
Population-wide principal component-based quantification of blood-brain-barrier dynamics in multiple sclerosis.
NeuroImage, 2011