Ethan Ulrich

Medicine · Health Sciences

8h-index306citations18works3.52yr avg
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Research Topics

Radiomics and Machine Learning in Medical Imaging(16), Medical Imaging Techniques and Applications(13), Advanced X-ray and CT Imaging(9), Prostate Cancer Diagnosis and Treatment(4), Prostate Cancer Treatment and Research(4)

Publications18 total

Part II: Effect of different evaluation methods to the application of a computer-aided prostate MRI detection/diagnosis (CADe/CADx) device on reader performance
Current Problems in Diagnostic Radiology·2024· 4 cited
Part I: prostate cancer detection, artificial intelligence for prostate cancer and how we measure diagnostic performance: a comprehensive review
Current Problems in Diagnostic Radiology·2024· 3 cited
Comparison of machine learning methods for detection of prostate cancer using bpMRI radiomics features
Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition·2023
Improving Prostate Cancer Detection With MRI: A Multi-Reader, Multi-Case Study Using Computer-Aided Detection (CAD)
Academic Radiology·2022· 10 cited
Multisite Technical and Clinical Performance Evaluation of Quantitative Imaging Biomarkers from 3D FDG PET Segmentations of Head and Neck Cancer Images
Tomography·2020· 6 citedOpen Access
FDG PET based prediction of response in head and neck cancer treatment: Assessment of new quantitative imaging features
PLoS ONE·2019· 25 citedOpen Access
FLT PET Radiomics for Response Prediction to Chemoradiation Therapy in Head and Neck Squamous Cell Cancer
Tomography·2019· 35 citedOpen Access
Development and implementation of a Joint-Commission compliant phantom program for PET/CT with fully-automated cloud-based analysis.
2018
Automated model‐based quantitative analysis of phantoms with spherical inserts in FDG PET scans
Medical Physics·2017· 15 citedOpen Access
Multi‐site quality and variability analysis of 3D FDG PET segmentations based on phantom and clinical image data
Medical Physics·2016· 27 citedOpen Access
Impact of Contouring Accuracy on Expected Tumor Control Probability for Head and Neck Cancer: Semiautomated Segmentation Versus Manual Contouring
International Journal of Radiation Oncology*Biology*Physics·2016· 6 citedOpen Access
Peer Review #1 of "DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research (v0.1)"
2016Open Access
DICOM for quantitative imaging biomarker development: a standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research
PeerJ·2016· 92 citedOpen Access
Semiautomated segmentation of head and neck cancers in 18F‐FDG PET scans: A just‐enough‐interaction approach
Medical Physics·2016· 71 citedOpen Access
DICOM for quantitative imaging biomarker development: A standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research
2016· 12 citedOpen Access
DICOM for quantitative imaging biomarker development: A standards based approach to sharing clinical data and structured PET/CT analysis results in head and neck cancer research
2016Open Access
DICOM for quantitative imaging biomarker development: A standards based approach to sharing of clinical data and structured PET/CT analysis results in head and neck cancer research
2016Open Access
DICOM for quantitative imaging biomarker development: A standards based approach to sharing of clinical data and structured PET/CT analysis results in head and neck cancer research
2015Open Access

Frequent Co-authors

Reinhard Beichel(14), John M. Buatti(13), Christian Bauer(7), Bartley Brown(7), Bruce A. Smith(7), John J. Sunderland(7), Andriy Fedorov(6), David Clunie(6), Andreas Wahle(6), Michael D. Onken(6), Steve Pieper(6), Ron Kikinis(4), Randall W. Jones(4), Christian Bauer(4), Jörg Riesmeier(3), Kristin A. Plichta(3), Michael M. Graham(3), Jasser Dhaouadi(3), Jörg Riesmeier(3), Ron Kikinis(2)