Eric M. Rohren

Eric M. Rohren, MD, PhD

Full Affliliate Member, Research Institute
Houston Methodist


Publications

Social Determinants of Health Framework to Identify and Reduce Barriers to Imaging in Marginalized Communities
Elmohr, MM, Javed, Z, Dubey, P, Jordan, JE, Shah, L, Nasir, K, Rohren, EM & Lincoln, CM 2024, , Radiology, vol. 310, no. 2, 223097. https://doi.org/10.1148/radiol.223097

The role of artificial intelligence in supporting person-centred care
Currie, G, Rohren, E & Hawk, KE 2024, . in Person-Centred Care in Radiology: International Perspectives on High-Quality Care. CRC Press, pp. 343-362. https://doi.org/10.1201/9781003310143-29

Generative Artificial Intelligence Biases, Limitations and Risks in Nuclear Medicine: An Argument for Appropriate Use Framework and Recommendations
Currie, GM, Hawk, KE & Rohren, EM 2024, , Seminars in Nuclear Medicine. https://doi.org/10.1053/j.semnuclmed.2024.05.005

Toward Integrated Independence Johannes Czernin Discusses the Future of Theranostics with Ebrahim Delpassand, Eric Rohren, andWolfgangWeber
Delpassand, ES, Rohren, EM, Weber, WA & Czernin, J 2023, , Journal of Nuclear Medicine, vol. 64, no. 9, pp. 1361-1363. https://doi.org/10.2967/jnumed.123.266395

Promoting a Robust Pipeline for Nuclear Medicine Practitioners
Rohren, EM 2023, , Academic Radiology, vol. 30, no. 4, pp. 763-764. https://doi.org/10.1016/j.acra.2023.01.006

The deep radiomic analytics pipeline
Currie, G & Rohren, E 2022, , Veterinary Radiology and Ultrasound, vol. 63 Suppl 1, no. S1, pp. 889-896. https://doi.org/10.1111/vru.13147

Intelligent imaging: Applications of machine learning and deep learning in radiology
Currie, G & Rohren, E 2022, , Veterinary Radiology and Ultrasound, vol. 63 Suppl 1, no. S1, pp. 880-888. https://doi.org/10.1111/vru.13144

DOTATATE Uptake in an Axillary Lymph Node After COVID-19 Vaccination
Brophy, J, Henkle, G & Rohren, EM 2022, , Clinical Nuclear Medicine, vol. 47, no. 2, pp. 174-175. https://doi.org/10.1097/RLU.0000000000003847

Whole-body tumor burden in PET/CT expert review
Santos, DF, Takahashi, ME, Camacho, M, de Lima, MDCL, Amorim, BJ, Rohren, EM & Etchebehere, E 2023, , Clinical and Translational Imaging, vol. 11, no. 1, pp. 5-22. https://doi.org/10.1007/s40336-022-00517-5

The transformational potential of molecular radiomics
Currie, G, Hawk, KE & Rohren, E 2023, , Journal of Medical Radiation Sciences, vol. 70 Suppl 2, no. Suppl 2, pp. 77-88. https://doi.org/10.1002/jmrs.626

Radiation Dosimetry, Artificial Intelligence and Digital Twins: Old Dog, New Tricks
Currie, GM & Rohren, EM 2023, , Seminars in Nuclear Medicine, vol. 53, no. 3, pp. 457-466. https://doi.org/10.1053/j.semnuclmed.2022.10.007

A Multidisciplinary Approach to Cancer: A Radiologist’s View
Rohren, EM 2022, . in Oncologic Imaging: A Multidisciplinary Approach. Elsevier, pp. 1-6. https://doi.org/10.1016/B978-0-323-69538-1.00001-X

Integration of Artificial Intelligence, Machine Learning, and Deep Learning into Clinically Routine Molecular Imaging
Currie, G & Rohren, E 2022, . in Artificial Intelligence/Machine Learning in Nuclear Medicine and Hybrid Imaging. Springer International Publishing, pp. 87-108. https://doi.org/10.1007/978-3-031-00119-2_7

Delayed FDG PET Provides Superior Glioblastoma Conspicuity Compared to Conventional Image Timing
Johnson, JM, Chen, MM, Rohren, EM, Prabhu, S, Chasen, B, Mawlawi, O, Liu, HL & Gule-Monroe, MK 2021, , Frontiers in Neurology, vol. 12, 740280, pp. 740280. https://doi.org/10.3389/fneur.2021.740280

Radioiodine Imaging and Treatment in Thyroid Disorders
Varghese, J, Rohren, E & Guofan, X 2021, , Neuroimaging Clinics of North America, vol. 31, no. 3, pp. 337-344. https://doi.org/10.1016/j.nic.2021.04.003

Pitfalls in Interpretation of PET/CT in the Chest
Strange, C, Shroff, GS, Truong, MT & Rohren, EM 2021, , Seminars in Ultrasound, CT and MRI, vol. 42, no. 6, pp. 588-598. https://doi.org/10.1053/j.sult.2021.04.017

Social Asymmetry, Artificial Intelligence and the Medical Imaging Landscape
Currie, G & Rohren, E 2022, , Seminars in Nuclear Medicine, vol. 52, no. 4, pp. 498-503. https://doi.org/10.1053/j.semnuclmed.2021.11.011

Low-dose versus High-dose Carfilzomib with Dexamethasone (S1304) in Patients with Relapsed-Refractory Multiple Myeloma
Ailawadhi, S, Sexton, R, Lentzsch, S, Abidi, MH, Voorhees, PM, Cohen, AD, Rohren, EM, Heitner, S, Kelly, K, Mackler, NJ, Baer, DM, Hoering, A, Durie, B & Orlowski, RZ 2020, , Clinical Cancer Research, vol. 26, no. 15, pp. 3969-3978. https://doi.org/10.1158/1078-0432.CCR-19-1997

Ethical principles for the application of artificial intelligence (AI) in nuclear medicine
Currie, G, Hawk, KE & Rohren, EM 2020, , European Journal of Nuclear Medicine and Molecular Imaging, vol. 47, no. 4, pp. 748-752. https://doi.org/10.1007/s00259-020-04678-1

Intelligent Imaging in Nuclear Medicine: the Principles of Artificial Intelligence, Machine Learning and Deep Learning
Currie, G & Rohren, E 2021, , Seminars in Nuclear Medicine, vol. 51, no. 2, pp. 102-111. https://doi.org/10.1053/j.semnuclmed.2020.08.002

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