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Edward Florez, PhD

E. Florez, T.V. Thomas, C.M. Howard, H.R. Krosravi, S.T. Lirette, A. Fatemi. Machine Learning based on CT Radiomic Features can Predict Residual Tumor from Radiation Changes in Head and Neck Cancer Patients Treated with Definitive Chemoradiotherapy. Biomed Sci Instrum Vol 57(2) April 2021. doi: 10.34107/BiomedSciInstrum.57.04199(View the full-text on page 199 at

E. Florez, V. Vijayakumar, S. Furuie. Dynamic and Metabolic Quantification of Nuclear Medicine images in the PET/CT modality. Res. Biomed. Eng. Published January 2021. doi: 10.1007/s42600-020-00117-0 (View the full-text at

E. Florez, T. Nichols, E. Parker, S. Lirette, C. Howard, A. Fatemi. Multiparametric MR brain tumor imaging as a metric for guided radiation treatment planning. Cureus Journal of Medical Science. 2018; 10(10): e3426. Published 2018 Oct 8. doi:10.7759/cureus.3426

S. Taghizadeh, C. Labuda, C. Chunli Yang, B. Morris, M.R. Kanakamedala, S. Vijayakumar, R. Rey-Dios, W.N. Duggar, E. Florez, A. Fatemi. Optimizing MRI sequences and images for MRI-based stereotactic radiosurgery treatment planning. Reports of Practical Oncology and Radiotherapy. 2018, Volume 24, Issue 1.

E. Florez, T. Nichols, S. Lirette, A. Fatemi. Developing texture analysis technique using Fluid-attenuated inversion recovery (FLAIR) to differentiate tumor from edema in common primary intracranial tumors. SM Journal of Clinical and Medical Imaging. 2018; 4(2): 1023

E. Florez, A. Fatemi, P.P. Claudio, C.M. Howard. Emergence of Radiomics: Novel Methodology Identifying Imaging Biomarkers of Disease in Diagnosis, Response, and Progression. SM Journal of Clinical and Medical Imaging. March 2018; 4(1): 1019

C. Adcock, E. Florez, K. Zand, A. Patel, C. Howard, A. Fatemi. Assessment of treatment response following yttrium-90 transarterial radioembolization of liver malignancies. Cureus Journal of Medical Science. 2018; 10(6): e2895. Published 2018 Jun 29. doi:10.7759/cureus.2895

A. Smith, E. Varney, K. Zand, T. Lewis, R. Sirous, J. York, E. Florez, A. Elkassem, C. Howard-Claudio, M. Roda, E. Parker, E. Scortegagna, D. Joyner, D. Sandlin, A. Newsome, P. Brewster, S. Lirette, M. Griswold. Precision analysis of a quantitative CT liver surface nodularity score. Abdominal Radiology (2018) 43: 3307.

B.C. Allen, E. Florez, R. Sirous, S.T. Lirette, M. Griswold, E.M. Remer, Z.J. Wang, J.E. Bieszczad, K.L. Cox, A.H. Goenka, C.M. Howard-Claudio, H.C. Kang, S.B. Nandwana, R. Sanyal, A.B. Shinagare, J.C. Henagen, J. Storrs, M.S. Davenport, B. Ganeshan, K. Ocain, J. Bryan,  A. Vasanji, B. Rini, A.D. Smith. Comparative Effectiveness of Tumor Response Methods: Standard-of-Care vs. Computer-Assisted Response Evaluation. Journal of Clinical Oncology (JCO) Clinical Cancer Informatics, 2017 35:6_suppl, 432-432 

A. Smith, K. Zand, E. Florez, R. Sirous, D. Shlapak, F. Souza, M. Roda, J. Bryan, A. Vasanji, M. Griswold, S. Lirette. Liver Surface Nodularity Score Allows Prediction of Cirrhosis Decompensation and Death. RSNA – Radiology, 2016.