Publications

2023:

Provenzano, D.; Melnyk, O.; Imtiaz, D.; McSweeney, B.; Nemirovsky, D.; Wynne, M.; Whalen, M.; Rao, Y.J.; Loew, M.; Haji-Momenian, S. Machine Learning Algorithm Accuracy Using Single- versus Multi-Institutional Image Data in the Classification of Prostate MRI Lesions. Appl. Sci. 2023, 13, 1088. https://doi.org/10.3390/app13021088
Bakouny Z, Labaki C, Grover P, Provenzano D, et al. Interplay of Immunosuppression and Immunotherapy Among Patients With Cancer and COVID-19. JAMA Oncol. 2023;9(1):128–134. doi:10.1001/jamaoncol.2022.5357
Provenzano, D., Loew, M., S., Haji-Momenian, (2022). Exploring the Explainability of Machine Learning Algorithms for Prostate Cancer. In 2022 IEEE Applied Imagery Pattern Recognition Workshop (AIPR). 2022 IEEE Applied Imagery Pattern Recognition Workshop (AIPR). IEEE.

2022:

Provenzano D, Aghdam H, Goyal S, Loew L, Rao Y. 3D-Printing in Radiation Oncology: Development and Validation of Custom 3D-Printed Brachytherapy Alignment Device and Phantom. bioRxiv 2022.07.03.498548; doi: https://doi.org/10.1101/2022.07.03.498548
Thomas, R. J., Provenzano, D., Goyal, S., Loew, M., Lopez-Acevedo, M., Long, B., Chappell, N. P., & Rao, Y. J. (2022). Trends in guideline-adherent chemoradiation therapy for locally advanced cervical cancer before and after the affordable care act. Gynecologic oncology, S0090-8258(22)00256-6. Advance online publication. https://doi.org/10.1016/j.ygyno.2022.04.015
Provenzano, D., Loew, M. H., Goyal, S., & Rao, Y. J. (2022). Unmasking a Privacy Concern: Potential Identification of Patients in an Immobilization Mask from 3-Dimensional Reconstructions of Simulation Computed Tomography. Practical radiation oncology, 12(2), 120–124. https://doi.org/10.1016/j.prro.2021.09.006

2021:

Provenzano, D., Rao, Y. J., Goyal, S., Haji-Momenian, S., Lichtenberger, J., & Loew, M. (2021). Radiologist vs Machine Learning: A Comparison of Performance in Cancer Imaging. In 2021 IEEE Applied Imagery Pattern Recognition Workshop (AIPR). 2021 IEEE Applied Imagery Pattern Recognition Workshop (AIPR). IEEE. https://doi.org/10.1109/aipr52630.2021.9762211
Provenzano, D., Rao, K., Cifter, G., Taunk, N., Fischer-Valuck, B., Lin, A., Sarfaraz, M., Aghdam, H., Ojong-Ntui, M., Loew, M. H., Goyal, S., & Rao, Y. J. (2021). Adverse events of after-loading high dose rate brachytherapy reported to the United States Food and Drug Administration (FDA). Brachytherapy, 20(5), 1053–1061. https://doi.org/10.1016/j.brachy.2021.04.005

2020:

Li, L., Doroslovacki, M., & Loew, M. (2020). Approximating the gradient of cross-entropy life function. In press, IEEE (Vol 8, 2020), doi: 10.1109/ACCESS.2020.3001531.
Provenzano, D. Washington, S.D. Rao, Y.J. Loew, M. Baraniuk, J. (2020). Machine Learning Detects Pattern of Differences in Functional Magnetic Resonance Imaging (fMRI) Data between Chronic Fatigue Syndrome (CFS) and Gulf War Illness (GWI). In Brain Sciences, 10(7), 456.
Provenzano, D.; Washington, S.D.; Rao, Y.J.; Loew, M.; Baraniuk, J.N. Logistic Regression Algorithm Differentiates Gulf War Illness (GWI) Functional Magnetic Resonance Imaging (fMRI) Data from a Sedentary Control. Brain Sci. 2020, 10, 319.
Provenzano, D., Rao, Y. J., Mitic, K., Obaid, S. N., Berger, J., Goyal, S., & Loew, M. H. (2020). Alternative Qualitative Fit Testing Method for N95 Equivalent Respirators in the Setting of Resource Scarcity at the George Washington University. Cold Spring Harbor Laboratory. https://doi.org/10.1101/2020.04.06.20055368
Provenzano, D.; Rao, Y.J.; Mitic, K.; Obaid, S.N.; Pierce, D.; Huckenpahler, J.; Berger, J.; Goyal, S.; Loew, M.H. Rapid Prototyping of Reusable 3D-Printed N95 Equivalent Respirators at the George Washington University. Preprints 2020, 2020030444 (doi: 10.20944/preprints202003.0444.v1).

2019:

Guan, S., & Loew, M. (2019). Evaluation of generative adversarial network performance based on direct analysis of generated images. In 2019 IEEE Applied Imagery Pattern Recognition Workshop (AIPR), pp. 1-5, doi: 10.1109/AIPR47015.2019.9174595.
Li, L., Doroslovacki, M., & Loew, M. (2019). Loss functions forcing cluster separations for multi-class classification using deep neural networks. In 2019 53rd Asilomar Conference on Signals, Systems, and Computers, pp. 2106-2110, doi: 10.1109/IEEECONF44664.2019.9048718.
Li, L., Doroslovacki, M., & Loew, M. (2019). Discriminant analysis deep neural networks. In 2019 53rd Annual Conference on Information Sciences and Systems (CISS), pp. 1-6, doi: 10.1109/CISS.2019.8692803.
Guan, S., & Loew, M. (2019). Breast cancer detection using synthetic mammograms from generative adversarial networks in convolutional neural networks. Journal of Medical Imaging, 6(3), 031411.
Guan, S., & Loew, M. (2019). Using generative adversarial networks and transfer learning for breast cancer detection by convolutional neural networks. In Medical Imaging 2019: Imaging Informatics for Healthcare, Research, and Applications (Vol. 10954, p. 109541C). International Society for Optics and Photonics.

2018:

Delaney, J., & Loew, M. (2018). Use of infrared hyperspectral imaging (960-1680 nm) and low energy x-radiography to visualize watermarks. In 2018 52nd Annual Conference on Information Sciences and Systems (CISS).
Guan, S., Kamona, N., & Loew, M. (2018). Segmentation of Thermal Breast Images Using Convolutional and Deconvolutional Neural Networks. In 2018 IEEE Applied Imagery Pattern Recognition Workshop (AIPR). IEEE.
Asfour, H., Guan, S., Muselimyan, N., Swift, L., Loew, M., & Sarvazyan, N. (2018). Optimization of wavelength selection for multispectral image acquisition: a case study of atrial ablation lesions. Biomedical optics express, 9(5), 2189-2204.
Shuyue Guan, Huda Asfour, Narine Sarvazyan, Murray Loew, Application of unsupervised learning to hyperspectral imaging of cardiac ablation lesions, Journal of Medical Imaging 5(4), 046003 (2018), doi: 10.1117/1.JMI.5.4.046003
Guan, S., Loew, M., Asfour, H., Sarvazyan, N., & Muselimyan, N. (2018, March). Lesion detection for cardiac ablation from auto-fluorescence hyperspectral images. In Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging (Vol. 10578, p. 105781O). International Society for Optics and Photonics.

2017:

Guan, S., & Loew, M. (2017, October). Breast Cancer Detection Using Transfer Learning in Convolutional Neural Networks. In 2017 IEEE Applied Imagery Pattern Recognition Workshop (AIPR) (pp. 1-8). IEEE.

Others:

J. Ju, M. Loew, B. Ku, and H. Ko, “Hybrid retinal image registration using mutual information and salient features,” Institute of Electronics, Information and Communication Engineers Transactions (Japan). In press, February 2016.
M. H. Loew, M. Alborz, S. Fan, and S. Tirumala, “Thermography for breast cancer detection: basis, methods, and human/computer performance,” Medical Image Perception Society, Proc. Conference XVI, Ghent, Belgium, June 2015.
N. J. Prindeze, H. A. Hoffman, B. C. Carney, L. T. Moffatt, M. H. Loew, and J. W. Shupp, “Evaluation of the variable depth resolution of active dynamic thermography on human skin,” Proc. SPIE, Vol. 9531, Biophotonics South America, 95310P (19 June 2015); doi: 10.1117/12.2180807
D. M. Conover, J. K. Delaney, and M. H. Loew, “Automatic registration and mosaicking of technical images of Old Master paintings,” Applied Physics A, April 2015, DOI 10.1007/s00339-015-9140-1.
K. A. Dooley, S. Lomax, J. G. Zeibel, C. Miliani, P. Ricciardi, A. Hoenigswald, M. Loew, and J. K. Delaney, “Mapping of egg yolk and animal skin glue paint binders in Early Renaissance paintings using near infrared reflectance imaging spectroscopy,” Analyst, 2013,138, 4838-4848, DOI: 10.1039/C3AN00926B.
J. K. Delaney, K. A. Dooley, D. M. Conover, S. Lomax, and M. H. Loew, “Visible and Infrared Imaging Spectroscopy of Paintings,” Technart: Non-destructive and microanalytical techniques in art and cultural heritage, Catania, Italy, April 2015.
J. K. Delaney, K. A. Dooley, D. M. Conover, L. D. Glinsman, S. Lomax, and M. H. Loew, “Application of Visible and Infrared Imaging Spectroscopy to Analyze Paintings,” AAAS 2015 Annual Meeting: Innovations, Information, and Imaging, San Jose, CA.
P. Ricciardi, J. K. Delaney, M. Facini, J. G. Zeibel, M. Picollo, S. Lomax, and M. Loew, “Near Infrared Reflectance Imaging Spectroscopy to Map Paint Binders In Situ on Illuminated Manuscripts,” Angewandte Chemie, Intl. Ed., 2012, Vol. 51, 1-5.
D. M. Conover, J. K. Delaney, P. Ricciardi, and M. H. Loew, “Automatic control-point selection for image registration using disparity fitting,” Proc. SPIE, 8314, 14 February 2012, DOI: 10.1117/12.912471.
M. H. Loew, “Choosing an image fusion method for human observers,” Proc. MIPS XIV (Medical Image Perception Society), Dublin, August 2011.
L. Jiang, W. Zhan, and M. H. Loew, “Toward understanding the complex mechanisms behind breast thermography: an overview for comprehensive numerical study,” Proc. SPIE 7965, Medical Imaging 2011, 79650H (2011).
D. M. Conover, J. K. Delaney, P. Ricciardi, and M. H. Loew, “Towards automatic registration of technical images of works of art,” Proc. SPIE 7869, Electronic Imaging 2011, 78690C (2011)
L. Jiang, W. Zhan, and M. H. Loew, “Modeling static and dynamic thermography of the human breast under elastic deformation,” Phys. Med. Biol., Vol. 56, No.1, 2011, pp. 187-202.
L. Jiang, W. Zhan, and M. H. Loew, “Modeling thermography of the tumorous human breast: from forward problem to inverse problem solving,” Proc. 2010 IEEE Intl. Symp. on Biomedical Imaging: from Nano to Micro, April 2010.
K. J. Oweis, M. M. Berl, W. D. Gaillard, E. S. Duke, K. Blackstone, M. H. Loew, and J. M. Zara, “Topologic analysis and comparison of brain activation in children with epilepsy versus controls: an fMRI study,” Proc. SPIE, Vol. 7626; Medical Imaging 2010: Biomedical Applications in Molecular, Structural, and Functional Imaging, ed. by R. C. Molthen and J. B. Weaver, March 2010. 76261W (9 March 2010); doi: 10.1117/12.843927.
L. Jiang, W. Zhan, and M. H. Loew, “A numerical study of the inverse problem of breast infrared thermography modeling,” Proc. SPIE, Vol. 7626; Medical Imaging 2010: Biomedical Applications in Molecular, Structural, and Functional Imaging, ed. by R. C. Molthen and J. B. Weaver, March 2010. 76260O (9 March 2010); doi: 10.1117/12.844695.