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.