References - djkurran/Automated-framework-for-evaluating-microwave-and-multi-modality-breast-images GitHub Wiki

  1. D. Kurrant, A. Baran, J. LoVetri, E. Fear. “Integrating prior information into microwave tomography Part 1: Impact of detail on image quality,” Med. Phys., vol. 44, pp. 6461–6481, 2017, doi: 10.1002/mp.12585.

  2. Saskia A. Otto, Martina Kadin, Michele Casini, Maria A. Torres, Thorsten Blenckner, “A quantitative framework for selecting and validating food web indicators”. Ecological Indicators, vol. 84, pp. 619-631, 2018, ISSN 1470-160X, doi: 10.1016/j.ecolind.2017.05.045.

  3. V. Thada and V. Jaglan, “Comparison of Jaccard, Dice, Cosine Similarity Coefficient To Find Best Fitness Value for Web Retrieved Documents Using Genetic Algorithm”, International Journal of Innovation in Engineering and Technology, vol. 2, no. 4, p. 202-205, 2013.

  4. E. Bolin, W. Lam. “A review of sensitivity, specificity, and likelihood ratios: evaluating the utility of the electrocardiogram as a screening tool in hypertrophic cardiomyopathy”. Congenit Heart Dis.,vol. 8(5), pp. 406-10, 2013, doi: 10.1111/chd.12083.

  5. D. P. Huttenlocher, G. A. Klanderman and W. J. Rucklidge, "Comparing images using the Hausdorff distance," in IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 15, no. 9, pp. 850-863, Sept. 1993, doi: 10.1109/34.232073.

  6. M. Dubuisson and A. K. Jain, "A modified Hausdorff distance for object matching," Proceedings of 12th International Conference on Pattern Recognition, 1994, pp. 566-568 vol.1, doi: 10.1109/ICPR.1994.576361.

  7. B. R. Lavoie, J. Bourqui, E. C. Fear and M. Okoniewski, "Metrics for Assessing the Similarity of Microwave Breast Imaging Scans of Healthy Volunteers," in IEEE Transactions on Medical Imaging, vol. 37, no. 8, pp. 1788-1798, Aug. 2018, doi: 10.1109/TMI.2018.2806878.

  8. E. C. Fear, X. Li, S. C. Hagness and M. A. Stuchly, "Confocal microwave imaging for breast cancer detection: localization of tumors in three dimensions," in IEEE Transactions on Biomedical Engineering, vol. 49, no. 8, pp. 812-822, Aug. 2002, doi: 10.1109/TBME.2002.800759.

  9. M. Omer (2019). Synergistic Combination of Microwaves and Acoustic Signals: Towards Improved Breast Imaging (Unpublished doctoral thesis). University of Calgary, Calgary, AB., doi: http://dx.doi.org/10.11575/PRISM/36159.

  10. Zhou Wang, A. C. Bovik, H. R. Sheikh and E. P. Simoncelli, "Image quality assessment: from error visibility to structural similarity," in IEEE Transactions on Image Processing, vol. 13, no. 4, pp. 600-612, April 2004, doi: 10.1109/TIP.2003.819861.

  11. D. Kurrant, M. Omer, E. Fear. “Automated workflow for evaluating microwave and multi-modality breast images”. IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology, 2023, (Submitted for review).

  12. N. Abdollahi, D. Kurrant, P. Mojabi, M. Omer, E. Fear, and J. LoVetri, "Incorporation of Ultrasonic Prior Information for Improving Quantitative Microwave Imaging of Breast," IEEE Journal on Multiscale and Multiphysics Computational Techniques, vol. 4, pp. 98-110, 2019, doi: 10.1109/JMMCT.2019.2905344.

  13. R. Haralick, L.G. Shapiro. “Computer and Robot Vision”. Addison-Wesley: Boston, MA, USA, vol. I, pp 158-205, 1992.

  14. R. Van den Boomgard, R. van Balen. “Methods for fast morphological image transforms using bitmapped images”. Comput. Vis. Graph. Image Process. Graph. Models Image Process, vol. 54, pp 254-258, 1992.

  15. M. Lazebnik, D. Popovic, L. McCartney, C. B. Watkins, M. J. Lindstrom, J. Harter, S. Sewall, T. Ogilvie, A. Magliocco, T. M. Breslin, et al., “A large-scale study of the ultrawideband microwave dielectric properties of normal breast tissue obtained from reduction surgeries,” Physics in Medicine & Biology, vol. 52, no. 10, p. 2637-2656, 2007.

  16. M. Lazebnik, D. Popovic, L. McCartney, C. B. Watkins, M. J. Lindstrom, J. Harter, S. Sewall, T. Ogilvie, A. Magliocco, T. M. Breslin, et al., “A large-scale study of the ultrawideband microwave dielectric properties of normal, benign and malignant breast tissues obtained from cancer surgeries,” Physics in Medicine & Biology, vol. 52, no. 20, p. 6093, 2007.

  17. D. Kurrant, M. Omer, N. Abdollahi, P. Mojabi, E. Fear, J. LoVetri, “Evaluating Performance of Microwave Image Reconstruction Algorithms: Extracting Tissue Types with Segmentation Using Machine Learning”. J. Imaging, vol. 7, no. 5, 2021, https://doi.org/10.3390/jimaging7010005.

  18. D. Kurrant, N. Abdollahi, M. Omer, P. Mojabi, E. Fear, and J. LoVetri, "MWSegEval—An image analysis toolbox for microwave breast images," SoftwareX, vol. 15, p. 100728, 2021/07/01/ 2021, doi: https://doi.org/10.1016/j.softx.2021.100728.

  19. M. Omer, P. Mojabi, D. Kurrant, J. LoVetri and E. Fear, "Proof-of-Concept of the Incorporation of Ultrasound-Derived Structural Information Into Microwave Radar Imaging," in IEEE Journal on Multiscale and Multiphysics Computational Techniques, vol. 3, pp. 129-139, 2018, doi: 10.1109/JMMCT.2018.2865111.

  20. J. Bourqui, M. Okoniewski and E. C. Fear, "Balanced Antipodal Vivaldi Antenna With Dielectric Director for Near-Field Microwave Imaging," in IEEE Transactions on Antennas and Propagation, vol. 58, no. 7, pp. 2318-2326, July 2010, doi: 10.1109/TAP.2010.2048844.

  21. D. Kurrant, J. Bourqui, C. Curtis and E. Fear, "Evaluation of 3-D Acquisition Surfaces for Radar-Based Microwave Breast Imaging," in IEEE Transactions on Antennas and Propagation, vol. 63, no. 11, pp. 4910-4920, Nov. 2015, doi: 10.1109/TAP.2015.2476415.

  22. E. C. Fear, J. Bourqui, C. Curtis, D. Mew, B. Docktor and C. Romano, "Microwave Breast Imaging With a Monostatic Radar-Based System: A Study of Application to Patients," in IEEE Transactions on Microwave Theory and Techniques, vol. 61, no. 5, pp. 2119-2128, May 2013, doi: 10.1109/TMTT.2013.2255884.

  23. B. Maklad, C. Curtis, Elise C. Fear, Geoffrey G. Messier, "Neighborhood-Based Algorithm to Facilitate the Reduction of Skin Reflections in Radar-Based Microwave Imaging," Progress In Electromagnetics Research B, Vol. 39, 115-139, 2012. doi:10.2528/PIERB11122208

  24. C. Curtis (2015). Factors Affecting Image Quality in Near-field Ultra-wideband Radar Imaging for Biomedical Applications (Unpublished doctoral thesis). University of Calgary, Calgary, AB., doi: http://dx.doi.org/10.11575/PRISM/26144.

  25. B.R. Lavoie, M. Okoniewski, E.C. Fear (2016) Estimating the Effective Permittivity for Reconstructing Accurate Microwave-Radar Images. PLoS ONE 11(9): e0160849. https://doi.org/10.1371/journal.pone.0160849.

  26. Muhammad Adnan Elahi, Martin Glavin, Edward Jones, Martin O'Halloran , "Artifact Removal Algorithms for Microwave Imaging of the Breast," Progress In Electromagnetics Research, Vol. 141, 185-200, 2013. doi:10.2528/PIER13052407

  27. P. Mojabi and J. LoVetri, "Composite Tissue-Type and Probability Image for Ultrasound and Microwave Tomography," in IEEE Journal on Multiscale and Multiphysics Computational Techniques, vol. 1, pp. 26-35, 2016, doi: 10.1109/JMMCT.2016.2560625.

  28. S. Lloyd, "Least squares quantization in PCM," in IEEE Transactions on Information Theory, vol. 28, no. 2, pp. 129-137, March 1982, doi: 10.1109/TIT.1982.1056489.

  29. E. Porter and D. O'Loughlin, "Pathway to Demonstrating Clinical Efficacy of Microwave Breast Imaging: Qualitative and Quantitative Performance Assessment," in IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology, vol. 6, no. 4, pp. 439-448, Dec. 2022, doi: 10.1109/JERM.2022.3218756.