Ms Ziba Gandomkar

Research Associate

C43A - Jeffrey Miller Admin Building Cumberland Campus
The University of Sydney


Themes

E-Health and Health Care Delivery; Medical Imaging; Cancer Diagnosis and Rehabilitation

Selected publications

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Journals

  • Gandomkar, Z., Tay, K., Brennan, P., Kozuch, E., Mello-Thoms, C. (2018). Can eye-tracking metrics be used to better pair radiologists in a mammogram reading task? Medical Physics, 45(11), 4844-4856. [More Information]
  • Li, T., Tang, L., Gandomkar, Z., Heard, R., Mello-Thoms, C., Shao, Z., Brennan, P. (2018). Mammographic density and other risk factors for breast cancer among women in China. The Breast Journal, 24(3), 426-428. [More Information]
  • Gandomkar, Z., Brennan, P., Mello-Thoms, C. (2018). MuDeRN: Multi-category classification of breast histopathological image using deep residual networks. Artificial Intelligence in Medicine, 88, 14-24. [More Information]
  • Brennan, P., Gandomkar, Z., Ekpo, E., Tapia, K., Trieu, P., Lewis, S., Wolfe, J., Evans, K. (2018). RadioloGISTs can detect the 'GIST' of breast cancer before any overt signs of cancer appear. Scientific Reports, 8(1), 1-12. [More Information]
  • Gandomkar, Z., Tay, K., Brennan, P., Mello-Thoms, C. (2018). Recurrence quantification analysis of radiologists' scanpaths when interpreting mammograms. Medical Physics, 45(7), 3052-3062. [More Information]
  • Gandomkar, Z., Brennan, P., Mello-Thoms, C. (2017). Determining image processing features describing the appearance of challenging mitotic figures and miscounted nonmitotic objects. Journal of Pathology Informatics, 8(34), 1-10. [More Information]
  • Gandomkar, Z., Tay, K., Ryder, W., Brennan, P., Mello-Thoms, C. (2017). iCAP: an individualized model combining gaze parameters and image-based features to predict radiologists' decisions while reading mammograms. IEEE Transactions on Medical Imaging, 36(5), 1066-1075. [More Information]
  • Gandomkar, Z., Brennan, P., Mello-Thoms, C. (2016). Computer-based image analysis in breast pathology. Journal of Pathology Informatics, 7(1), 1-12. [More Information]

Conferences

  • Gandomkar, Z., Brennan, P., Mello-Thoms, C. (2018). A cognitive approach to determine the benefits of pairing radiologists in mammogram reading. SPIE Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment, Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]
  • Gandomkar, Z., Brennan, P., Mello-Thoms, C. (2018). A framework for distinguishing benign from malignant breast histopathological images using deep residual networks. 14th International Workshop on Breast Imaging (IWBI 2018), Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]
  • Gandomkar, Z., Ekpo, E., Lewis, S., Evans, K., Tapia, K., Trieu, P., Wolfe, J., Brennan, P. (2018). Detection of the abnormal GIST in the prior mammograms even with no overt sign of breast cancer. 14th International Workshop on Breast Imaging (IWBI 2018), Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]
  • Gandomkar, M., Sarang, R., Gandomkar, Z. (2018). TrainingPal: An Algorithm for Recognition and Counting Popular Exercises Using Smartphone Sensors. 26th Iranian Conference on Electrical Engineering (ICEE 2018), Mashhad: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Gandomkar, Z., Tay, K., Brennan, P., Mello-Thoms, C. (2017). A model based on temporal dynamics of fixations for distinguishing expert radiologists' scan paths. SPIE Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment. [More Information]
  • Demchig, D., Gandomkar, Z., Brennan, P. (2017). Automatic segmentation of the dense tissue in digital mammograms for BIRADS density categorization. Medical Image Perception Society (MIPS) XVII Conference 2017, United States: S P I E - International Society for Optical Engineering.
  • Gandomkar, Z., Brennan, P., Mello-Thoms, C. (2017). Determining local and contextual features describing appearance of less easily identifiable mitotic figures. SPIE Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment. [More Information]
  • Gandomkar, Z., Tay, K., Ryder, W., Brennan, P., Mello-Thoms, C. (2016). Predicting radiologists' true and false positive decisions in reading mammograms by using gaze parameters and image-based features. Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]
  • Gandomkar, Z., Tay, K., Ryder, W., Brennan, P., Mello-Thoms, C. (2015). iDensity: an automatic Gabor filter-based algorithm for breast density assessment. SPIE Medical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment, Washington USA: SPIE Publications. [More Information]

2018

  • Gandomkar, Z., Brennan, P., Mello-Thoms, C. (2018). A cognitive approach to determine the benefits of pairing radiologists in mammogram reading. SPIE Medical Imaging 2018: Image Perception, Observer Performance, and Technology Assessment, Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]
  • Gandomkar, Z., Brennan, P., Mello-Thoms, C. (2018). A framework for distinguishing benign from malignant breast histopathological images using deep residual networks. 14th International Workshop on Breast Imaging (IWBI 2018), Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]
  • Gandomkar, Z., Tay, K., Brennan, P., Kozuch, E., Mello-Thoms, C. (2018). Can eye-tracking metrics be used to better pair radiologists in a mammogram reading task? Medical Physics, 45(11), 4844-4856. [More Information]
  • Gandomkar, Z., Ekpo, E., Lewis, S., Evans, K., Tapia, K., Trieu, P., Wolfe, J., Brennan, P. (2018). Detection of the abnormal GIST in the prior mammograms even with no overt sign of breast cancer. 14th International Workshop on Breast Imaging (IWBI 2018), Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]
  • Li, T., Tang, L., Gandomkar, Z., Heard, R., Mello-Thoms, C., Shao, Z., Brennan, P. (2018). Mammographic density and other risk factors for breast cancer among women in China. The Breast Journal, 24(3), 426-428. [More Information]
  • Gandomkar, Z., Brennan, P., Mello-Thoms, C. (2018). MuDeRN: Multi-category classification of breast histopathological image using deep residual networks. Artificial Intelligence in Medicine, 88, 14-24. [More Information]
  • Brennan, P., Gandomkar, Z., Ekpo, E., Tapia, K., Trieu, P., Lewis, S., Wolfe, J., Evans, K. (2018). RadioloGISTs can detect the 'GIST' of breast cancer before any overt signs of cancer appear. Scientific Reports, 8(1), 1-12. [More Information]
  • Gandomkar, Z., Tay, K., Brennan, P., Mello-Thoms, C. (2018). Recurrence quantification analysis of radiologists' scanpaths when interpreting mammograms. Medical Physics, 45(7), 3052-3062. [More Information]
  • Gandomkar, M., Sarang, R., Gandomkar, Z. (2018). TrainingPal: An Algorithm for Recognition and Counting Popular Exercises Using Smartphone Sensors. 26th Iranian Conference on Electrical Engineering (ICEE 2018), Mashhad: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2017

  • Gandomkar, Z., Tay, K., Brennan, P., Mello-Thoms, C. (2017). A model based on temporal dynamics of fixations for distinguishing expert radiologists' scan paths. SPIE Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment. [More Information]
  • Demchig, D., Gandomkar, Z., Brennan, P. (2017). Automatic segmentation of the dense tissue in digital mammograms for BIRADS density categorization. Medical Image Perception Society (MIPS) XVII Conference 2017, United States: S P I E - International Society for Optical Engineering.
  • Gandomkar, Z., Brennan, P., Mello-Thoms, C. (2017). Determining image processing features describing the appearance of challenging mitotic figures and miscounted nonmitotic objects. Journal of Pathology Informatics, 8(34), 1-10. [More Information]
  • Gandomkar, Z., Brennan, P., Mello-Thoms, C. (2017). Determining local and contextual features describing appearance of less easily identifiable mitotic figures. SPIE Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment. [More Information]
  • Gandomkar, Z., Tay, K., Ryder, W., Brennan, P., Mello-Thoms, C. (2017). iCAP: an individualized model combining gaze parameters and image-based features to predict radiologists' decisions while reading mammograms. IEEE Transactions on Medical Imaging, 36(5), 1066-1075. [More Information]

2016

  • Gandomkar, Z., Brennan, P., Mello-Thoms, C. (2016). Computer-based image analysis in breast pathology. Journal of Pathology Informatics, 7(1), 1-12. [More Information]
  • Gandomkar, Z., Tay, K., Ryder, W., Brennan, P., Mello-Thoms, C. (2016). Predicting radiologists' true and false positive decisions in reading mammograms by using gaze parameters and image-based features. Medical Imaging 2016: Image Perception, Observer Performance, and Technology Assessment, Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]

2015

  • Gandomkar, Z., Tay, K., Ryder, W., Brennan, P., Mello-Thoms, C. (2015). iDensity: an automatic Gabor filter-based algorithm for breast density assessment. SPIE Medical Imaging 2015: Image Perception, Observer Performance, and Technology Assessment, Washington USA: SPIE Publications. [More Information]

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