Ms Ziba Gandomkar

Research Associate

A14 - The Quadrangle
The University of Sydney


Themes

Medical Imaging

Selected publications

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Journals

  • 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, Article in press. [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., 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: SPIE Society of Photo-Optical Instrumentation Engineers. [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]

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, Article in press. [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: SPIE Society of Photo-Optical Instrumentation Engineers. [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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