People_

Dr Moe Suleiman

PhD (Sydney School of Health Sciences), University of Sydney

Phone

+61 2 9351 9465

Email

moe.suleiman@sydney.edu.au

Details

Member of Sydney Southeast Asia Centre

Websites

Dr Suleiman’s research focuses on exploring innovative technologies and techniques that improve the recognition of clinical indicators of disease, whilst minimising risk to the patient. His research on radiation dose optimisation has resulted in significant findings regarding the method utilized for the estimation of absorbed radiation dose; leading to the design of an updated method for the calculation of actual glandular dose and a better estimation of individualised absorbed radiation dose for women undergoing screening mammography.

Research interests

Medical imaging, Breast cancer, Mammography, Digital Breast Tomosynthesis, Lung cancer, Dust disease, Image perception, Radiation dose optimisation.

Current projects

Transforming diagnosis of silicosis: a novel AI approach
CHEST: transforming dust disease detection in Australia.
Gist in the prior and current mammograms
Lifetime risk of radiation induced breast cancer.
The effect of "Time of day" on Radiologists performance.
Assessing the diagnostic efficacy and radiation risk for screening mammography in older women.
Breast compression in mammography.

Transforming diagnosis of silicosis: a novel AI approach

Associations

China Studies Centre

BreastScreen Reader Assessment Strategy

MIOPeG

Awards and honours

The John C Harsanyi Medal for innovation

Themes

Cancer, Medical Imaging

Keywords

Cancer, Diagnostic imaging, Lung cancer, Lung diseases, Radiology

Approaches

Adult, Translational Research

Current research students

Project title	Research student
ASSESSING THE PERFORMANCE OF ARTIFICIAL INTELLIGENCE IN BREAST IMAGING: A COMPARATIVE STUDY ACROSS VARYING LEVELS OF CASE DIFFICULTY	Putu Irma WULANDARI

Publications

By Type

Expand all

Journals

Wong, D., Gandomkar, Z., Lewis, S., Reed, W., Suleiman, M., Siviengphanom, S., Ekpo, E. (2023). Do Reader Characteristics Affect Diagnostic Efficacy in Screening Mammography? A Systematic Review. Clinical Breast Cancer, 23(3), e56-e67. [More Information]
Yapp, K., Suleiman, M., Brennan, P., Ekpo, E. (2023). Periapical Radiography versus Cone Beam Computed Tomography in Endodontic Disease Detection: A Free-response, Factorial Study. The Journal of Endodontics, 49(4), 419-429. [More Information]
Gandomkar, Z., Siviengphanom, S., Suleiman, M., Wong, D., Reed, W., Ekpo, E., Xu, D., Lewis, S., Evans, K., Wolfe, J., Brennan, P. (2023). Reliability of radiologists' first impression when interpreting a screening mammogram. PloS One, 18(2024-04-04 00:00:00). [More Information]
Hooshmand, S., Reed, W., Suleiman, M., Brennan, P. (2023). RRIMS: Radiation Risk in mammography Screening - A Novel model for predicting the lifetime dose and risk of radiation-induced breast cancer from the first screening visit. BJR - Open, 4, 20220028. [More Information]
Hooshmand, S., Reed, W., Suleiman, M., Brennan, P. (2023). RRIMS: Radiation Risk In Mammography Screening — model evaluation. British Journal of Radiology, 96(1152), 20230250. [More Information]
Hooshmand, S., Reed, W., Suleiman, M., Brennan, P. (2022). A review of screening mammography: The benefits and radiation risks put into perspective. Journal of Medical Imaging and Radiation Sciences, 53(1), 147-158. [More Information]
Liu, Q., Suleiman, M., McEntee, M., Soh, B. (2022). Diagnostic reference levels in digital mammography: A systematic review. Journal of Radiological Protection, 42(1), 1-15. [More Information]
Alshabibi, A., Suleiman, M., Albeshan, S., Heard, R., Brennan, P. (2022). Variations in breast cancer detection rates during mammogram-reading sessions: Does experience have an impact? British Journal of Radiology, 95(1129), 20210895. [More Information]
Hooshmand, S., Reed, W., Suleiman, M., Brennan, P. (2021). Breast-iRRISC: a novel model for predicting the individualised lifetime risk of radiation-induced breast cancer from a single screening event. British Journal of Radiology, 94(1117), 20200734. [More Information]
Gandomkar, Z., Siviengphanom, S., Ekpo, E., Suleiman, M., Tavakoli Taba, S., Li, T., Xu, D., Evans, K., Lewis, S., Wolfe, J., Brennan, P. (2021). Global processing provides malignancy evidence complementary to the information captured by humans or machines following detailed mammogram inspection. Scientific Reports, 11(1), 20122. [More Information]
Alshabibi, A., Suleiman, M., Tapia, K., Heard, R., Brennan, P. (2021). Impact of Hours Awake and Hours Slept at Night on Radiologists’ Mammogram Interpretations. Journal of the American College of Radiology, 18(5), 730-738. [More Information]
Hooshmand, S., Reed, W., Suleiman, M., Brennan, P. (2021). Screening Mammography: Diagnostic Efficacy - Issues and Considerations for the 2020s. Radiation Protection Dosimetry, 197(1), 54-62. [More Information]
Alshabibi, A., Suleiman, M., Tapia, K., Brennan, P. (2020). Effects of time of day on radiological interpretation. Clinical Radiology, 75(2), 148-155. [More Information]
Alshabibi, A., Suleiman, M., Tapia, K., Heard, R., Brennan, P. (2020). Impact of time of day on radiology image interpretations. Clinical Radiology, 75(10), 746-756. [More Information]
Suleiman, M., Rickard, M., Brennan, P. (2020). Perfecting detection through education. Radiography, 26, S49-S53. [More Information]
Li, T., Tavakoli Taba, S., Khong, P., Tan, T., Trieu, P., Chan, E., Suleiman, M., Li, Y., Brennan, P., Lewis, S. (2020). Reading high breast density mammograms: Differences in diagnostic performance between radiologists from Hong Kong SAR/guangdong province in China and Australia. Asian Pacific Journal of Cancer Prevention, 21(9), 2623-2629. [More Information]
Rawashdeh, M., Abdelrahman, M., Zaitoun, M., Suleiman, M., AbuTaimai, R., Nusairat, T., Brennan, P. (2019). Accuracy among Jordanian and Australian radiologists reading the same set of test screening cases. Breast Cancer Management, 8(3), 1758-1931. [More Information]
Suleiman, M., Brennan, P., Ekpo, E., Kench, P., McEntee, M. (2018). Integrating mammographic breast density in glandular dose calculation. British Journal of Radiology, 91(1085), 1-7. [More Information]
Suleiman, M., McEntee, M., Cartwright, L., Diffey, J., Brennan, P. (2017). Diagnostic reference levels for digital mammography in New South Wales. Journal of Medical Imaging and Radiation Oncology, 61(1), 48-57. [More Information]
Suleiman, M., Brennan, P., McEntee, M. (2017). Mean glandular dose in digital mammography: a dose calculation method comparison. Journal of Medical Imaging, 4(1), 1-6. [More Information]
Suleiman, M., Brennan, P., McEntee, M. (2015). Diagnostic reference levels in digital mammography: A systematic review. Radiation Protection Dosimetry, 167(4), 608-619. [More Information]

show 18 more

Conferences

Gandomkar, Z., Lewis, S., Siviengphanom, S., Wong, D., Ekpo, E., Suleiman, M., Tao, X., Reed, W., Brennan, P. (2023). False-negative diagnosis might occur due to absence of the global radiomic signature of malignancy on screening mammograms. SPIE Medical Imaging 2023, United States: SPIE. [More Information]
Gandomkar, Z., Lewis, S., Siviengphan, S., Suleiman, M., Wong, D., Reed, W., Ekpo, E., Brennan, P. (2022). Classification and reviewing of prior screening mammograms from screen-detected breast cancer cases. 16th International Workshop on Breast Imaging (IWBI2022), United States: SPIE. [More Information]
Gandomkar, Z., Siviengphanom, S., Suleiman, M., Wong, D., Reed, W., Ekpo, E., Xu, D., Lewis, S., Brennan, P. (2022). The reliability of radiologists' first impression interpreting a screening mammogram. SPIE Medical Imaging 2022, United States: SPIE. [More Information]
Gandomkar, Z., Ekpo, E., Lewis, S., Suleiman, M., Siviengphanom, S., Li, T., Brennan, P. (2021). An end-to-end deep learning model can detect the gist of the abnormal in prior mammograms as perceived by experienced radiologists. Medical Imaging 2021: Image Perception, Observer Performance, and Technology Assessment, United States: SPIE. [More Information]
Alshabibi, A., Suleiman, M., Tapia, K., Heard, R., Brennan, P. (2021). Effect of time awake and hours slept at night on radiologists' interpretations of mammogram images. Medical Imaging 2021: Image Perception, Observer Performance, and Technology Assessment, United States: SPIE. [More Information]
Alshabibi, A., Suleiman, M., Tapia, K., Heard, R., Brennan, P. (2020). Effect of time of day on radiology image interpretations. Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment, Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]
Gandomkar, Z., Ekpo, E., Chen, Z., Suleiman, M., Li, T., Tapia, K., Brennan, P., Lewis, S. (2020). Expert radiologist performance does not appear to impact upon their capability in perceiving the gist of the abnormal on mammograms. 15th International Workshop on Breast Imaging (IWBI 2020), Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]
Gandomkar, Z., Ekpo, E., Lewis, S., Suleiman, M., Tapia, K., Li, T., Tavakoli Taba, S., Trieu, P., Brennan, P. (2020). Investigating the potential of a gist-sensitive computer-aided detection tool. Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment, Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]
Gandomkar, Z., Suleiman, M., Demchig, D., Brennan, P., McEntee, M. (2019). BI-RADS density categorization using deep neural networks. Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment, Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]
Suleiman, M., Brennan, P., McEntee, M. (2016). DICOM organ dose does not accurately represent calculated dose in mammography. SPIE Medical Imaging 2016: Physics of Medical Imaging, USA: SPIE Publications. [More Information]
Suleiman, M., Brennan, P., Kench, P., McEntee, M. (2016). Radiation doses received by women attending BreastScreen NSW in 2014. European Congress of Radiology ECR 2017, Vienna: Springer.

show 8 more

By Year

Expand all

2023

Wong, D., Gandomkar, Z., Lewis, S., Reed, W., Suleiman, M., Siviengphanom, S., Ekpo, E. (2023). Do Reader Characteristics Affect Diagnostic Efficacy in Screening Mammography? A Systematic Review. Clinical Breast Cancer, 23(3), e56-e67. [More Information]
Gandomkar, Z., Lewis, S., Siviengphanom, S., Wong, D., Ekpo, E., Suleiman, M., Tao, X., Reed, W., Brennan, P. (2023). False-negative diagnosis might occur due to absence of the global radiomic signature of malignancy on screening mammograms. SPIE Medical Imaging 2023, United States: SPIE. [More Information]
Yapp, K., Suleiman, M., Brennan, P., Ekpo, E. (2023). Periapical Radiography versus Cone Beam Computed Tomography in Endodontic Disease Detection: A Free-response, Factorial Study. The Journal of Endodontics, 49(4), 419-429. [More Information]
Gandomkar, Z., Siviengphanom, S., Suleiman, M., Wong, D., Reed, W., Ekpo, E., Xu, D., Lewis, S., Evans, K., Wolfe, J., Brennan, P. (2023). Reliability of radiologists' first impression when interpreting a screening mammogram. PloS One, 18(2024-04-04 00:00:00). [More Information]
Hooshmand, S., Reed, W., Suleiman, M., Brennan, P. (2023). RRIMS: Radiation Risk in mammography Screening - A Novel model for predicting the lifetime dose and risk of radiation-induced breast cancer from the first screening visit. BJR - Open, 4, 20220028. [More Information]
Hooshmand, S., Reed, W., Suleiman, M., Brennan, P. (2023). RRIMS: Radiation Risk In Mammography Screening — model evaluation. British Journal of Radiology, 96(1152), 20230250. [More Information]

show 3 more

2022

Hooshmand, S., Reed, W., Suleiman, M., Brennan, P. (2022). A review of screening mammography: The benefits and radiation risks put into perspective. Journal of Medical Imaging and Radiation Sciences, 53(1), 147-158. [More Information]
Gandomkar, Z., Lewis, S., Siviengphan, S., Suleiman, M., Wong, D., Reed, W., Ekpo, E., Brennan, P. (2022). Classification and reviewing of prior screening mammograms from screen-detected breast cancer cases. 16th International Workshop on Breast Imaging (IWBI2022), United States: SPIE. [More Information]
Liu, Q., Suleiman, M., McEntee, M., Soh, B. (2022). Diagnostic reference levels in digital mammography: A systematic review. Journal of Radiological Protection, 42(1), 1-15. [More Information]
Gandomkar, Z., Siviengphanom, S., Suleiman, M., Wong, D., Reed, W., Ekpo, E., Xu, D., Lewis, S., Brennan, P. (2022). The reliability of radiologists' first impression interpreting a screening mammogram. SPIE Medical Imaging 2022, United States: SPIE. [More Information]
Alshabibi, A., Suleiman, M., Albeshan, S., Heard, R., Brennan, P. (2022). Variations in breast cancer detection rates during mammogram-reading sessions: Does experience have an impact? British Journal of Radiology, 95(1129), 20210895. [More Information]

show 2 more

2021

Gandomkar, Z., Ekpo, E., Lewis, S., Suleiman, M., Siviengphanom, S., Li, T., Brennan, P. (2021). An end-to-end deep learning model can detect the gist of the abnormal in prior mammograms as perceived by experienced radiologists. Medical Imaging 2021: Image Perception, Observer Performance, and Technology Assessment, United States: SPIE. [More Information]
Hooshmand, S., Reed, W., Suleiman, M., Brennan, P. (2021). Breast-iRRISC: a novel model for predicting the individualised lifetime risk of radiation-induced breast cancer from a single screening event. British Journal of Radiology, 94(1117), 20200734. [More Information]
Alshabibi, A., Suleiman, M., Tapia, K., Heard, R., Brennan, P. (2021). Effect of time awake and hours slept at night on radiologists' interpretations of mammogram images. Medical Imaging 2021: Image Perception, Observer Performance, and Technology Assessment, United States: SPIE. [More Information]
Gandomkar, Z., Siviengphanom, S., Ekpo, E., Suleiman, M., Tavakoli Taba, S., Li, T., Xu, D., Evans, K., Lewis, S., Wolfe, J., Brennan, P. (2021). Global processing provides malignancy evidence complementary to the information captured by humans or machines following detailed mammogram inspection. Scientific Reports, 11(1), 20122. [More Information]
Alshabibi, A., Suleiman, M., Tapia, K., Heard, R., Brennan, P. (2021). Impact of Hours Awake and Hours Slept at Night on Radiologists’ Mammogram Interpretations. Journal of the American College of Radiology, 18(5), 730-738. [More Information]
Hooshmand, S., Reed, W., Suleiman, M., Brennan, P. (2021). Screening Mammography: Diagnostic Efficacy - Issues and Considerations for the 2020s. Radiation Protection Dosimetry, 197(1), 54-62. [More Information]

show 3 more

2020

Alshabibi, A., Suleiman, M., Tapia, K., Heard, R., Brennan, P. (2020). Effect of time of day on radiology image interpretations. Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment, Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]
Alshabibi, A., Suleiman, M., Tapia, K., Brennan, P. (2020). Effects of time of day on radiological interpretation. Clinical Radiology, 75(2), 148-155. [More Information]
Gandomkar, Z., Ekpo, E., Chen, Z., Suleiman, M., Li, T., Tapia, K., Brennan, P., Lewis, S. (2020). Expert radiologist performance does not appear to impact upon their capability in perceiving the gist of the abnormal on mammograms. 15th International Workshop on Breast Imaging (IWBI 2020), Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]
Alshabibi, A., Suleiman, M., Tapia, K., Heard, R., Brennan, P. (2020). Impact of time of day on radiology image interpretations. Clinical Radiology, 75(10), 746-756. [More Information]
Gandomkar, Z., Ekpo, E., Lewis, S., Suleiman, M., Tapia, K., Li, T., Tavakoli Taba, S., Trieu, P., Brennan, P. (2020). Investigating the potential of a gist-sensitive computer-aided detection tool. Medical Imaging 2020: Image Perception, Observer Performance, and Technology Assessment, Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]
Suleiman, M., Rickard, M., Brennan, P. (2020). Perfecting detection through education. Radiography, 26, S49-S53. [More Information]
Li, T., Tavakoli Taba, S., Khong, P., Tan, T., Trieu, P., Chan, E., Suleiman, M., Li, Y., Brennan, P., Lewis, S. (2020). Reading high breast density mammograms: Differences in diagnostic performance between radiologists from Hong Kong SAR/guangdong province in China and Australia. Asian Pacific Journal of Cancer Prevention, 21(9), 2623-2629. [More Information]

show 4 more

2019

Rawashdeh, M., Abdelrahman, M., Zaitoun, M., Suleiman, M., AbuTaimai, R., Nusairat, T., Brennan, P. (2019). Accuracy among Jordanian and Australian radiologists reading the same set of test screening cases. Breast Cancer Management, 8(3), 1758-1931. [More Information]
Gandomkar, Z., Suleiman, M., Demchig, D., Brennan, P., McEntee, M. (2019). BI-RADS density categorization using deep neural networks. Medical Imaging 2019: Image Perception, Observer Performance, and Technology Assessment, Bellingham: Society of Photo-Optical Instrumentation Engineers (SPIE). [More Information]

2018

Suleiman, M., Brennan, P., Ekpo, E., Kench, P., McEntee, M. (2018). Integrating mammographic breast density in glandular dose calculation. British Journal of Radiology, 91(1085), 1-7. [More Information]

2017

Suleiman, M., McEntee, M., Cartwright, L., Diffey, J., Brennan, P. (2017). Diagnostic reference levels for digital mammography in New South Wales. Journal of Medical Imaging and Radiation Oncology, 61(1), 48-57. [More Information]
Suleiman, M., Brennan, P., McEntee, M. (2017). Mean glandular dose in digital mammography: a dose calculation method comparison. Journal of Medical Imaging, 4(1), 1-6. [More Information]

2016

Suleiman, M., Brennan, P., McEntee, M. (2016). DICOM organ dose does not accurately represent calculated dose in mammography. SPIE Medical Imaging 2016: Physics of Medical Imaging, USA: SPIE Publications. [More Information]
Suleiman, M., Brennan, P., Kench, P., McEntee, M. (2016). Radiation doses received by women attending BreastScreen NSW in 2014. European Congress of Radiology ECR 2017, Vienna: Springer.

2015

Suleiman, M., Brennan, P., McEntee, M. (2015). Diagnostic reference levels in digital mammography: A systematic review. Radiation Protection Dosimetry, 167(4), 608-619. [More Information]

Selected Grants

2021

Transforming diagnosis of silicosis: a novel AI approach, Brennan P, Rickard M, Suleiman M, Gandomkar Z, Tapia K, Xu D, Department of Health and Aged Care (Federal)/MRFF - Emerging Priorities and Consumer Driven Research 2020 Silico

2020

Chest diagnosis- a High level Education Strategy CHEST, Suleiman M, Brennan P, Sommerfeld N, ICare/Research Grant

Faculty of Medicine and Health

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