Dr. Seyedamir Tavakoli Taba Profile

Dr. Seyedamir Tavakoli Taba

at Univ of Sydney

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Author

Publications (14)

Proceedings Article | 29 March 2024 Presentation + Paper

Deep learning analysis of breast arterial calcifications: a study on predicting cardiovascular disease in women

Mu'ath Ibrahim, Ziba Gandomkar, Mo'ayyad Suleiman, Jessica Yi, Seyedamir Tavakoli Taba, Patrick Brennan

Proceedings Volume 12929, 1292905 (2024) https://doi.org/10.1117/12.3007042

KEYWORDS: Mammography, Deep learning, Image segmentation, Cardiovascular disorders, Breast, Statistical analysis

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Proceedings Article | 29 March 2024 Presentation + Paper

Artificial intelligence can improve cancer detection in a double reading screening mammography scenario

Zhengqiang Jiang, Ziba Gandomkar, Phuong Dung (Yun) Trieu, Seyedamir Tavakoli Taba, Melissa Barron, Sarah Lewis

Proceedings Volume 12929, 1292903 (2024) https://doi.org/10.1117/12.3006376

KEYWORDS: Cancer, Artificial intelligence, Mammography, Tumor growth modeling, Cancer detection, Machine learning, Performance modeling, Breast, Statistical modeling, Histograms

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Proceedings Article | 29 March 2024 Presentation + Paper

Radiologists’ performance in diagnosing silicosis on high-resolution computed tomography (HRCT) scans: an online platform

Jessica Yi, Kriscia Tapia, John Robinson, Ziba Gandomkar, Mo'ayyad Suleiman, Patrick Brennan, Nigel Sommerfeld, Seyedamir Tavakoli Taba

Proceedings Volume 12929, 1292908 (2024) https://doi.org/10.1117/12.3006114

KEYWORDS: Education and training, Opacity, Radiology, Pulmonary disorders, Lung, Diagnostics, Computed tomography, Emphysema, Lymph nodes, Chest, Chest imaging, Silica, Accuracy assessment

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Proceedings Article | 3 April 2023 Presentation + Paper

A comparative study of diagnostic performance and work experience of radiologists in three countries interpreting digital breast tomosynthesis

Elly Gallagher, Phuong Trieu, Ziba Gandomkar, Tong Li, Masoumeh Gity, Patrick Brennan, Sarah Lewis, Seyedamir Tavakoli Taba

Proceedings Volume 12467, 1246709 (2023) https://doi.org/10.1117/12.2651547

KEYWORDS: Digital breast tomosynthesis, Mammography, Education and training, Cancer, Breast cancer, Breast imaging, Diagnostics, Breast, Cancer detection, Radiology

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Proceedings Article | 3 April 2023 Presentation + Paper

How do you solve a problem like concordance? a study of radiologists’ clinical annotations for mammographic AI training

Zhengqiang Jiang, Phuong Trieu, Ziba Gandomkar, Seyedamir Tavakoli Taba, Melissa Barron, Sarah Lewis

Proceedings Volume 12467, 124670M (2023) https://doi.org/10.1117/12.2654147

KEYWORDS: Mammography, Current controlled current source, Artificial intelligence, Education and training, Breast density, Cancer, Cancer detection, Breast cancer

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Proceedings Article | 4 April 2022 Poster + Paper

Energy optimisation of propagation-based phase-contrast computed tomography: a quantitative image quality assessment

Belinda Lim, Sarah Lewis, Benedicta Arhatari, Yakov Nesterets, Sheridan Mayo, Darren Thomposon, Jane Fox, Beena Kumar, Daniel Hausermann, Anton Maksimenko, Christopher Hall, Matthew Dimmock, Darren Lockie, Mary Rickard, Nicola Giannotti, Andrew Peele, Harry Quiney, Timur Gureyev, Patrick Brennan, SeyedamirTavakoli Taba

Proceedings Volume 12031, 120313O (2022) https://doi.org/10.1117/12.2608596

KEYWORDS: Image quality, X-rays, Breast, Signal to noise ratio, X-ray imaging, Quality measurement, Visualization, Visibility, Phase contrast

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Proceedings Article | 9 September 2021 Presentation + Paper

X-ray phase-contrast computed tomography for full breast mastectomy imaging at the Australian Synchrotron

Benedicta Arhatari, Yakov Nesterets, Seyedamir Taba, Anton Maksimenko, Christopher Hall, Andrew Stevenson, Daniel Häsermann, Sarah Lewis, Matthew Dimmock, Darren Thompson, Sheridan Mayo, Harry Quiney, Timur Gureyev, Patrick Brennan

Proceedings Volume 11840, 1184012 (2021) https://doi.org/10.1117/12.2596225

KEYWORDS: Breast, X-rays, Tissues, Synchrotrons, Phase retrieval, X-ray imaging, Image quality, Breast cancer, Computed tomography, Phase contrast

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One of the imaging modalities offered by the Imaging and Medical Beamline (IMBL) at the Australian Synchrotron is Xray phase-contrast propagation-based computed tomography (PB-CT). The unique combination of high coherence and high brightness of radiation produced by synchrotron X-ray sources enables phase contrast imaging with excellent sensitivity to small density differences in soft tissues and tumors. The PB-CT images using spatially coherent radiation show high signal-to-noise ratio (SNR) without reducing the spatial resolution. This is due to the combined effect of forward free-space propagation and the advanced step of phase retrieval in the reconstruction processes that allows to accommodate noisier recorded images. This gives an advantage of potentially reducing the radiation dose delivered to the sample whilst preserving the reconstructed image quality. It is expected that the PB-CT technique will be well suited for diagnostic breast imaging in the near future with the advantage that it could provide better tumor detection and characterization/grading than mammography and other breast imaging modalities/techniques in general. The PB-CT technique is expected to reduce false negative and false positive cancer diagnoses that result from overlapping regions of tissue in 2D mammography and avoid patient pain and discomfort that results from breast compression. The present paper demonstrates that PB-CT produces superior results for imaging low-density materials such as breast mastectomy samples, when compared to the conventional absorption-based CT collected at the same radiation dose. The performance was quantified in terms of both the measured objective image characteristics and the subjective scores from radiological assessments. This work is part of the ongoing research project aimed at the introduction of 3D X-ray medical imaging at the IMBL as innovative tomographic methods to improve the detection and diagnosis of breast cancer. Major progress of this project includes the characterization of a large number of mastectomy samples, both normal and cancerous.

SPIE Journal Paper | 12 July 2021

Effect of x-ray energy on the radiological image quality in propagation-based phase-contrast computed tomography of the breast

Sarina Wan, Benedicta Arhatari, Yakov Nesterets, Sheridan Mayo, Darren Thompson, Jane Fox, Beena Kumar, Zdenka Prodanovic, Daniel Hausermann, Anton Maksimenko, Christopher Hall, Matthew Dimmock, Konstantin Pavlov, Darren Lockie, Mary Rickard, Ziba Gandomkar, Alaleh Alaleh, Elham Vafa, Andrew Peele, Harry Quiney, Sarah Lewis, Timur Gureyev, Patrick Brennan, Seyedamir Tavakoli Taba

JMI, Vol. 8, Issue 05, 052108, (July 2021) https://doi.org/10.1117/12.10.1117/1.JMI.8.5.052108

KEYWORDS: Image quality, X-rays, X-ray imaging, Breast, Sensors, Breast cancer, Tissues, Radio propagation, X-ray detectors, X-ray computed tomography

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Purpose: Breast cancer is the most common cancer in women in developing and developed countries and is responsible for 15% of women’s cancer deaths worldwide. Conventional absorption-based breast imaging techniques lack sufficient contrast for comprehensive diagnosis. Propagation-based phase-contrast computed tomography (PB-CT) is a developing technique that exploits a more contrast-sensitive property of x-rays: x-ray refraction. X-ray absorption, refraction, and contrast-to-noise in the corresponding images depend on the x-ray energy used, for the same/fixed radiation dose. The aim of this paper is to explore the relationship between x-ray energy and radiological image quality in PB-CT imaging. Approach: Thirty-nine mastectomy samples were scanned at the imaging and medical beamline at the Australian Synchrotron. Samples were scanned at various x-ray energies of 26, 28, 30, 32, 34, and 60 keV using a Hamamatsu Flat Panel detector at the same object-to-detector distance of 6 m and mean glandular dose of 4 mGy. A total of 132 image sets were produced for analysis. Seven observers rated PB-CT images against absorption-based CT (AB-CT) images of the same samples on a five-point scale. A visual grading characteristics (VGC) study was used to determine the difference in image quality. Results: PB-CT images produced at 28, 30, 32, and 34 keV x-ray energies demonstrated statistically significant higher image quality than reference AB-CT images. The optimum x-ray energy, 30 keV, displayed the largest area under the curve ( AUCVGC ) of 0.754 (p = 0.009). This was followed by 32 keV (AUCVGC = 0.731, p ≤ 0.001), 34 keV (AUCVGC = 0.723, p ≤ 0.001), and 28 keV (AUCVGC = 0.654, p = 0.015). Conclusions: An optimum energy range (around 30 keV) in the PB-CT technique allows for higher image quality at a dose comparable to conventional mammographic techniques. This results in improved radiological image quality compared with conventional techniques, which may ultimately lead to higher diagnostic efficacy and a reduction in breast cancer mortalities.

Proceedings Article | 22 May 2020 Paper

Impact of digital breast tomosynthesis on readers with different experience

Maram Alakhras, Dana Almousa, Patrick Brennan, Amir Tavakoli Taba, Rula AbuTaimai, Mary Rickard

Proceedings Volume 11513, 1151329 (2020) https://doi.org/10.1117/12.2564280

KEYWORDS: Digital breast tomosynthesis, Mammography, Breast cancer, Digital mammography, Cancer, Breast, Diagnostics, Tomography, New and emerging technologies, Medicine

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Proceedings Article | 22 May 2020 Paper

Getting a-breast of immobilisation needs for the implementation of phase contrast tomography

Sarah Lewis, Nathan Tam, Lucia Mariel Arana Pena, Isabella Juria, Seyedamir Tavakoli Taba, Daniel Hausermann, Patrick Brennan, Chris Hall, Benedicta Arhatari, Giuliana Tromba, Renata Longo, Timur Gureyev

Proceedings Volume 11513, 115131P (2020) https://doi.org/10.1117/12.2563572

KEYWORDS: Breast, Synchrotrons, Phase contrast, Tomography, Breast cancer, Silicon, Tissues, Synchrotron radiation, Medical imaging, Biomedical engineering

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Proceedings Article | 22 May 2020 Paper

Comparison of propagation-based phase-contrast CT and absorption-based CT for breast imaging using synchrotron radiation

Seyedamir Tavakoli Taba, Sarah Lewis, Patrycja Baran, Benedicta Arhatari, Yakov Nesterets, Sheridan Mayo, Darren Thompson, Jane Fox, Beena Kumar, Zdenka Prodanovic, Daniel Hausermann, Anton Maksimenko, Christopher Hall, Matthew Dimmock, Konstantin Pavlov, Andrew Peele, Harry Quiney, Darren Lockie, Giuliana Tromba, Timur Gureyev, Patrick Brennan

Proceedings Volume 11513, 115130T (2020) https://doi.org/10.1117/12.2564053

KEYWORDS: Phase contrast, Image quality, Breast, X-ray computed tomography, X-rays, Tissues, Synchrotrons, Visualization, Breast imaging, Synchrotron radiation, X-ray imaging

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Proceedings Article | 16 March 2020 Presentation + Paper

Investigating the potential of a gist-sensitive computer-aided detection tool

Ziba Gandomkar, Ernest Ekpo, Sarah Lewis, Moayyad Suleiman, Kriscia Tapia, Tong Li, Seyedamir Tavakoli Taba, Phuong Dung Trieu, Patrick Brennan

Proceedings Volume 11316, 113160J (2020) https://doi.org/10.1117/12.2549921

KEYWORDS: Breast cancer, Mammography, Cancer, Medical imaging, Image processing, Breast, Computer aided diagnosis and therapy

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Proceedings Article | 6 July 2018 Paper

Towards clinic-friendly solutions for patient trials in breast cancer phase contrast imaging

Sarah Lewis, Timur Gureyev, Patrycja Baran, Seyedamir Tavakoli Taba, Serena Pacile, Christian Dullin, Giuliana Tromba, Daniel Hausermann, Andrew Peele, Darren Lockie, Patrick Brennan

Proceedings Volume 10718, 107181P (2018) https://doi.org/10.1117/12.2316498

KEYWORDS: Breast, Breast cancer, Mammography, Cancer, Sensors, Synchrotrons, X-rays, X-ray imaging, Tissues

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Proceedings Article | 10 March 2017 Presentation + Paper

Applying a social network analysis (SNA) approach to understanding radiologists' performance in reading mammograms

Seyedamir Tavakoli Taba, Liaquat Hossain, Robert Heard, Patrick Brennan, Warwick Lee, Sarah Lewis

Proceedings Volume 10136, 101360F (2017) https://doi.org/10.1117/12.2254177

KEYWORDS: Social networks, Social network analysis, Mammography, Breast, Radiology, Imaging systems, Medical imaging, Breast cancer, Health sciences, Statistical analysis

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Showing 5 of 14 publications

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