Dr. Fatemeh Zabihollahy Profile

Dr. Fatemeh Zabihollahy

AI Research Scientist

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Publications (10)

SPIE Journal Paper | 16 June 2022

Transfer learning-based approach for automated kidney segmentation on multiparametric MRI sequences

Rohini Gaikar, Fatemeh Zabihollahy, Mohamed Elfaal, Azar Azad, Nicola Schieda, Eranga Ukwatta

JMI, Vol. 9, Issue 03, 036001, (June 2022) https://doi.org/10.1117/12.10.1117/1.JMI.9.3.036001

KEYWORDS: Kidney, Image segmentation, Data modeling, Magnetic resonance imaging, 3D modeling, Performance modeling, Statistical modeling, 3D image processing, Tumor growth modeling, 3D acquisition

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Proceedings Article | 4 April 2022 Poster + Presentation + Paper

Transfer learning based fully automated kidney segmentation on MR images

Rohini Gaikar, Fatemeh Zabihollahy, Nadia Farrag, Mohamed Elfaal, Nicola Schieda, Eranga Ukwatta

Proceedings Volume 12036, 120361M (2022) https://doi.org/10.1117/12.2607526

KEYWORDS: Kidney, Image segmentation, Magnetic resonance imaging, 3D modeling, Data modeling, 3D image processing, Tumor growth modeling, Algorithm development, Tissues, Cancer

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Proceedings Article | 4 April 2022 Presentation + Paper

A deep learning-based clinical target volume segmentation in female pelvic MRI for radiation therapy planning

Fatemeh Zabihollahy, Akila Viswanathan, Ehud Schmidt, Junghoon Lee

Proceedings Volume 12034, 120341D (2022) https://doi.org/10.1117/12.2611102

KEYWORDS: Image segmentation, Magnetic resonance imaging, Tumors, Cervical cancer, Radiotherapy, Cancer, Volume rendering, Radiation oncology, Visible radiation, Silver

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SPIE Journal Paper | 23 August 2021 Open Access

Detection of COVID-19 from chest x-ray images using transfer learning

Jenita Manokaran, Fatemeh Zabihollahy, Andrew Hamilton-Wright, Eranga Ukwatta

JMI, Vol. 8, Issue S1, 017503, (August 2021) https://doi.org/10.1117/12.10.1117/1.JMI.8.S1.017503

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Proceedings Article | 15 February 2021 Presentation + Paper

Deep learning-based detection of COVID-19 from chest x-ray images

Jenita Manokaran, Fatemeh Zabihollahy, Andrew Hamilton-Wright, Eran Ukwatta

Proceedings Volume 11600, 116000O (2021) https://doi.org/10.1117/12.2581314

KEYWORDS: Chest imaging, Data modeling, Polymers, Image classification, Diagnostics

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Proceedings Article | 18 March 2019 Presentation + Paper

Machine learning-based approach for fully automated segmentation of muscularis propria from histopathology images of intestinal specimens

Conor McKeen, Fatemeh Zabihollahy, Jinu Kurian, Adrian D. Chan, Dina El Demellawy, Eranga Ukwatta

Proceedings Volume 10956, 109560P (2019) https://doi.org/10.1117/12.2512970

KEYWORDS: Image segmentation, Colon, Convolutional neural networks, Network architectures, Machine learning

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Proceedings Article | 15 March 2019 Presentation + Paper

Deep learning based approach for fully automated detection and segmentation of hard exudate from retinal images

F. Zabihollahy, A. Lochbihler, E. Ukwatta

Proceedings Volume 10953, 1095308 (2019) https://doi.org/10.1117/12.2513034

KEYWORDS: Image segmentation, Convolutional neural networks, Image processing algorithms and systems, Macula, Detection and tracking algorithms, Optical discs, Machine learning

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Proceedings Article | 13 March 2019 Paper

Fully-automated segmentation of optic disk from retinal images using deep learning techniques

F. Zabihollahy, E. Ukwatta

Proceedings Volume 10950, 1095032 (2019) https://doi.org/10.1117/12.2512239

KEYWORDS: Image segmentation, Image processing algorithms and systems, Optical discs, Eye, Convolutional neural networks, Algorithm development, Machine learning

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Proceedings Article | 13 March 2019 Paper

Fully automated segmentation of left ventricular myocardium from 3D late gadolinium enhancement magnetic resonance images using a U-net convolutional neural network-based model

Fatemeh Zabihollahy, James White, Eranga Ukwatta

Proceedings Volume 10950, 109503C (2019) https://doi.org/10.1117/12.2512146

KEYWORDS: Image segmentation, 3D image processing, 3D modeling, Magnetic resonance imaging, Resonance enhancement, Tissues, Gadolinium, Machine learning

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Proceedings Article | 27 February 2018 Paper

Myocardial scar segmentation from magnetic resonance images using convolutional neural network

Fatemeh Zabihollahy, James White, Eranga Ukwatta

Proceedings Volume 10575, 105752Z (2018) https://doi.org/10.1117/12.2293518

KEYWORDS: 3D image processing, Convolutional neural networks, Image processing algorithms and systems, Algorithm development, Magnetic resonance imaging, Image segmentation

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Showing 5 of 10 publications

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