Dr. Martin Fergie Profile

Dr. Martin Fergie

at Univ of Manchester

SPIE Involvement:

Author

Publications (7)

Proceedings Article | 29 May 2024 Paper

Comparing percent breast density assessments of an AI-based method with expert reader estimates: inter-observer variability

Stepan Romanov, Sacha Howell, Elaine Harkness, D. Gareth Evans, Sue Astley, Martin Fergie

Proceedings Volume 13174, 131740N (2024) https://doi.org/10.1117/12.3027003

KEYWORDS: Artificial intelligence, Breast density, Breast, Mammography, Breast cancer, Risk assessment, Deep learning, Correlation coefficients

Read Abstract +

Proceedings Article | 3 April 2024 Poster + Paper

Maintaining high resolution information in AI-based breast cancer risk prediction

Stepan Romanov, Sacha Howell, Elaine Harkness, D. Gareth Evans, Steven Squires, Martin Fergie, Sue Astley

Proceedings Volume 12927, 129271X (2024) https://doi.org/10.1117/12.3006522

KEYWORDS: Cancer, Mammography, Breast cancer, Deep learning, Breast density, Breast

Read Abstract +

Proceedings Article | 7 April 2023 Poster + Paper

Artificial intelligence for image-based breast cancer risk prediction using attention

Stepan Romanov, Sacha Howell, Elaine Harkness, Megan Bydder, D. Gareth Evans, Steven Squires, Martin Fergie, Sue Astley

Proceedings Volume 12465, 1246526 (2023) https://doi.org/10.1117/12.2653875

KEYWORDS: Risk assessment, Mammography, Cancer, Breast cancer, Machine learning, Cancer detection, Deep learning, Breast

Read Abstract +

Proceedings Article | 7 April 2023 Presentation + Paper

A transformer-based computational approach for H&E to multiplexed immunohistochemistry stain translation

Chang Bian, Tim Cootes, Martin Fergie

Proceedings Volume 12471, 1247108 (2023) https://doi.org/10.1117/12.2653590

KEYWORDS: Data modeling, Education and training, Transformers, Performance modeling, Visualization, Deep learning, Visual process modeling, Multiplexing, Image processing, Diagnostics

Read Abstract +

SPIE Journal Paper | 31 January 2019 Open Access

Prediction of reader estimates of mammographic density using convolutional neural networks

Georgia Ionescu, Martin Fergie, Michael Berks, Elaine Harkness, Johan Hulleman, Adam Brentnall, Jack Cuzick, D. Gareth Evans, Susan Astley

JMI, Vol. 6, Issue 03, 031405, (January 2019) https://doi.org/10.1117/12.10.1117/1.JMI.6.3.031405

KEYWORDS: Breast cancer, Cancer, Breast, Mammography, Convolutional neural networks, Data modeling, Tumor growth modeling, Control systems, Visualization, Tissues

Read Abstract +

DOWNLOAD PAPER

Proceedings Article | 6 July 2018 Paper

Using a convolutional neural network to predict readers' estimates of mammographic density for breast cancer risk assessment

Georgia Ionescu, Martin Fergie, Michael Berks, Elaine Harkness, Johan Hulleman, Adam Brentnall, Jack Cuzick, D. Gareth Evans, Susan Astley

Proceedings Volume 10718, 107180D (2018) https://doi.org/10.1117/12.2318464

KEYWORDS: Breast, Mammography, Cancer, Breast cancer, Convolutional neural networks, Network architectures, Health sciences

Read Abstract +

Proceedings Article | 6 March 2018 Presentation + Paper

Quantifying cell-type interactions and their spatial patterns as prognostic biomarkers in follicular lymphoma

Anna Maria Tsakiroglou, Sophie Fitzpatrick, Lilli Nelson, Catharine West, Kim Linton, Kang Zeng, Garry Ashton, Sue Astley, Richard Byers, Martin Fergie

Proceedings Volume 10581, 105810G (2018) https://doi.org/10.1117/12.2293572

KEYWORDS: Lymphoma, Multiplexing, Tissues, Proteins, Cancer, Feature extraction

Read Abstract +

Showing 5 of 7 publications

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years