Dr. Savannah C. Partridge Profile

Dr. Savannah C. Partridge

at Univ of Washington

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Author

Publications (4)

Proceedings Article | 15 February 2021 Presentation + Paper

Intrinsic radiomics phenotypes of DCI from breast DCE-MRI: demonstrating feasibility in interim analysis of the ECOG-ACRIN E4112 trial

Vivian Belenky, Rhea Chitalia, Nickolas Lewis, Debosmita Biswas, Constantine Gatsonis, Jennifer Xiao, Michael Hirano, Sunil Badve, Joseph Sparano, Seema Khan, Kathy Miller, Constance Lehman, Justin Romanoff, Antonio Wolff, Christopher Comstock, Savannah Partridge, Habib Rahbar, Despina Kontos

Proceedings Volume 11597, 115970B (2021) https://doi.org/10.1117/12.2582000

KEYWORDS: Breast, Surveillance, Principal component analysis, Diagnostics, Cancer, Breast cancer, Biopsy, 3D image processing, 3D acquisition

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Proceedings Article | 16 March 2020 Paper

Genetic algorithm for machine learning architecture selection for breast MRI classification

Peter Carras, Carina Pereira, Debosmita Biswas, Christoph Lee, Savannah Partridge, Adam Alessio

Proceedings Volume 11314, 1131422 (2020) https://doi.org/10.1117/12.2547490

KEYWORDS: Genetic algorithms, Breast, Magnetic resonance imaging, Data modeling, Machine learning, Image classification, Performance modeling, Convolutional neural networks, Network architectures

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Proceedings Article | 7 March 2018 Paper

Simulating magnetic resonance images based on a model of tumor growth incorporating microenvironment

Pamela Jackson, Andrea Hawkins-Daarud, Savannah Partridge, Paul Kinahan, Kristin Swanson

Proceedings Volume 10577, 105771D (2018) https://doi.org/10.1117/12.2293645

KEYWORDS: Tumors, Magnetic resonance imaging, Mathematical modeling, Brain, Neuroimaging

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SPIE Journal Paper | 22 January 2018

Distinguishing benign and malignant breast tumors: preliminary comparison of kinetic modeling approaches using multi-institutional dynamic contrast-enhanced MRI data from the International Breast MR Consortium 6883 trial

Anna Sorace, Savannah Partridge, Xia Li, Jack Virostko, Stephanie Barnes, Daniel Hippe, Wei Huang, Thomas Yankeelov

JMI, Vol. 5, Issue 01, 011019, (January 2018) https://doi.org/10.1117/12.10.1117/1.JMI.5.1.011019

KEYWORDS: Magnetic resonance imaging, Breast, Diagnostics, Data modeling, Tumors, Tumor growth modeling, Temporal resolution, Biopsy, Breast cancer, Data acquisition

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