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Thomas Wolfgruber

Thomas Wolfgruber

Postdoctoral Researcher

I am a post-doctoral researcher primarily studying mammography for risk detection using machine learning. As a data scientist and software engineer I support the general scientific and technological goals of the group. My experience ranges from co-authoring scientific papers published in peer-reviewed journals to more day-to-day tasks like server administration.

Publications (13)

  • Deep Learning Enables Large-Scale Shape and Appearance Modeling in Total-Body DXA Imaging
    Bunnell A, Cataldi D, Glaser Y, Wolfgruber T, Heymsfield SB, Zonderman AB, Kelly TL, Sadowski P, Shepherd J
    Lecture notes in computer science, 2025· doi:10.1007/978-3-032-06774-6_20
  • Prediction of mammographic breast density based on clinical breast ultrasound images using deep learning: a retrospective analysis
    Bunnell A, Valdez D, Wolfgruber T, Quon BK, Hung K, Hernandez BY, Seto TB, Killeen J, Miyoshi M, Sadowski P, Shepherd J
    The Lancet Regional Health - Americas, 2025· doi:10.1016/j.lana.2025.101096
  • Deep Learning Predicts Mammographic Breast Density in Clinical Breast Ultrasound Images
    Bunnell A, Valdez D, Wolfgruber T, Quon BK, Hung K, Hernandez BY, Seto TB, Killeen J, Marshall M, Sadowski P, Shepherd J
    arXiv (Cornell University), 2024· doi:10.48550/arxiv.2411.00891
  • Learning a Clinically-Relevant Concept Bottleneck for Lesion Detection in Breast Ultrasound
    Bunnell A, Glaser Y, Valdez D, Wolfgruber T, Altamirano A, González CZ, Hernandez BY, Sadowski P, Shepherd J
    Lecture notes in computer science, 2024· doi:10.1007/978-3-031-72384-1_61
  • Abstract P3-03-02: Can artificial intelligence derived ultrasound breast density provide comparable breast cancer risk estimates to density derived from mammograms
    Valdez D, Bunnell A, Wolfgruber T, Altamirano A, Quon BK, Maskarinec G, Sadowski P, Shepherd J
    Cancer Research, 2023· doi:10.1158/1538-7445.sabcs22-p3-03-02
  • Abstract P3-04-05: Artificial Intelligence Detects, Classifies, and Describes Lesions in Clinical Breast Ultrasound Images
    Bunnell A, Valdez D, Wolfgruber T, Altamirano A, Hernandez BY, Sadowski P, Shepherd J
    Cancer Research, 2023· doi:10.1158/1538-7445.sabcs22-p3-04-05
  • Quantitative Imaging Principles Improves Medical Image Learning
    Leong LT, Wong M, Glaser Y, Wolfgruber T, Heymsfield SB, Peter S, Shepherd J
    arXiv (Cornell University), 2022· doi:10.48550/arxiv.2206.06663
  • Abstract P3-01-13: Comparing portable and clinical ultrasound systems using 3D printed breast phantom inserts
    Valdez D, Fukui J, Wolfgruber T, Leong LT, Maskarinec G, Shepherd J
    Cancer Research, 2022· doi:10.1158/1538-7445.sabcs21-p3-01-13
  • Technical note: Low clinical efficacy, but good acceptability of a point‐of‐care electronic palpation device for breast cancer screening for a lower middle‐income environment
    Valdez D, Cruz T, Rania S, Badowski G, Cassel K, Wolfgruber T, Grosskreutz S, Dulana L, Adonay R, Maskarinec G, Shepherd J
    Medical Physics, 2022· doi:10.1002/mp.15499
  • Deep learning predicts all-cause mortality from longitudinal total-body DXA imaging
    Glaser Y, Shepherd J, Leong LT, Wolfgruber T, Lui L, Sadowski P, Cummings SR
    Communications Medicine, 2022· doi:10.1038/s43856-022-00166-9
  • Dual-energy three compartment breast imaging (3CB) for novel compositional biomarkers to improve detection of malignant lesions
    Leong LT, Malkov S, Drukker K, Niell BL, Sadowski P, Wolfgruber T, Greenwood H, Joe BN, Kerlikowske K, Giger ML, Shepherd J
    Research Square, 2021· doi:10.21203/rs.3.rs-292446/v1
  • Dual-energy three-compartment breast imaging for compositional biomarkers to improve detection of malignant lesions
    Leong LT, Malkov S, Drukker K, Niell BL, Sadowski P, Wolfgruber T, Greenwood H, Joe BN, Kerlikowske K, Giger ML, Shepherd J
    Communications Medicine, 2021· doi:10.1038/s43856-021-00024-0
  • Deep Learning Predicts Interval and Screening-detected Cancer from Screening Mammograms: A Case-Case-Control Study in 6369 Women
    Zhu X, Wolfgruber T, Leong LT, Jensen MR, Scott CG, Winham SJ, Sadowski P, Vachon CM, Kerlikowske K, Shepherd J
    Radiology, 2021· doi:10.1148/radiol.2021203758

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