Publications

Tianyu Zhang

2024

  1. To deform or not: treatment-aware longitudinal registration for breast DCE-MRI during neoadjuvant chemotherapy via unsupervised keypoints detection
    L. Han, T. Tan, T. Zhang, Y. Gao, X. Wang, V. Longo, S. Ventura-Díaz, A. D'Angelo, J. Teuwen, R. Mann, 2024
    ArXiv
    Abstract
  2. IMPORTANT-Net: Integrated MRI multi-parametric increment fusion generator with attention network for synthesizing absent data
    Information Fusion
    T. Zhang, T. Tan, L. Han, X. Wang, Y. Gao, J. Van Dijk, A. Portaluri, A. Gonzalez-Huete, A. D’Angelo, C. Lu, J. Teuwen, R. Beets-Tan, Y. Sun, R. Mann, 2024, 108
    doi preprints paper (open access)
    Abstract
  3. Ordinal Learning: Longitudinal Attention Alignment Model for Predicting Time to Future Breast Cancer Events from Mammograms
    Lecture Notes in Computer Science
    X. Wang, T. Tan, Y. Gao, E. Marcus, L. Han, A. Portaluri, T. Zhang, C. Lu, X. Liang, R. Beets-Tan, J. Teuwen, R. Mann, 2024
    doi
    Abstract
  4. Improving Neoadjuvant Therapy Response Prediction by Integrating Longitudinal Mammogram Generation with Cross-Modal Radiological Reports: A Vision-Language Alignment-Guided Model
    Lecture Notes in Computer Science
    Y. Gao, H. Zhou, X. Wang, T. Zhang, L. Han, C. Lu, X. Liang, J. Teuwen, R. Beets-Tan, T. Tan, R. Mann, 2024
    doi
    Abstract

2023

  1. Predicting up to 10 year breast cancer risk using longitudinal mammographic screening history
    X. Wang, T. Tan, Y. Gao, R. Su, T. Zhang, L. Han, J. Teuwen, A. D’Angelo, C. A. Drukker, M. K. Schmidt, R. Beets-Tan, N. Karssemeijer, R. Mann, 2023
    doi
    Abstract
  2. Visualize what you learn: a well-explainable joint-learning framework based on multi-view mammograms and associated reports
    Y. Gao, H. Zhou, X. Wang, T. Zhang, R. Tan, L. Han, L. Estacio, A. D’Angelo, J. Teuwen, R. Mann, T. Tan, 2023
    doi
    Abstract
  3. RadioLOGIC, a healthcare model for processing electronic health records and decision-making in breast disease
    Cell Reports Medicine
    T. Zhang, T. Tan, X. Wang, Y. Gao, L. Han, L. Balkenende, A. D’Angelo, L. Bao, H. M. Horlings, J. Teuwen, R. G. Beets-Tan, R. M. Mann, 2023
    doi paper (open access)
    Abstract
  4. Synthesis of Contrast-Enhanced Breast MRI Using T1- and Multi-b-Value DWI-Based Hierarchical Fusion Network with Attention Mechanism
    Lecture Notes in Computer Science
    T. Zhang, L. Han, A. D’Angelo, X. Wang, Y. Gao, C. Lu, J. Teuwen, R. Beets-Tan, T. Tan, R. Mann, 2023
    doi
    Abstract
  5. Synthesis-based imaging-differentiation representation learning for multi-sequence 3D/4D MRI
    Medical Image Analysis
    L. Han, T. Tan, T. Zhang, Y. Huang, X. Wang, Y. Gao, J. Teuwen, R. Mann, 2023
    doi
    Abstract
  6. Predicting breast cancer types on and beyond molecular level in a multi-modal fashion
    npj Breast Cancer
    T. Zhang, T. Tan, L. Han, L. Appelman, J. Veltman, R. Wessels, K. M. Duvivier, C. Loo, Y. Gao, X. Wang, H. M. Horlings, R. G. H. Beets-Tan, R. M. Mann, 2023, 9;(1)
    doi paper (open access)
    Abstract