---
res:
  bibo_abstract:
  - "Cardiac T1 mapping provides critical quantitative insights into myocardial tissue
    composition, enabling the assessment of pathologies such as fibrosis, inflammation,
    and edema.\r\nHowever, the inherently dynamic nature of the heart imposes strict
    limits on acquisition\r\ntimes, making high-resolution T1 mapping a persistent
    challenge. Compressed sensing (CS)\r\napproaches have reduced scan durations by
    undersampling k-space and reconstructing images from partial data, and recent
    studies show that jointly optimizing the undersampling\r\npatterns with the reconstruction
    network can substantially improve performance. Still,\r\nmost current T1 mapping
    pipelines rely on static, hand-crafted masks that do not exploit\r\nthe full acceleration
    and accuracy potential. Furthermore, most existing methods do not\r\nlevarage
    the physical T1 decay model in optimization. In this work, we introduce T1-\r\nPILOT:
    an end-to-end method that explicitly incorporates the T1 signal relaxation model\r\ninto
    the sampling–reconstruction framework to guide the learning of non-Cartesian trajectories,
    cross-frame alignment, and T1 decay estimation. Through extensive experiments\r\non
    the CMRxRecon dataset, T1-PILOT significantly outperforms several baseline strategies
    (including learned single-mask and fixed radial or golden-angle sampling schemes),\r\nachieving
    higher T1 map fidelity at greater acceleration factors. In particular, we observe
    consistent gains in PSNR and VIF relative to existing methods, along with marked\r\nimprovements
    in delineating finer myocardial structures. Our results highlight that optimizing
    sampling trajectories in tandem with the physical relaxation model leads to both\r\nenhanced
    quantitative accuracy and reduced acquisition times. Code for reproducing all\r\nexperiments
    and results is available at https://github.com/tamirshor7/T1-PILOT@eng"
  bibo_authorlist:
  - foaf_Person:
      foaf_givenName: Tamir
      foaf_name: Shor, Tamir
      foaf_surname: Shor
  - foaf_Person:
      foaf_givenName: Moti
      foaf_name: Freiman, Moti
      foaf_surname: Freiman
  - foaf_Person:
      foaf_givenName: Chaim
      foaf_name: Baskin, Chaim
      foaf_surname: Baskin
  - foaf_Person:
      foaf_givenName: Alexander
      foaf_name: Bronstein, Alexander
      foaf_surname: Bronstein
      foaf_workInfoHomepage: http://www.librecat.org/personId=58f3726e-7cba-11ef-ad8b-e6e8cb3904e6
    orcid: 0000-0001-9699-8730
  bibo_volume: 315
  dct_date: 2026^xs_gYear
  dct_isPartOf:
  - http://id.crossref.org/issn/2640-3498
  dct_language: eng
  dct_publisher: ML Research Press@
  dct_subject:
  - Cardiac T1 Mapping
  - Trajectory Optimization and Reconstruction
  - PhysicsInformed Deep-Learning
  dct_title: 'T1-PILOT: Physics-informed learned optimized trajectories for T1 mapping
    acceleration@'
...