HierAdaptMR: Cross-Center Cardiac MRI Reconstruction with Hierarchical Feature Adapters

Ruru Xu; Ilkay Oksuz

doi:10.1007/978-3-032-17734-6_28

HierAdaptMR: Cross-Center Cardiac MRI Reconstruction with Hierarchical Feature Adapters

Ruru Xu
, Ilkay Oksuz^*

^*Bu çalışma için yazışmadan sorumlu yazar

Bilgisayar Mühendisliği Bölümü

Istanbul Technical University

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › Hakem

Özet

Deep learning-based cardiac MRI reconstruction faces significant domain shift challenges when deployed across multiple clinical centers with heterogeneous scanner configurations and imaging protocols. We propose HierAdaptMR, a hierarchical feature adaptation framework that addresses multi-level domain variations through parameter-efficient adapters. Our method employs Protocol-Level Adapters for sequence-specific characteristics and Center-Level Adapters for scanner-dependent variations, built upon a variational unrolling backbone. A Universal Adapter enables generalization to entirely unseen centers through stochastic training that learns center-invariant adaptations. The framework utilizes multi-scale SSIM loss with frequency domain enhancement and contrast-adaptive weighting for robust optimization. Comprehensive evaluation on the CMRxRecon2025 dataset spanning 5+ centers, 10+ scanners, and 9 modalities demonstrates superior cross-center generalization while maintaining reconstruction quality.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers - 16th International Workshop, STACOM 2025, Held in Conjunction with MICCAI 2025, Revised Selected Papers
Editörler	Oscar Camara, Esther Puyol Antón, Charlène Mauge, Alistair Young, Maxime Sermesant, Marta Varela, Yingliang Ma, Rasmus Paulsen, Chengyan Wang, Qian Tao
Yayınlayan	Springer Science and Business Media Deutschland GmbH
Sayfalar	299-310
Sayfa sayısı	12
ISBN (Basılı)	9783032177339
DOI'lar	https://doi.org/10.1007/978-3-032-17734-6_28
Yayın durumu	Yayınlandı - 2026
Etkinlik	16th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2025, Held in Conjunction with MICCAI 2025 - Daejeon, Korea, Republic of Süre: 27 Eyl 2025 → 27 Eyl 2025

Yayın serisi

Adı	Lecture Notes in Computer Science
Hacim	16459 LNCS
ISSN (Basılı)	0302-9743
ISSN (Elektronik)	1611-3349

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???event.eventtypes.event.conference???	16th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2025, Held in Conjunction with MICCAI 2025
Ülke/Bölge	Korea, Republic of
Şehir	Daejeon
Periyot	27/09/25 → 27/09/25

Bibliyografik not

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.

Belgeye Erişim

10.1007/978-3-032-17734-6_28

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

Xu, R., & Oksuz, I. (2026). HierAdaptMR: Cross-Center Cardiac MRI Reconstruction with Hierarchical Feature Adapters. In O. Camara, E. Puyol Antón, C. Mauge, A. Young, M. Sermesant, M. Varela, Y. Ma, R. Paulsen, C. Wang, & Q. Tao (Eds.), Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers - 16th International Workshop, STACOM 2025, Held in Conjunction with MICCAI 2025, Revised Selected Papers (pp. 299-310). (Lecture Notes in Computer Science; Hac. 16459 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-032-17734-6_28

Xu, Ruru ; Oksuz, Ilkay. / HierAdaptMR : Cross-Center Cardiac MRI Reconstruction with Hierarchical Feature Adapters. Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers - 16th International Workshop, STACOM 2025, Held in Conjunction with MICCAI 2025, Revised Selected Papers. editör / Oscar Camara ; Esther Puyol Antón ; Charlène Mauge ; Alistair Young ; Maxime Sermesant ; Marta Varela ; Yingliang Ma ; Rasmus Paulsen ; Chengyan Wang ; Qian Tao. Springer Science and Business Media Deutschland GmbH, 2026. pp. 299-310 (Lecture Notes in Computer Science).

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author = "Ruru Xu and Ilkay Oksuz",

note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2026.; 16th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2025, Held in Conjunction with MICCAI 2025 ; Conference date: 27-09-2025 Through 27-09-2025",

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Xu, R & Oksuz, I 2026, HierAdaptMR: Cross-Center Cardiac MRI Reconstruction with Hierarchical Feature Adapters. in O Camara, E Puyol Antón, C Mauge, A Young, M Sermesant, M Varela, Y Ma, R Paulsen, C Wang & Q Tao (eds), Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers - 16th International Workshop, STACOM 2025, Held in Conjunction with MICCAI 2025, Revised Selected Papers. Lecture Notes in Computer Science, hac. 16459 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 299-310, 16th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2025, Held in Conjunction with MICCAI 2025, Daejeon, Korea, Republic of, 27/09/25. https://doi.org/10.1007/978-3-032-17734-6_28

HierAdaptMR: Cross-Center Cardiac MRI Reconstruction with Hierarchical Feature Adapters. / Xu, Ruru; Oksuz, Ilkay.
Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers - 16th International Workshop, STACOM 2025, Held in Conjunction with MICCAI 2025, Revised Selected Papers. ed. / Oscar Camara; Esther Puyol Antón; Charlène Mauge; Alistair Young; Maxime Sermesant; Marta Varela; Yingliang Ma; Rasmus Paulsen; Chengyan Wang; Qian Tao. Springer Science and Business Media Deutschland GmbH, 2026. p. 299-310 (Lecture Notes in Computer Science; Hac. 16459 LNCS).

Araştırma çıktısı: Kitap/Rapor/Konferans Bildirisinde Bölüm › Konferans katkısı › Hakem

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T2 - 16th International Workshop on Statistical Atlases and Computational Models of the Heart, STACOM 2025, Held in Conjunction with MICCAI 2025

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PY - 2026

Y1 - 2026

N2 - Deep learning-based cardiac MRI reconstruction faces significant domain shift challenges when deployed across multiple clinical centers with heterogeneous scanner configurations and imaging protocols. We propose HierAdaptMR, a hierarchical feature adaptation framework that addresses multi-level domain variations through parameter-efficient adapters. Our method employs Protocol-Level Adapters for sequence-specific characteristics and Center-Level Adapters for scanner-dependent variations, built upon a variational unrolling backbone. A Universal Adapter enables generalization to entirely unseen centers through stochastic training that learns center-invariant adaptations. The framework utilizes multi-scale SSIM loss with frequency domain enhancement and contrast-adaptive weighting for robust optimization. Comprehensive evaluation on the CMRxRecon2025 dataset spanning 5+ centers, 10+ scanners, and 9 modalities demonstrates superior cross-center generalization while maintaining reconstruction quality.

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Xu R, Oksuz I. HierAdaptMR: Cross-Center Cardiac MRI Reconstruction with Hierarchical Feature Adapters. In Camara O, Puyol Antón E, Mauge C, Young A, Sermesant M, Varela M, Ma Y, Paulsen R, Wang C, Tao Q, editörler, Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers - 16th International Workshop, STACOM 2025, Held in Conjunction with MICCAI 2025, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2026. p. 299-310. (Lecture Notes in Computer Science). doi: 10.1007/978-3-032-17734-6_28