mlsanityData to 7 Oct 2026

Recent Advances in Fibrosis and Scar Segmentation from Cardiac MRI: A State-of-the-Art Review and Future Perspectives

arXiv 2106.15707 ↗First posted 28 Jun 2021eess.IV cs.CV physics.med-phcited by 7

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Abstract (arXiv)

Segmentation of cardiac fibrosis and scar are essential for clinical diagnosis and can provide invaluable guidance for the treatment of cardiac diseases. Late Gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) has been successful for its efficacy in guiding the clinical diagnosis and treatment reliably. For LGE CMR, many methods have demonstrated success in accurately segmenting scarring regions. Co-registration with other non-contrast-agent (non-CA) modalities, balanced steady-state free precession (bSSFP) and cine magnetic resonance imaging (MRI) for example, can further enhance the efficacy of automated segmentation of cardiac anatomies. Many conventional methods have been proposed to provide automated or semi-automated segmentation of scars. With the development of deep learning in recent years, we can also see more advanced methods that are more efficient in providing more accurate segmentations. This paper conducts a state-of-the-art review of conventional and current state-of-the-art approaches utilising different modalities for accurate cardiac fibrosis and scar segmentation.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 40 of its 167 references that are in the map. First posted on arXiv 28 Jun 2021.

Builds on

40 of 167 references.

References · 40

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28 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 2; 2023: 0; 2024: 1; 2025: 0; 2026: 4.

7 papers.

  1. 2022Multi-Modality Cardiac Image Computing: A Surveycited by 19
  2. 2024Integrating Deep Learning in Cardiology: A Comprehensive Review of Atrial Fibrillation, Left Atrial Scar Segmentation, and the Frontiers of State-of-the-Art Techniquescited by 2
  3. 2022Automated Diagnosis of Cardiovascular Diseases from Cardiac Magnetic Resonance Imaging Using Deep Learning Models: A Reviewcited by 0
  4. 2026Synthesis of Late Gadolinium Enhancement Images via Implicit Neural Representations for Cardiac Scar Segmentationcited by 0
  5. 2026Few-Shot Left Atrial Wall Segmentation in 3D LGE MRI via Meta-Learningcited by 0
  6. 2026Deep Image Prototype Learning with Geometric Heat-Kernel Priorscited by 0
  7. 2026Multicentre Bi-atrial Segmentation from LGE-MRI for Atrial Fibrillation with a 2D and 3D Frameworkcited by 0