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Zhong W, Zhang H, Gao Z, Hau WK, Yang G, Liu X, Xu L. Distraction-aware hierarchical learning for vascular structure segmentation in intravascular ultrasound images. Comput Med Imaging Graph 2024; 115:102381. [PMID: 38640620 DOI: 10.1016/j.compmedimag.2024.102381] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 02/19/2024] [Accepted: 04/09/2024] [Indexed: 04/21/2024]
Abstract
Vascular structure segmentation in intravascular ultrasound (IVUS) images plays an important role in pre-procedural evaluation of percutaneous coronary intervention (PCI). However, vascular structure segmentation in IVUS images has the challenge of structure-dependent distractions. Structure-dependent distractions are categorized into two cases, structural intrinsic distractions and inter-structural distractions. Traditional machine learning methods often rely solely on low-level features, overlooking high-level features. This way limits the generalization of these methods. The existing semantic segmentation methods integrate low-level and high-level features to enhance generalization performance. But these methods also introduce additional interference, which is harmful to solving structural intrinsic distractions. Distraction cue methods attempt to address structural intrinsic distractions by removing interference from the features through a unique decoder. However, they tend to overlook the problem of inter-structural distractions. In this paper, we propose distraction-aware hierarchical learning (DHL) for vascular structure segmentation in IVUS images. Inspired by distraction cue methods for removing interference in a decoder, the DHL is designed as a hierarchical decoder that gradually removes structure-dependent distractions. The DHL includes global perception process, distraction perception process and structural perception process. The global perception process and distraction perception process remove structural intrinsic distractions then the structural perception process removes inter-structural distractions. In the global perception process, the DHL searches for the coarse structural region of the vascular structures on the slice of IVUS sequence. In the distraction perception process, the DHL progressively refines the coarse structural region of the vascular structures to remove structural distractions. In the structural perception process, the DHL detects regions of inter-structural distractions in fused structure features then separates them. Extensive experiments on 361 subjects show that the DHL is effective (e.g., the average Dice is greater than 0.95), and superior to ten state-of-the-art IVUS vascular structure segmentation methods.
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Affiliation(s)
- Wenhao Zhong
- School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, 518055, Guangdong, China
| | - Heye Zhang
- School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, 518055, Guangdong, China
| | - Zhifan Gao
- School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, 518055, Guangdong, China
| | - William Kongto Hau
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China
| | - Guang Yang
- Bioengineering Department and Imperial-X, Imperial College London, W12 7SL London, UK; Cardiovascular Research Centre, Royal Brompton Hospital, SW3 6NP London, UK; National Heart and Lung Institute, Imperial College London, SW7 2AZ London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, WC2R 2LS London, UK
| | - Xiujian Liu
- School of Biomedical Engineering, Sun Yat-sen University, Shenzhen, 518055, Guangdong, China.
| | - Lin Xu
- Department of Geriatric Cardiology, PLA General Hospital of the Southern Theatre Command, Guangzhou, China.
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