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Cascaded Framework with Complementary CMR Information for Myocardial Pathology Segmentation

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Book cover Myocardial Pathology Segmentation Combining Multi-Sequence Cardiac Magnetic Resonance Images (MyoPS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 12554))

Abstract

Myocardial pathology segmentation in cardiac magnetic resonance (CMR) is an important step for patients suffering from myocardial infarction. In this paper, we present a cascaded framework with complementary information for infarcted and edema regions segmentation in CMR sequences. Specifically, instead of using all the three CMR sequences as joint inputs, we first use a 2D U-Net with balanced-Steady State Free Precession (bSSFP) cine sequence to segment the whole heart (left ventricle and myocardium) because bSSFP can capture cardiac motions and present clear boundaries. Then, we crop the whole heart as a region of interest (ROI). Finally, we segment the scar and edema regions in the late gadolinium enhancement (LGE) and T2 CMR sequence ROI. We evaluate the proposed method on MICCAI 2020 MyoPS testing set and achieve Dice scores 0.6283 ± 0.2772 for scar and 0.5419 ± 0.2406 for the combination of edema and scar, which is better than the inter-observer variation of manual scar segmentation (0.5243 ± 0.1578).

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Notes

  1. 1.

    In step 1 and step 3, the networks are trained end-to-end, while the whole framework is not end-to-end.

References

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Acknowledgement

This work is supported by the National Natural Science Foundation of China (No. 91630311, No.11971229). The author highly appreciates the organizers of Myocardial pathology segmentation combining multi-sequence CMR (MyoPS 2020) for their public dataset and organizing the great challenge.

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Authors and Affiliations

  1. Department of Mathematics, Nanjing University of Science and Technology, Nanjing, China

    Jun Ma

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  1. Jun Ma
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Correspondence to Jun Ma .

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Editors and Affiliations

  1. Fudan University, Shanghai, China

    Xiahai Zhuang

  2. Shanghai Jiao Tong University, Shanghai, China

    Lei Li

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Ma, J. (2020). Cascaded Framework with Complementary CMR Information for Myocardial Pathology Segmentation. In: Zhuang, X., Li, L. (eds) Myocardial Pathology Segmentation Combining Multi-Sequence Cardiac Magnetic Resonance Images. MyoPS 2020. Lecture Notes in Computer Science(), vol 12554. Springer, Cham. https://doi.org/10.1007/978-3-030-65651-5_15

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  • DOI: https://doi.org/10.1007/978-3-030-65651-5_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-65650-8

  • Online ISBN: 978-3-030-65651-5

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