Automated segmentation of cardiomyocyte Z-disks from high-throughput scanning electron microscopy data
Abstract Background With the advent of new high-throughput electron microscopy techniques such as serial block-face scanning electron microscopy (SBF-SEM) and focused ion-beam scanning electron microscopy (FIB-SEM) biomedical scientists can study sub-cellular structural mechanisms of heart disease a...
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| Format: | Article |
| Language: | English |
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BMC
2019-12-01
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| Series: | BMC Medical Informatics and Decision Making |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s12911-019-0962-1 |
| _version_ | 1818610085542232064 |
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| author | Afshin Khadangi Eric Hanssen Vijay Rajagopal |
| author_facet | Afshin Khadangi Eric Hanssen Vijay Rajagopal |
| author_sort | Afshin Khadangi |
| collection | DOAJ |
| description | Abstract Background With the advent of new high-throughput electron microscopy techniques such as serial block-face scanning electron microscopy (SBF-SEM) and focused ion-beam scanning electron microscopy (FIB-SEM) biomedical scientists can study sub-cellular structural mechanisms of heart disease at high resolution and high volume. Among several key components that determine healthy contractile function in cardiomyocytes are Z-disks or Z-lines, which are located at the lateral borders of the sarcomere, the fundamental unit of striated muscle. Z-disks play the important role of anchoring contractile proteins within the cell that make the heartbeat. Changes to their organization can affect the force with which the cardiomyocyte contracts and may also affect signaling pathways that regulate cardiomyocyte health and function. Compared to other components in the cell, such as mitochondria, Z-disks appear as very thin linear structures in microscopy data with limited difference in contrast to the remaining components of the cell. Methods In this paper, we propose to generate a 3D model of Z-disks within single adult cardiac cells from an automated segmentation of a large serial-block-face scanning electron microscopy (SBF-SEM) dataset. The proposed fully automated segmentation scheme is comprised of three main modules including “pre-processing”, “segmentation” and “refinement”. We represent a simple, yet effective model to perform segmentation and refinement steps. Contrast stretching, and Gaussian kernels are used to pre-process the dataset, and well-known “Sobel operators” are used in the segmentation module. Results We have validated our model by comparing segmentation results with ground-truth annotated Z-disks in terms of pixel-wise accuracy. The results show that our model correctly detects Z-disks with 90.56% accuracy. We also compare and contrast the accuracy of the proposed algorithm in segmenting a FIB-SEM dataset against the accuracy of segmentations from a machine learning program called Ilastik and discuss the advantages and disadvantages that these two approaches have. Conclusions Our validation results demonstrate the robustness and reliability of our algorithm and model both in terms of validation metrics and in terms of a comparison with a 3D visualisation of Z-disks obtained using immunofluorescence based confocal imaging. |
| first_indexed | 2024-12-16T15:08:50Z |
| format | Article |
| id | doaj.art-5785f8d1cd7845bc9fbec51a1180f775 |
| institution | Directory Open Access Journal |
| issn | 1472-6947 |
| language | English |
| last_indexed | 2024-12-16T15:08:50Z |
| publishDate | 2019-12-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Medical Informatics and Decision Making |
| spelling | doaj.art-5785f8d1cd7845bc9fbec51a1180f7752022-12-21T22:27:02ZengBMCBMC Medical Informatics and Decision Making1472-69472019-12-0119S611410.1186/s12911-019-0962-1Automated segmentation of cardiomyocyte Z-disks from high-throughput scanning electron microscopy dataAfshin Khadangi0Eric Hanssen1Vijay Rajagopal2Cell Structure and Mechanobiology Group, Department of Biomedical Engineering, Melbourne School of Engineering, The University of MelbourneAdvanced Microscopy Facility, Bio21 Molecular Science and Biotechnology Institute, The University of MelbourneCell Structure and Mechanobiology Group, Department of Biomedical Engineering, Melbourne School of Engineering, The University of MelbourneAbstract Background With the advent of new high-throughput electron microscopy techniques such as serial block-face scanning electron microscopy (SBF-SEM) and focused ion-beam scanning electron microscopy (FIB-SEM) biomedical scientists can study sub-cellular structural mechanisms of heart disease at high resolution and high volume. Among several key components that determine healthy contractile function in cardiomyocytes are Z-disks or Z-lines, which are located at the lateral borders of the sarcomere, the fundamental unit of striated muscle. Z-disks play the important role of anchoring contractile proteins within the cell that make the heartbeat. Changes to their organization can affect the force with which the cardiomyocyte contracts and may also affect signaling pathways that regulate cardiomyocyte health and function. Compared to other components in the cell, such as mitochondria, Z-disks appear as very thin linear structures in microscopy data with limited difference in contrast to the remaining components of the cell. Methods In this paper, we propose to generate a 3D model of Z-disks within single adult cardiac cells from an automated segmentation of a large serial-block-face scanning electron microscopy (SBF-SEM) dataset. The proposed fully automated segmentation scheme is comprised of three main modules including “pre-processing”, “segmentation” and “refinement”. We represent a simple, yet effective model to perform segmentation and refinement steps. Contrast stretching, and Gaussian kernels are used to pre-process the dataset, and well-known “Sobel operators” are used in the segmentation module. Results We have validated our model by comparing segmentation results with ground-truth annotated Z-disks in terms of pixel-wise accuracy. The results show that our model correctly detects Z-disks with 90.56% accuracy. We also compare and contrast the accuracy of the proposed algorithm in segmenting a FIB-SEM dataset against the accuracy of segmentations from a machine learning program called Ilastik and discuss the advantages and disadvantages that these two approaches have. Conclusions Our validation results demonstrate the robustness and reliability of our algorithm and model both in terms of validation metrics and in terms of a comparison with a 3D visualisation of Z-disks obtained using immunofluorescence based confocal imaging.https://doi.org/10.1186/s12911-019-0962-1Cardiac ultrastructureImage segmentationSerial-block-face scanning electron microscopyFocused ion-beam scanning electron microscopyComputational biology |
| spellingShingle | Afshin Khadangi Eric Hanssen Vijay Rajagopal Automated segmentation of cardiomyocyte Z-disks from high-throughput scanning electron microscopy data BMC Medical Informatics and Decision Making Cardiac ultrastructure Image segmentation Serial-block-face scanning electron microscopy Focused ion-beam scanning electron microscopy Computational biology |
| title | Automated segmentation of cardiomyocyte Z-disks from high-throughput scanning electron microscopy data |
| title_full | Automated segmentation of cardiomyocyte Z-disks from high-throughput scanning electron microscopy data |
| title_fullStr | Automated segmentation of cardiomyocyte Z-disks from high-throughput scanning electron microscopy data |
| title_full_unstemmed | Automated segmentation of cardiomyocyte Z-disks from high-throughput scanning electron microscopy data |
| title_short | Automated segmentation of cardiomyocyte Z-disks from high-throughput scanning electron microscopy data |
| title_sort | automated segmentation of cardiomyocyte z disks from high throughput scanning electron microscopy data |
| topic | Cardiac ultrastructure Image segmentation Serial-block-face scanning electron microscopy Focused ion-beam scanning electron microscopy Computational biology |
| url | https://doi.org/10.1186/s12911-019-0962-1 |
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