Efficient and robust segmentation and tracking of sperm cells in microscopic image sequences
Sperm motility analysis is an important factor in male fertility diagnosis. This article presents a hybrid segmentation method to detect sperm cells, which is robust to density variation of the cells in the image sequences. In addition, a preprocessing scheme is employed to remove fixed sperm cells...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Wiley
2019-08-01
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| Series: | IET Computer Vision |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/iet-cvi.2018.5662 |
| _version_ | 1797684729526353920 |
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| author | Fateme Mostajer Kheirkhah Hamid Reza Sadegh Mohammadi Abdolhossein Shahverdi |
| author_facet | Fateme Mostajer Kheirkhah Hamid Reza Sadegh Mohammadi Abdolhossein Shahverdi |
| author_sort | Fateme Mostajer Kheirkhah |
| collection | DOAJ |
| description | Sperm motility analysis is an important factor in male fertility diagnosis. This article presents a hybrid segmentation method to detect sperm cells, which is robust to density variation of the cells in the image sequences. In addition, a preprocessing scheme is employed to remove fixed sperm cells and debris, which facilitate and speed up the cells' tracking stage. The article also proposes an automated sperm‐tracking algorithm in semen samples image sequences. It is a multi‐step tracking scheme, which is an enhanced version of adaptive window average speed (AWAS) tracking algorithm. It retrieves lost sperm cells during the tracking stage in adjacent frames and alleviates the cells collide problem. The proposed tracking algorithm provides both superior accuracy and higher speed compared to those of the other competitive algorithms for image sequences regardless of their particle densities. |
| first_indexed | 2024-03-12T00:33:57Z |
| format | Article |
| id | doaj.art-3fceeea6525444fda787ca95e7f55211 |
| institution | Directory Open Access Journal |
| issn | 1751-9632 1751-9640 |
| language | English |
| last_indexed | 2024-03-12T00:33:57Z |
| publishDate | 2019-08-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Computer Vision |
| spelling | doaj.art-3fceeea6525444fda787ca95e7f552112023-09-15T10:01:39ZengWileyIET Computer Vision1751-96321751-96402019-08-0113548949910.1049/iet-cvi.2018.5662Efficient and robust segmentation and tracking of sperm cells in microscopic image sequencesFateme Mostajer Kheirkhah0Hamid Reza Sadegh Mohammadi1Abdolhossein Shahverdi2Iranian Research Institute for Electrical EngineeringACECRTehranIranIranian Research Institute for Electrical EngineeringACECRTehranIranDepartment of EmbryologyRoyan InstituteACECRTehranIranSperm motility analysis is an important factor in male fertility diagnosis. This article presents a hybrid segmentation method to detect sperm cells, which is robust to density variation of the cells in the image sequences. In addition, a preprocessing scheme is employed to remove fixed sperm cells and debris, which facilitate and speed up the cells' tracking stage. The article also proposes an automated sperm‐tracking algorithm in semen samples image sequences. It is a multi‐step tracking scheme, which is an enhanced version of adaptive window average speed (AWAS) tracking algorithm. It retrieves lost sperm cells during the tracking stage in adjacent frames and alleviates the cells collide problem. The proposed tracking algorithm provides both superior accuracy and higher speed compared to those of the other competitive algorithms for image sequences regardless of their particle densities.https://doi.org/10.1049/iet-cvi.2018.5662microscopic image sequencessperm motility analysismale fertility diagnosishybrid segmentation methodfixed sperm cellsautomated sperm-tracking algorithm |
| spellingShingle | Fateme Mostajer Kheirkhah Hamid Reza Sadegh Mohammadi Abdolhossein Shahverdi Efficient and robust segmentation and tracking of sperm cells in microscopic image sequences IET Computer Vision microscopic image sequences sperm motility analysis male fertility diagnosis hybrid segmentation method fixed sperm cells automated sperm-tracking algorithm |
| title | Efficient and robust segmentation and tracking of sperm cells in microscopic image sequences |
| title_full | Efficient and robust segmentation and tracking of sperm cells in microscopic image sequences |
| title_fullStr | Efficient and robust segmentation and tracking of sperm cells in microscopic image sequences |
| title_full_unstemmed | Efficient and robust segmentation and tracking of sperm cells in microscopic image sequences |
| title_short | Efficient and robust segmentation and tracking of sperm cells in microscopic image sequences |
| title_sort | efficient and robust segmentation and tracking of sperm cells in microscopic image sequences |
| topic | microscopic image sequences sperm motility analysis male fertility diagnosis hybrid segmentation method fixed sperm cells automated sperm-tracking algorithm |
| url | https://doi.org/10.1049/iet-cvi.2018.5662 |
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