Automated region mask for four-chamber fetal heart biometry
Abstract
This letter proposes an automated region mask for the detection of cardiac chambers from ultrasonic fetal heart biometry. The fetal biometry consists of two dimensional ultrasonic cine-loop sequences of apical four chamber view of fetal heart, which are comparatively The clinical motion information of individual frame is extracted by keeping a constant frame rate of 25 frames per second (fps). The region mask is designed based on the superimposition of motion information from a set of consecutive frames that belong to one cardiac cycle followed by connected component labelling. The borders and edges of all four chambers are thus recognized leading to formation of binary region mask. Experimental study based on second trimester cine-loop sequences confirms the suitability of the proposed technique for detection of heart chambers.
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Detection of the fetal heart as a ROI in US images can be performed by AI models.
“the detection of the fetal heart as a ROI in US images can be performed by AI models [72,73].”
Cites
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Segmentation and classification in MRI and US fetal imaging: Recent trends and future prospects
Torrents-Barrena, J., Piella, G., Masoller, N., Gratacós, E., Eixarch, E., Ceresa, M., & Ballester, M. Á. G. (2019) · Medical Image Analysis · doi:10.1016/j.media.2018.10.003 · Cited by 97 · see citing works
Jost, E., Kosian, P., Jimenez Cruz, J., Albarqouni, S., Gembruch, U., Strizek, B., & Recker, F. (2023) · Journal of Clinical Medicine · doi:10.3390/jcm12216833 · Cited by 44 · see citing works
“As a solution to this issue and an emerging research focus, the detection of the fetal heart as a ROI in US images can be performed by AI models [72,73].”
BackgroundSriraam, N., Punyaprabha, V., Sushma, T. V., & Suresh, S. (2023) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-023-02814-1 · Cited by 5 · see citing works
- Authors
- Vijayalakshmi, S., Sriraam, N., Suresh, S., & Muttan, S.
- Affiliations
- Anna University, Chennai (IN)
- Sri Sivasubramaniya Nadar College of Engineering (IN)
- Corresponding author
- Sriraam, N.
- ORCID
- Sriraam, N.
- Venue
- Journal of Clinical Monitoring and Computing
- Published
- 2012-10-21
- Volume
- 27
- Issue
- 2
- Pages
- 205-209
- ISSN
- 1387-1307 (ISSN-L)
- 1573-2614
- OpenAlex
- W2034252414
- Cited by
- 15
- References
- 12
- Citations by year
- 2024: 2 · 2023: 3 · 2022: 3 · 2021: 1 · 2019: 3 · 2018: 1 · 2016: 1 · 2012: 1
- FWCI
- 0.33
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Journal of Clinical Monitoring and Computing (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Health Sciences › Health Professions › Health Information Management › Artificial Intelligence in Healthcare
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- apical four-chamber view, motion information, connected component labeling, binary segmentation, second trimester, fetal echocardiography
- MeSH terms
- Algorithms, Automation, Biometry, Female, Fetal Heart, Gestational Age, Humans, Image Processing, Computer-Assisted, Pregnancy, Pregnancy Trimester, Second, Ultrasonography, Prenatal
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