Multi-Target Tracking of Human Spermatozoa in Phase-Contrast Microscopy Image Sequences using a Hybrid Dynamic Bayesian Network
| Autor: | Bijan Vosoughi Vahdat, Reza Salman Yazdi, Abdollah Arasteh |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Male Computer science Phase contrast microscopy lcsh:Medicine Semen 02 engineering and technology Tracking (particle physics) Article Image (mathematics) law.invention 03 medical and health sciences law 0202 electrical engineering electronic engineering information engineering Image Processing Computer-Assisted Multi target tracking Humans Microscopy Phase-Contrast lcsh:Science Dynamic Bayesian network Infertility Male Multidisciplinary Sperm Count business.industry lcsh:R Pattern recognition Bayes Theorem Spermatozoa Semen Analysis 030104 developmental biology Cell Tracking Sperm Motility 020201 artificial intelligence & image processing lcsh:Q Artificial intelligence business Algorithms |
| Zdroj: | Scientific Reports Scientific Reports, Vol 8, Iss 1, Pp 1-19 (2018) |
| ISSN: | 2045-2322 |
| Popis: | Male infertility is mostly related to semen and spermatozoa, and any diagnosis or treatment requires the investigation of the motility patterns of spermatozoa. The movements of spermatozoa are fast and involve collision and occlusion with each other. In order to extract the motility patterns of spermatozoa, multi-target tracking (MTT) of spermatozoa is necessary. One of the most important steps of MTT is data association, in which the newly arrived observations are used to update the previous tracks. Dynamic Bayesian network (DBN) is a powerful tool for modeling and solving various types of problems such as tracking and classification. There can also be a hybrid-DBN (HDBN), in which both continuous and discrete nodes are present. HDBN has a suitable structure for modeling problems that have both discrete and continuous parameters like MTT. In this research, the data association for MTT of human spermatozoa has been studied. The proposed algorithm was tested over hundreds of manually extracted spermatozoa tracks and evaluated using several standard measures. The superior results of the proposed algorithm in comparison to the other well-known algorithms, show that it could be considered as an improved alternative to traditional computer assisted sperm analysis (CASA) algorithms. |
| Databáze: | OpenAIRE |
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