Modified histogram-based segmentation and adaptive distance tracking of sperm cells image sequences. (February 2018)

• Record Type: Journal Article
• Authors: Mostajer Kheirkhah, Fateme; Sadegh Mohammadi, Hamid Reza; Shahverdi, Abdolhossein
• Is Part Of: Computer methods and programs in biomedicine. Volume 154(2018)
• Page Start: 173
• Page End: 182
• Publication Date: 2018-02
• Subjects: Histogram-based thresholding -- Sperm cells -- Motility analysis -- Segmentation -- Tracking -- Adaptive distance; Medicine -- Computer programs -- Periodicals; Biology -- Computer programs -- Periodicals; Computers -- Periodicals; Medicine -- Periodicals; Médecine -- Logiciels -- Périodiques; Biologie -- Logiciels -- Périodiques; Biology -- Computer programs; Medicine -- Computer programs; Periodicals; Electronic journals; 610.28
• DOI: 10.1016/j.cmpb.2017.11.005
• Languages: English
• ISSNs: 0169-2607

Abstract

Abstract: Proper recognition and tracking of microscopic sperm cells in video images are vital steps of male infertility diagnosis and treatment. The segmentation and detection of sperms in microscopic image analysis is a complicate process as a result of their small sizes, fast movements, and considerable collisions. Histogram-based thresholding schemes are very popular for this purpose, since they are quite fast and provide almost acceptable results. This paper proposes a combined method for sperm cells detection, which consists of a non-linear pre-processing stage, a histogram-based thresholding algorithm, and a tracking method based on an adaptive distance scheme. The results of conducted experiments verify the superiority of the proposed scheme with incorporated Kittler algorithm compared to the other competitive methods in the majority of cases.