Hatta, Moch. (2016) Penentuan Abnormalitas Pergerakan Spermatozoa Manusia Berbasis Regresi Linier. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Salah satu faktor penentu kualitas sperma adalah motilitas spermatozoa. Motilitas spermatozoa dapat dilakukan melalui uji mikroskopis sperma. Penentuan motilitas spermatozoa secara konvensional bergantung pada keberadaan ahli di mana penilaiannya bersifat subjektif. Computer-Assisted Sperm Analysis (CASA) sangat membantu memecahkan masalah ini. Umumnya CASA dan para peneliti di bidang ini menggunakan phase contrast microscope untuk mendapatkan image dengan kontras yang lebih tinggi. Namun dalam penelitian ini penentuan posisi dan gerakan spermatozoa pada video dilakukan menggunakan rekaman video yang berasal dari bright field microscope yang berkontras rendah dengan berbagai kekurangan lainnya. Dengan kombinasi beberapa tahapan yaitu mean filter background substraction, pengaturan kontras dengan berpatokan pada Otsu threshold, proses filtering menggunakan mathematical morphology untuk menetukan posisi dari objek serta penghitungan regresi linier dan nilai root mean square (RMS).
Dari hasil percobaan yang dilakukan video data spermatozoa manusia, ternyata metode di atas didapat posisi pergerakan spermatozoa hasil penjejakan dikenali bentuk lintasannya berdasarkan rata-rata jarak posisinya terhadap garis regresi linier, dengan threshold RMS sebesar 10 terdapat 10 spermatozoa progresif dan 4 spermatozoa non progresif. Metode yang digunakan berhasil menentukan 14 spermatozoa manusia, terdapat 71% progresif dan 29% non progresif. Menurut WHO laboratory manual for the examination and processing of human semen tahun 2010 dengan nilai 71% progresif berarti pergerakan sperma normal. ========== One key factor of the sperm quality is motility. Motility can be done through the microscopic sperm test. Determination of conventional sperm motility relies on the presence of experts in which the evaluation is subjective. Computer-Assisted Sperm Analysis (CASA) is very helpful to solve this problem. Generally CASA and researchers in this field using a phase contrast microscope to obtain images with higher contrast. However, in this study the positioning and movement of spermatozoa in the video was done using video footage came from bright field microscope that low contrast with many other shortcomings. With the combination of several stages of the mean filter Substraction background, in contrast with the arrangement based on the Otsu threshold, using mathematical morphology filtering process to determine the position of the object as well as the calculation of linear regression, and the value of root mean square (RMS).
From the results of experiments conducted on two types of data that test data video motility collection UNSW Embryology and video data recording the motility of human spermatozoa, it was found above the position of the movement of spermatozoa results tracking recognizable form of trajectory based on the average distance of the position to the line of linear regression, with RMS threshold of 10 there are four spermatozoa progressive and non-progressive spermatozoa 4 for the test data, while the video data is human spermatozoa 10 spermatozoa are progressive and non-progressive 4 spermatozoa. The method used successfully determine the eight data spermatozoa UNSW Embryology, there are 50% progressive and 50% non progressive; and 14 human spermatozoa, there are 71% progressive and 29% progressive non-progressive.
| Item Type: | Thesis (Masters) |
|---|---|
| Additional Information: | RTE 621.367 Hat p 2016 3100016068148 |
| Uncontrolled Keywords: | spermatozoa, regresi linier, root mean square, background substraction, mathematical morphology, spermatozoa, linear regression, root mean square, background subtraction, mathematical morphology |
| Subjects: | T Technology > TA Engineering (General). Civil engineering (General) > TA1637 Image processing--Digital techniques |
| Divisions: | Faculty of Industrial Technology > Electrical Engineering > 20101-(S2) Master Thesis |
| Depositing User: | - Davi Wah |
| Date Deposited: | 29 Oct 2019 09:27 |
| Last Modified: | 29 Oct 2019 09:27 |
| URI: | http://repository.its.ac.id/id/eprint/71412 |
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