Image segmentation of women’s salivary ferning patterns using harmony frangi filter
Medical research proves that entering the fertile period, especially during ovulation, all-female body fluids contain ferning patterns in the form of crystallization of salt shaped like a fern tree. Until now, not many research topics have been carried out related to the segmentation process in the...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English English English |
| Published: |
Springer
2022
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/39160/1/Lecture%20Notes%20in%20Electrical%20Engineering%20vol%20632.pdf http://umpir.ump.edu.my/id/eprint/39160/2/Image%20Segmentation%20of%20Women%E2%80%99s.pdf http://umpir.ump.edu.my/id/eprint/39160/3/Image%20segmentation%20of%20women%E2%80%99s%20salivary%20ferning%20patterns%20.pdf http://umpir.ump.edu.my/id/eprint/39160/ https://doi.org/10.1007/978-981-15-2317-5_51 |
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| Summary: | Medical research proves that entering the fertile period, especially during ovulation, all-female body fluids contain ferning patterns in the form of crystallization of salt shaped like a fern tree. Until now, not many research topics have been carried out related to the segmentation process in the salivary ferning pattern, this is due to several problems including first, the unavailability of a database of image salivary ferning pattern online. Second, the salivary ferning pattern has several hidden layers and uneven intensity. The purpose of this study was to detect and determine the line shape of the salivary ferning crystal pattern using the Harmony Frangi Filter method based on the Hessian matrix operation. The results of the segmentation process from this study are a crucial basis in determining the level of accuracy and precision at the next stage of research, namely: the prediction process of a woman’s ovulation in each menstrual cycle. The measurement of segmentation results has an average value of MSE 2.25, PSNR 44.86 dB, FSIM 0.954, accuracy 99.88%, sensitivity 99.98% and specificity 99.88%. |
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