Detection of PCOS in Ultrasound Images using Digital Imaging

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Published Sep 20, 2021
Sivakumar Rajagopal Ramyalakshmi K Prabadevi B N Deepa

Abstract

Most of the ladies in this generation are suffering from early puberty, improper ovulation, excessive weight gain, and other hormonal imbalances. One of the major reasons for these is Polycystic ovary disorder (or polycystic ovarian disorder – PCOS). PCOS is a compound hormonal condition [1]. 'Polycystic' truly deciphers as 'multiple cysts'. ladies with PCOS can have Insulin protection because of hereditary components, Insulin protection because of being overweight (identified with eating routine and idleness), or a blend of both of these elements. Ladies with PCOS have elevated amounts of insulin or male hormones known as 'androgens', or both. The reason for this is misty, yet insulin protection is believed to be the critical issue driving this disorder. The accurate diagnosis of PCOS is essential. These days the conclusion performed by specialists is to physically tally the quantity of follicular cyst in the ovary, which is utilized to judge whether the PCOS exists or not. The ultrasound plays a vital role in examining various diseases [2]. The ultrasound image is taken as input as shown in fig.1 A and further processed using different filters for extracting the values accurately. This paper aims to find out the factor causing PCOS and to process the ultrasound images to visualize the cyst as shown in fig.1.B. The statistical analysis of PCOS and its symptoms were collected from the ladies of different age groups.  From the analysis, it is evident that the causes for PCOS vary instantly based on different factors [3]. About 92 patient real records were processed. The results of various image filters and image segmentation techniques were compared. The results with CART are giving absolutely better results than other classifier methods to detect the factor. The experimental result shows that testosterone is the main cause of the given input but this factor may change based on food habits and physical activity. This study will help the medical practitioners and researchers for taking necessary precautions in treating infected ladies.

How to Cite

Rajagopal, S., Ramyalakshmi K, Prabadevi B, & N Deepa. (2021). Detection of PCOS in Ultrasound Images using Digital Imaging. SPAST Abstracts, 1(01). Retrieved from https://spast.org/techrep/article/view/1080
Abstract 199 |

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References
[1] M. Jamal, S. Chakrabarty et al. Microsyst Technol 24, 4217–4223 (2018).
https://doi.org/ 10.1007%2Fs11892-017-0956-2
[2] Dongxin, et al. Applied Acoustics 179, 108056 (2021).
https://doi.org/10.1016/j.apacoust.2021.108056
[3] Moghadam, Zahra Behboodi, et al. International journal of women's health 10, 397 (2018): 397.https://doi: 10.2147/IJWH.S165794
Section
GE3- Computers & Information Technology

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