Optimized Segmentation Technique for Detecting PCOS in Ultrasound Images-Reference-Cited by-同舟云学术

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Optimized Segmentation Technique for Detecting PCOS in Ultrasound Images

Published:2022 Issue: Volume: Page:759-771
ISSN:2367-4512
Container-title:Lecture Notes on Data Engineering and Communications Technologies
language:
Short-container-title:

Author:

Jeevitha S.,Priya N.

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-16-9416-5_56

Reference26 articles.

1. Padmapriya B, Kesavamurthy T (2016) Detecting of follicles in poly cystic ovarian syndrome in ultrasound images using morophological operations. J Med Imaging Health Inf 6:240–243

2. Mehrotra P, Chakraborty C, Ghoshdastidar B (2011) Automated ovarian follicle recognition for polycystic ovary syndrome. In: Proceeding of international conference on image information processing (ICIIP 2011). IEEE, 978-1-61284-861-7

3. Prasanna Kumar H, Srinivasan S (2014) Despeckling of polycystic ovary ultrasound images by improved total variation method. Int J Eng Technol (UET) 6(4):0975–4024

4. Krivanek A, Sonka M (1998) Ovarian ultrasound image analysis; follicle segmentation. IEEE Trans Med Imaging 17(6):0278–0062

5. Cigale B, Zazula D (2014) Segmentation of ovarian ultrasound images using cellular neural networks. Int J Patt Recogn Artif Intell 18:563–581

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. 2D Medical Image Segmentation;Lecture Notes in Networks and Systems;2024

2. Optimized GrabCut Algorithm in Medical Image Analyses;Third Congress on Intelligent Systems;2023

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