Segmentation of ovarian cyst in ultrasound images using AdaResU-net with optimization algorithm and deep learning model

Author:

Sha Mohemmed

Funder

Deanship of Scientific Research, Prince Sattam bin Abdulaziz University

Publisher

Springer Science and Business Media LLC

Reference34 articles.

1. Kiruthika, V., Sathiya, S., Ramya, M. M. & Sankaran, K. S. An intelligent machine learning approach for ovarian detection and classification system using ultrasonogram images. Eng. Sci. 23, 879 (2023).

2. Srivastava, S., Kumar, P., Chaudhry, V. & Singh, A. Detection of ovarian cyst in ultrasound images using fine-tuned VGG-16 deep learning network. SN Comput. Sci. 1(2), 81 (2020).

3. Gopalakrishnan, C. & Iyapparaja, M. Multilevel thresholding based follicle detection and classification of polycystic ovary syndrome from the ultrasound images using machine learning. Int. J. Syst. Assur. Eng. Manag. 1, 1–8 (2021).

4. Raja, P. & Suresh, P. Variety of ovarian cysts detection and classification using 2D Convolutional Neural Network. Multimed. Tools Appl. 83(16), 49473–49491 (2024).

5. Shivaram, J. M. Segmentation of ovarian cyst using improved U-NET and hybrid deep learning model. Multimedia Tools Appl. 83(14), 42645–42679 (2024).

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