Performance evaluation of optimized convolutional neural network mechanism in the detection and classification of ovarian cancer

• Published in: Multimedia tools and applications Vol. 83; no. 28; pp. 71311 - 71334
• Main Authors: Kongara, Srinivasa Rao, Prakasha, S., Brindha, A., Pathak, Sumit Kumar, Miya, Javed, Taqui, Syed Noeman, Almoallim, Hesham S., Alharbi, Sulaiman Ali, Raghavan, S. S.
• Format: Journal Article
• Language: English
• Published: New York Springer US 07.02.2024; Springer Nature B.V
• Subjects: Artificial neural networks; Cancer; Classification; Computer Communication Networks; Computer Science; Data Structures and Information Theory; Image enhancement; Image segmentation; Krill; Machine learning; Multimedia Information Systems; Neural networks; Ovarian cancer; Performance evaluation; Special Purpose and Application-Based Systems; Tumors; Ultrasonic imaging; Wavelet transforms; Convolutional Neural Network; Ovarian cancer Detection; Krill Herd Optimization; Deep Learning

Female mortality is frequently caused by ovarian cancer (OC). Because of its late detection, ovarian cancer seems to have a low survival rate, and new techniques are required for its early identification. One of the more prevalent gynecologic cancers is ovarian cancer. The various diagnoses of ovari...