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首页> 外文会议>International Conference on Parallel, Distributed and Grid Computing >Detecting Malignancy of Ovarian Tumour using Convolutional Neural Network: A Review
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Detecting Malignancy of Ovarian Tumour using Convolutional Neural Network: A Review

机译：用卷积神经网络检测卵巢肿瘤恶性肿瘤：综述

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摘要

Ovaries are important part of female reproductive system. The importance of these tiny glands is derived from the production of female sex hormones and female gametes. The location of these ductless almond shaped small glandular organs is on just opposite sides of uterus attached with ovarian ligament. There are many factors due to which ovarian cancer can occur but it can be detected by using various techniques and among them there is one method named as convolutional neural network. This review paper tells us about how we can use Convolutional Neural Network to classify the ovarian cancer tumour and what other ways to deal with it. In this research work we have also discussed about the comparison of various machine learning algorithms like K-Nearest Neighbor, Support Vector Machine and Artificial Neural Network used in detection of ovarian cancer. After comparing the different methods for this cancer detection, it seemed Deep Learning Technique to be the best for yielding results.
机译：卵巢是女性生殖系统的重要组成部分。这些微型腺体的重要性来自雌性荷尔蒙和女性配子的生产。这些导管的杏仁形小腺体器官的位置恰好是子宫的相对侧，附着卵巢韧带。由于哪种卵巢癌可能发生了许多因素，而是可以通过使用各种技术来检测，其中有一种名为卷积神经网络的方法。这篇评论纸质告诉我们我们如何使用卷积神经网络来分类卵巢癌肿瘤以及其他方式处理它。在本研究中，我们还讨论了关于k-最近邻居等各种机器学习算法的比较，支持卵巢癌中使用的支持向量机和人工神经网络。在比较这种癌症检测的不同方法后，它似乎是深度学习技术，是屈服的最佳结果。

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