Prostate Cancer Classifier based on Three-Dimensional Magnetic Resonance Imaging and Convolutional Neural Networks

Ana-Maria Minda, Adrian C. Albu
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Abstract

The main reason for this research is the worldwide existence of a large number of prostate cancers. This article underlines how necessary medical imaging is, in association with artificial intelligence, in early detection of this medical condition. The diagnosis of a patient with prostate cancer is conventionally made based on multiple biopsies, histopathologic tests and other procedures that are time consuming and directly dependent on the experience level of the radiologist. The deep learning algorithms reduce the investigation time and could help medical staff. This work proposes a binary classification algorithm which uses convolutional neural networks to predict whether a 3D MRI scan contains a malignant lesion or not. The provided result can be a starting point in the diagnosis phase. The investigation, however, should be finalized by a human expert.
基于三维磁共振成像和卷积神经网络的前列腺癌分类器
这项研究的主要原因是世界范围内存在大量的前列腺癌。这篇文章强调了医学成像与人工智能在早期发现这种疾病方面的必要性。前列腺癌患者的诊断通常是基于多次活组织检查、组织病理学检查和其他耗时且直接依赖于放射科医生经验水平的程序。深度学习算法减少了调查时间,可以帮助医务人员。本研究提出了一种使用卷积神经网络来预测三维MRI扫描是否包含恶性病变的二元分类算法。提供的结果可以作为诊断阶段的起点。然而,调查应该由人类专家来完成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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