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首页> 外文会议>International Conference on Computer, Electrical Communication Engineering >A Deep learning Framework for Eye Melanoma Detection employing Convolutional Neural Network
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A Deep learning Framework for Eye Melanoma Detection employing Convolutional Neural Network

机译：使用卷积神经网络的眼黑素瘤检测深度学习框架

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Eye melanoma is a rare disease but according to malignancy, it is the most common type of cancer. Just like other types of cancers, it is curable for most of the cases if diagnosed properly but the process of diagnosis is quite challenging and is the most problematic issue in the treatment of eye melanoma. This paper presents an automated eye melanoma detection method using a convolutional neural network (CNN). 170 pre-diagnosed samples are taken from a standard database followed by pre-processing to lower resolution samples and finally fed to the CNN architecture. The proposed work eliminates separate feature extraction as well as the classification for the detection of eye melanoma. Although the proposed method requires a huge computation, a high accuracy rate of 91.76% is achieved outperforming the eye melanoma detection using an artificial neural network (ANN).
机译：眼黑素瘤是一种罕见的疾病，但根据恶性肿瘤，它是最常见的癌症类型。就像其他类型的癌症一样，如果诊断正确，在大多数情况下都可以治愈，但是诊断过程非常具有挑战性，并且是治疗眼部黑色素瘤中最成问题的问题。本文提出了一种使用卷积神经网络（CNN）的自动眼黑素瘤检测方法。从标准数据库中提取170个预先诊断的样本，然后进行预处理以降低分辨率的样本，最后将其送入CNN架构。拟议的工作消除了单独的特征提取以及用于眼黑素瘤检测的分类。尽管所提出的方法需要大量的计算，但仍达到了91.76％的高精度，优于使用人工神经网络（ANN）进行的眼睛黑素瘤检测。

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