Skin cancers image classification using transformation and first order statistic features with artificial neural network classifier

IF 16.4 1区 化学 Q1 CHEMISTRY, MULTIDISCIPLINARY
A. Alqaisi, Loay E. George
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引用次数: 0

Abstract

Skin cancer is one of the most dangerous types of cancer. Some types of this cancer lead to death, so cancer must be discovered and indexed to avoid its spread through initial detection in the impulsive stage. This paper deals with the detection and indexing of different types of melanomas using an artificial neural network (ANN) depending on the international skin imaging collaboration (ISIC) 2018 dataset that was used. The pre-processing is the most important part because it formulates an image by insolated the cancer part from the skin image. It consists of four stages, removable, cropping, thinning, and normalization. This phase has been used to eliminate all the undesirable hair particles on the image lesion. The cropped image transforms into frequency domain coefficients using discrete cosine transform (DCT), discrete wavelet transform (DWT), and gradient transform for sub-band images to extract its feature. The statistical feature extraction is implemented to minimize the size of data for ANN training. The experimental analysis used dataset ISIC 2018 consisting of seven different types of dermoscopic images (this paper deals with four types only). For classification purposes, ANN was implemented and the accuracy obtained is about 88.98% for DWT, 85.44% for sub-band DCT, and 76.07% for sub-band gradient transform.
基于变换和一阶统计特征的人工神经网络皮肤癌图像分类
皮肤癌是最危险的癌症之一。这种癌症的某些类型会导致死亡,因此必须通过在冲动阶段的初始检测来发现和索引癌症,以避免其扩散。本文根据使用的国际皮肤成像协作(ISIC) 2018数据集,使用人工神经网络(ANN)对不同类型的黑色素瘤进行检测和索引。预处理是将肿瘤部分从皮肤图像中剥离出来形成图像的关键环节。它包括四个阶段:可移除、裁剪、细化和归一化。此阶段已用于消除图像病变上所有不需要的毛发颗粒。利用离散余弦变换(DCT)、离散小波变换(DWT)和子带图像梯度变换将裁剪后的图像变换为频域系数,提取其特征。实现了统计特征提取,使人工神经网络训练的数据量最小化。实验分析使用的数据集ISIC 2018由7种不同类型的皮肤镜图像组成(本文仅处理4种类型)。在分类方面,采用人工神经网络进行分类,DWT、子带DCT和子带梯度变换的准确率分别为88.98%、85.44%和76.07%。
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来源期刊
Accounts of Chemical Research
Accounts of Chemical Research 化学-化学综合
CiteScore
31.40
自引率
1.10%
发文量
312
审稿时长
2 months
期刊介绍: Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.
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