An improved strategy for skin lesion detection and classification using uniform segmentation and feature selection based approach

Nasir Muhammad; Attique Khan Muhammad; Sharif Muhammad; Lali Ikram Ullah; Saba Tanzila; Iqbal Tassawar; Bianchini Paolo

摘要

Abstract >Melanoma is the deadliest type of skin cancer with highest mortality rate. However, the annihilation in early stage implies a high survival rate therefore, it demands early diagnosis. The accustomed diagnosis methods are costly and cumbersome due to the involvement of experienced experts as well as the requirements for highly equipped environment. The recent advancements in computerized solutions for these diagnoses are highly promising with improved accuracy and efficiency. In this article, we proposed a method for the classification of melanoma and benign skin lesions. Our approach integrates preprocessing, lesion segmentation, features extraction, features selection, and classification. Preprocessing is executed in the context of hair removal by DullRazor, whereas lesion texture and color information are utilized to enhance the lesion contrast. In lesion segmentation, a hybrid technique has been implemented and results are fused using additive law of probability. Serial based method is applied subsequently that extracts and fuses the traits such as color, texture, and HOG (shape). The fused features are selected afterwards by implementing a novel Boltzman Entropy method. Finally, the selected features are classified by Support Vector Machine. The proposed method is evaluated on publically available data set PH2. Our approach has provided promising results of sensitivity 97.7%, specificity 96.7%, accuracy 97.5%, and F‐score 97.5%, which are significantly better than the results of existing methods available on the same data set. The proposed method detects and classifies melanoma significantly good as compared to existing methods. </abstract> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> <div class="translation abstracttxt"> <span class="zhankaihshouqi fivelineshidden" id="abstract"> <span>机译：</span><abstract xmlns =“http://www.wiley.com/namespaces/wiley”type =“main”> <title type =“main”>抽象</ title> >黑色素瘤是最致命的皮肤癌最高的死亡率。然而，早期衰退的湮灭意味着高生存率，需要早期诊断。由于经验丰富的专家的参与以及高度装备的环境的要求，习惯的诊断方法是昂贵和繁琐的。这些诊断的最新进步，具有提高的准确性和效率，高度有前景。在本文中，我们提出了一种用于对黑色素瘤和良性皮肤病变进行分类的方法。我们的方法集成了预处理，病变分段，特征提取，特征选择和分类。预处理在杜拉佐尔脱毛的上下文中执行，而病变纹理和颜色信息用于增强病变对比度。在病变分割中，已经实施了混合技术，并且使用概率添加剂法融合了结果。随后应用基于串行的方法，提取和熔化颜色，纹理和猪（形状）等特征。之后通过实施新颖的Boltzman熵方法后选择融合特征。最后，所选功能由支持向量机分类。在公开可用的数据集PH2上评估所提出的方法。我们的方法提供了灵敏度的有希望的97.7％，特异性96.7％，精度为97.5％，F分数97.5％，这显着优于同一数据集上现有方法的结果。与现有方法相比，所提出的方法检测和分类黑色素瘤显着良好。</ p> </ abstract> </span> <span class="z_kbtn z_kbtnclass hoverxs" style="display: none;">展开▼</span> </div> </div> <div class="record"> <h2 class="all_title" id="enpatent33" >著录项</h2> <ul> <li> <span class="lefttit">来源</span> <div style="width: 86%;vertical-align: text-top;display: inline-block;"> <a href='/journal-foreign-24994/'>《Microscopy research and technique》</a> <b style="margin: 0 2px;">|</b><span>2018年第6期</span><b style="margin: 0 2px;">|</b><span>共16页</span> </div> </li> <li> <div class="author"> <span class="lefttit">作者</span> <p id="fAuthorthree" class="threelineshidden zhankaihshouqi"> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Nasir Muhammad&option=202" target="_blank" rel="nofollow">Nasir Muhammad;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Attique Khan Muhammad&option=202" target="_blank" rel="nofollow">Attique Khan Muhammad;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Sharif Muhammad&option=202" target="_blank" rel="nofollow">Sharif Muhammad;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Lali Ikram Ullah&option=202" target="_blank" rel="nofollow">Lali Ikram Ullah;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Saba Tanzila&option=202" target="_blank" rel="nofollow">Saba Tanzila;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Iqbal Tassawar&option=202" target="_blank" rel="nofollow">Iqbal Tassawar;</a> <a href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=Bianchini Paolo&option=202" target="_blank" rel="nofollow">Bianchini Paolo;</a> </p> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zkzz" style="display: none;">展开▼</span> </div> </li> <li> <div style="display: flex;"> <span class="lefttit">作者单位</span> <div style="position: relative;margin-left: 3px;max-width: 639px;"> <div class="threelineshidden zhankaihshouqi" id="fOrgthree"> <p>COMSATS Institute of Information TechnologyWah Cantt Pakistan;</p> <p>COMSATS Institute of Information TechnologyWah Cantt Pakistan;</p> <p>COMSATS Institute of Information TechnologyWah Cantt Pakistan;</p> <p>Department of Software EngineeringUniversity of GujratPakistan;</p> <p>College of Computer and Information Sciences Prince Sultan UniversityRiyadh 11586 Saudi Arabia;</p> <p>COMSATS Institute of Information TechnologyWah Cantt Pakistan;</p> </div> <span class="z_kbtnclass z_kbtnclassall hoverxs" id="zhdw" style="display: none;">展开▼</span> </div> </div> </li> <li > <span class="lefttit">收录信息</span> <span style="width: 86%;vertical-align: text-top;display: inline-block;"></span> </li> <li> <span class="lefttit">原文格式</span> <span>PDF</span> </li> <li> <span class="lefttit">正文语种</span> <span>eng</span> </li> <li> <span class="lefttit">中图分类</span> <span><a href="https://www.zhangqiaokeyan.com/clc/19294.html" title="显微镜">显微镜;</a></span> </li> <li class="antistop"> <span class="lefttit">关键词</span> <p style="width: 86%;vertical-align: text-top;"> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=features extraction&option=203" rel="nofollow">features extraction;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=features selection&option=203" rel="nofollow">features selection;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=image enhancement&option=203" rel="nofollow">image enhancement;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=image fusion&option=203" rel="nofollow">image fusion;</a> <a style="color: #3E7FEB;" href="/search.html?doctypes=4_5_6_1-0_4-0_1_2_3_7_9&sertext=skin cancer&option=203" rel="nofollow">skin cancer;</a> </p> <div class="translation"> 机译：特点提取;特征选择;图像增强;图像融合;皮肤癌; 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