Architecture of an effective convolutional deep neural network or segmentation of skin lesion in dermoscopic images

Ginni Arora; Ashwani Kumar Dubey; Zainul Abdin JafferyAlvaro Rocha

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Architecture of an effective convolutional deep neural network or segmentation of skin lesion in dermoscopic images

机译：Architecture of an effective convolutional deep neural network or segmentation of skin lesion in dermoscopic images

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The segmentation of dermoscopic-based skin lesion images is considered to be challengingowing to various factors. Some of the most tangible reasons include poorcontrast near the affected skin lesion, the fuzzy and unpredictable lesion limits, thepresence of variations in noise, and capturing images under different conditions. Thispaper aims to develop an efficient segmentation model for dermoscopic images ofdifferent skin lesions based on deep learning. This paper proposes the 11-layer convolutionaldeep neural network with two segmentation models trained from start tofinish and do not depend on any previous information about the data. The viability,efficiency, and speculation ability of the models are evaluated on the ISIC2018 database.The proposed model achieves 0.903 accuracy and 0.820 Jaccard index in thesegmentation of skin lesions. The model shows better performance compared toother image segmentation techniques from the leaderboards of ISIC2018 using deeplearning.

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《Expert systems: The international journal of knowledge engineering》 |2023年第6期|e12689.1-e12689.13|共13页
作者
Ginni Arora; Ashwani Kumar Dubey; Zainul Abdin JafferyAlvaro Rocha;
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作者单位

Amity Institute of Information Technology,Amity University Uttar Pradesh, Noida, India;

Amity School of Engineering and Technology,Amity University Uttar Pradesh, Noida, India;

Department of Electrical Engineering, FoE,Jamia Millia Islamia, New Delhi, IndiaISEG, University of Lisbon, Lisboa, Portugal;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
中图分类
关键词
convolutional neural network; deep learning; ISIC; Jaccard index; segmentation;

Architecture of an effective convolutional deep neural network or segmentation of skin lesion in dermoscopic images

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