Gabor wavelet-based deep learning for skin lesion classification.

Clicks: 201
ID: 42518
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #36 of 87 articles by views in Computers in biology and medicine

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Skin cancer cases are increasing and becoming one of the main problems worldwide. Skin cancer is known as a malignant type of skin lesion, and early detection and treatment are necessary. Malignant melanoma and seborrheic keratosis are known as common skin lesion types. A fast and accurate medical diagnosis of these lesions is crucial. In this study, a novel Gabor wavelet-based deep convolutional neural network is proposed for the detection of malignant melanoma and seborrheic keratosis. The proposed method is based on the decomposition of input images into seven directional sub-bands. Seven sub-band images and the input image are used as inputs to eight parallel CNNs to generate eight probabilistic predictions. Decision fusion based on the sum rule is utilized to classify the skin lesion. Gabor based approach provides directional decomposition where each sub-band gives isolated decisions that can be fused for improved overall performance. The results show that the proposed method outperforms alternative methods in the literature developed for skin cancer detection.
Reference Key
serte2019gaborcomputers Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Serte, Sertan;Demirel, Hasan;
Journal Computers in biology and medicine
Year 2019
DOI
S0010-4825(19)30300-2
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.