scholarly journals Classification of Melanoma Images Using Empirical Wavelet Transform

2021 ◽  
Vol 8 (1) ◽  
pp. 1-8
Author(s):  
Aida Fadaeian ◽  
Akram Esvand Rahmani ◽  
Reza Javid
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Skin Cancer ◽  
Skin Diseases ◽  
Gray Wolf ◽  
Ranking Models ◽  
Skin Cancers ◽  
Empirical Wavelet Transform ◽  
Significant Performance ◽  
Processing Techniques

Skin cancer is the most common cancer, accounting for 75% of all skin cancers worldwide. Malignant melanoma is the most invasive type of skin cancer, which is deadly. Some techniques have been investigated to diagnose skin diseases using skin tissue classification and diagnosis models and skin recognition approaches using colors based on image retrieval methods. In this regard, image processing techniques and classification methods are intelligent. The purpose of this method, diagnosing melanoma skin cancer using image processing. In the proposed method, after collecting the dataset, the boundary to separate the skin lesion from the background was specified. Then in the next step, the analysis was performed using Empirical wavelet transform (EWT). Then the color, texture, and shape features were extracted. In the next step, the feature was selected by Gray Wolf meta-heuristic algorithm using ranking models and the disease was classified into two categories, namely normal and abnormal. The database used in this study contains 594 dermatoscopic images with a resolution of 512 × 768 pixels, 476 images with normal spots, and 88 images with abnormal spots caused by melanoma. The evaluation results revealed that the proposed method had an accuracy of 97.25, indicating its significant performance compared to other methods. The contribution of the results of the proposed method can be very useful and valuable in the future for early detection of skin cancer.

scholarly journals Skin Cancer Analysis with Deep Learning

2021 ◽  
Vol 9 (VII) ◽  
pp. 2663-2672
Author(s):  
Siddharth Raj Dash
Keyword(s):  
Image Processing ◽  
Deep Learning ◽  
Skin Cancer ◽  
Medical Diagnosis ◽  
Skin Diseases ◽  
Detection System ◽  
Technological Advancement ◽  
Image Processing Techniques ◽  
The Cost ◽  
Processing Techniques

Skin diseases are some of the most common diseases and are often difficult to diagnose than other diseases. Skin diseases may be caused by fungus, bacteria, allergic reaction, viruses, cancer etc. The technological advancement in laser diagnosis and Photonics based medical diagnosis has made it possible to diagnose the skin diseases much more quickly and accurately. But the cost of diagnostics is time-consuming and very expensive. Hence, we can use image processing techniques to help build automated preliminary detection system for such dermatological diagnostics.

scholarly journals A Review of Skin Disease Classification Techniques based on Machine Learning

2021 ◽  
Vol 9 (8) ◽  
pp. 1097-1101
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Skin Cancer ◽  
Basal Cell Carcinoma ◽  
Actinic Keratosis ◽  
Skin Disease ◽  
Skin Diseases ◽  
Skin Condition ◽  
Disease Classification ◽  
Vascular Lesions

Dermatology is one of the most unpredictable and difficult field to diagnose. In this field, more tests are needed to be carried out so as to decide the skin condition the patient may be facing. The time to diagnose may vary according to the different dermatologist. Machine learning and image processing can be used to efficiently detect the skin diseases. There are seven different categories of skin cancer- melanocytic nevi, melanoma, benign keratosis, Basal cell carcinoma, actinic keratosis, vascular lesions and dermatofibroma. The purpose of this review is to outline types, diagnosis, methodology and treatment of skin cancer.

The Study of Materials Using Wavelet Image Processing Techniques

1990 ◽  
Vol 217 ◽  
Author(s):  
L. Beltrán-Del-Rŕo ◽  
A. Gónez ◽  
M. José-Yacamán
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Electron Micrographs ◽  
Small Particles ◽  
Image Processing Techniques ◽  
Medium Resolution ◽  
Resolution Electron ◽  
Edge Sensitivity ◽  
Processing Techniques ◽  
Wavelet Image

ABSTRACTIn this work the wavelet transform is used to process high- and medium resolution electron micrographs from small particles and their substrates. It is concluded that the edge sensitivity of the technique and its contrast enhancement capabilities are most useful in the processing of electron micrographs.

Opposing Roles of Antimicrobial Peptides in Skin Cancers

2021 ◽  
Vol 27 ◽  
Author(s):  
Chanisa Kiatsurayanon ◽  
Ge Peng ◽  
François Niyonsaba
Keyword(s):  
Skin Cancer ◽  
Antimicrobial Peptides ◽  
Cancer Biology ◽  
Skin Diseases ◽  
Immune Defense ◽  
The Body ◽  
Skin Tumor ◽  
Host Defense Peptides ◽  
Skin Cancers ◽  
The Impact

: Antimicrobial peptides (AMPs), also known as host defense peptides, are ubiquitous naturally occurring molecules secreted by various cell types of the body. In the skin, AMPs serve as a first-line innate immune defense against exogenous microorganisms, and they orchestrate adaptive immune responses to exert several immunomodulatory functions. Emerging evidence indicates that AMPs not only contribute to certain inflammatory skin diseases but also play a role in skin tumor carcinogenesis. Available data support the hypothesis that AMPs possess both pro-tumor and anti-neoplastic properties. Although inconsistent observations reported by multiple studies make it challenging to summarize the precise roles of AMPs in cancer, the differential expression of AMPs in skin cancers, such as the increased expression of human beta-defensins in squamous cell carcinoma and the ability of cathelicidin LL-37 to induce malignant melanoma cell invasion, implies they have procancer activities. On the other hand, the observation that certain AMPs show cytotoxic activity against cancer cells of the colon and kidney suggests their inherent antitumor properties. In this review, we describe the roles and mechanisms of AMPs in skin cancer development. We believe that further research is needed to elucidate the impact of these AMPs in skin cancer biology and to explore their potential roles as diagnostic/prognostic biomarkers and as novel therapeutic targets.

scholarly journals Skin cancer detection and stage prediction using image processing techniques

2018 ◽  
Vol 7 (1.8) ◽  
pp. 204 ◽  
Author(s):  
Sheeju Diana ◽  
Ramamurthy B
Keyword(s):  
Image Processing ◽  
Skin Cancer ◽  
Back Propagation ◽  
Histogram Equalization ◽  
Noise Removal ◽  
The Body ◽  
Back Propagation Algorithm ◽  
Environmental Threats ◽  
Image Processing Techniques ◽  
Processing Techniques

Skin cancer is one of the perilous forms of cancer that most recently occurred in preceding and in recent years as well. Early detection of skin cancer is curable and it eliminates the cost that is spent on the advanced treatment. Skin cancer mainly occurs due to exposure to sun’s ultraviolet radiation and other environmental threats. It can be categorized into, Melanoma and Non-Melanoma. Melanoma is dangerous one. Once it is occurred it starts spreading across other parts of the body if not treated in the early stages. Non-Melanoma is a static cancer which does not affect the normal cells of the skin. This paper aims to develop an application to detect skin cancer and stage prediction using Image Processing Techniques. Stage is predicted, so that the treatment for the same is done without any delay. Skin cancer affected image is taken as input and various preprocessing techniques is applied for the same. The Preprocessing Techniques such as Noise Removal is applied on the image to filter out the noise. Filtered image is enhanced using Histogram Equalization and image is segmented to extract the affected portion. The Area, Perimeter and Eccentricity values are calculated for the affected portion of the skin. The values are then fed into the Neural Networks using Back Propagation algorithm in order to predict the Stage and type of the Skin cancer.

scholarly journals Multiple skin neoplasms in subjects under 40 years of age in Goiania, Brazil

2015 ◽  
Vol 49 (0) ◽  
Author(s):  
Samir Pereira ◽  
Maria Paula Curado ◽  
Ana Maria Quinteiro Ribeiro
Keyword(s):  
Skin Cancer ◽  
Ultraviolet Radiation ◽  
Skin Diseases ◽  
Skin Neoplasms ◽  
Population Based ◽  
Annual Percentage Change ◽  
Multiple Lesions ◽  
Skin Cancers ◽  
Malignant Skin ◽  
Nonmelanoma Skin Cancers

OBJECTIVE To describe the trend for malignant skin neoplasms in subjects under 40 years of age in a region with high ultraviolet radiation indices.METHODS A descriptive epidemiological study on melanoma and nonmelanoma skin cancers that was conducted in Goiania, Midwest Brazil, with 1,688 people under 40 years of age, between 1988 and 2009. Cases were obtained fromRegistro de Câncer de Base Populacional de Goiânia(Goiania’s Population-Based Cancer File). Frequency, trends, and incidence of cases with single and multiple lesions were analyzed; transplants and genetic skin diseases were found in cases with multiple lesions.RESULTS Over the period, 1,995 skin cancer cases were observed to found, of which 1,524 (90.3%) cases had single lesions and 164 (9.7%) had multiple lesions. Regarding single lesions, incidence on men was observed to have risen from 2.4 to 3.1/100,000 inhabitants; it differed significantly for women, shifting from 2.3 to 5.3/100,000 (Annual percentage change – [APC] 3.0%, p = 0.006). Regarding multiple lesions, incidence on men was observed to have risen from 0.30 to 0.98/100,000 inhabitants; for women, it rose from 0.43 to 1.16/100,000 (APC 8.6%, p = 0.003). Genetic skin diseases or transplants were found to have been correlated with 10.0% of cases with multiple lesions – an average of 5.1 lesions per patient. The average was 2.5 in cases without that correlation.CONCLUSIONS Skin cancer on women under 40 years of age has been observed to be increasing for both cases with single and multiple lesions. It is not unusual to find multiple tumors in young people – in most cases, they are not associated with genetic skin diseases or transplants. It is necessary to avoid excessive exposure to ultraviolet radiation from childhood.

The potential cutaneous effects of stratospheric ozone depletion

1996 ◽  
Vol 4 (1) ◽  
pp. 1-7
Author(s):  
John H. Epstein
Keyword(s):  
Skin Cancer ◽  
Lupus Erythematosus ◽  
Skin Diseases ◽  
Stratospheric Ozone ◽  
Ultraviolet B ◽  
Uvb Radiation ◽  
Skin Cancers ◽  
Light Skin ◽  
Solar Urticaria ◽  
Common Skin

Recent evidence indicates that there has been a reduction in the stratospheric ozone over the northern hemisphere, as well as the Antarctic and Arctic latitudes. This has resulted in an increased penetration of ultraviolet B (UVB) at least as measured at Toronto, Canada, since 1989. If no precautions are observed by the human population, this could eventually result in an increase in the skin cancer incidence. This would be especially true for the most common cancers, that is, the nonmelanoma skin cancers (NMSCs), basal cell carcinomas and squamous cell carcinomas. In addition it has been predicted that the third most common skin cancer, the malignant melanoma, would also increase in incidence. However, the relationship between UVB radiation and melanoma formation is much less clear than it is for NMSCs. Clinically people with a loss or lack of melanin protection such as those with occulocutaneous albinism and vitiligo, or much more commonly, people with light skin, eyes, and hair would be at greatest risk. Also increased UVB penetration could exacerbate certain infections such as herpes simplex. People with UVB-sensitive diseases including solar urticaria, polymorphous light eruptions, lupus erythematosus, dermatomyositis, pemphigus, pemphigoid, Darier's disease, familial benign chronic pemphigus, and certain recessive degenerative genodermatoses would also be potentially more vulnerable.Key words: ozone, ultraviolet B (UVB), skin cancer, photosensitive skin diseases.

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