Real-Time Mobile-Phone-Aided Melanoma Skin Lesion Detection Using Triangulation Technique

Melanoma is a harmful disease among all types of skin cancer. Genetic factors and the exposure of UV rays causes melanoma skin lesions. Early diagnosis is important to identify malignant melanomas to improve the patient prognosis. A biopsy is a traditional method which is painful and invasive when used for skin cancer detection. This method requires laboratory testing which is not very efficient and time-consuming to detect skin lesions. To solve the above issue, a computer aided diagnosis (CAD) for skin lesion detection is needed. In this article, we have developed a mobile application with the capabilities to segment skin lesions in dermoscopy images using a triangulation method and categorize them into malignant or bengin lesions through a supervised method which is convolution neural network (CNN). This mobile application will make the skin cancer detection non-invasive which does not require any laboratory testing, making the detection less time consuming and inexpensive with a detection accuracy of 81%.

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Melanoma Skin Cancer Detection Based on Skin Lesions Characterization

IOSR Journal of Engineering ◽

10.9790/3021-03215259 ◽

2013 ◽

Vol 03 (02) ◽

pp. 52-59 ◽

Cited By ~ 1

Author(s):

Nisha Oommachen

Keyword(s):

Skin Cancer ◽

Cancer Detection ◽

Skin Lesions ◽

Skin Cancer Detection ◽

Melanoma Skin

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Melanoma Skin Cancer Detection based on Image Processing

Current Medical Imaging Formerly Current Medical Imaging Reviews ◽

10.2174/1573405614666180911120546 ◽

2020 ◽

Vol 16 (1) ◽

pp. 50-58 ◽

Cited By ~ 4

Author(s):

Nadia Smaoui Zghal ◽

Nabil Derbel

Keyword(s):

Skin Cancer ◽

Cancer Detection ◽

Early Stage ◽

Skin Lesions ◽

Simple Method ◽

Common Cause ◽

Extraction Stage ◽

Skin Cancer Detection ◽

Aided Diagnosis ◽

Melanoma Skin

Background: Skin cancer is one of the most common forms of cancers among humans. It can be classified as non-melanoma and melanoma. Although melanomas are less common than non-melanomas, the former is the most common cause of mortality. Therefore, it becomes necessary to develop a Computer-aided Diagnosis (CAD) aiming to detect this kind of lesion and enable the diagnosis of the disease at an early stage in order to augment the patient’s survival likelihood. Aims: This paper aims to develop a simple method capable of detecting and classifying skin lesions using dermoscopy images based on ABCD rules. Methods: The proposed approach follows four steps. 1) The preprocessing stage consists of filtering and contrast enhancing algorithms. 2) The segmentation stage aims at detecting the lesion. 3) The feature extraction stage based on the calculation of the four parameters which are asymmetry, border irregularity, color and diameter. 4) The classification stage based on the summation of the four extracted parameters multiplied by their weights yields the total dermoscopy value (TDV); hence, the lesion is classified into benign, suspicious or malignant. The proposed approach is implemented in the MATLAB environment and the experiment is based on PH2 database containing suspicious melanoma skin cancer. Results and Conclusion: Based on the experiment, the accuracy of the developed approach is 90%, which reflects its reliability.

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