Melanoma Skin Cancer Detection based on Image Processing
| Autor: | Nadia Smaoui Zghal, Nabil Derbel |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Skin Neoplasms
Computer science Feature extraction Dermoscopy CAD Image processing 02 engineering and technology 030207 dermatology & venereal diseases 03 medical and health sciences 0302 clinical medicine Image Processing Computer-Assisted 0202 electrical engineering electronic engineering information engineering medicine Humans Preprocessor Radiology Nuclear Medicine and imaging Segmentation Diagnosis Computer-Assisted Stage (cooking) Melanoma business.industry Reproducibility of Results Pattern recognition medicine.disease 020201 artificial intelligence & image processing Artificial intelligence Skin cancer business Algorithms |
| Zdroj: | Current Medical Imaging Formerly Current Medical Imaging Reviews. 16:50-58 |
| ISSN: | 1573-4056 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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