AI-Enabled Support System for Melanoma Detection and Classification

Skin lesion melanoma is the deadliest type of cancer. Artificial intelligence provides the power to classify skin lesions as melanoma and non-melanoma. The proposed system for melanoma detection and classification involves four steps: pre-processing, resizing all the images, removing noise and hair...

Full description

Saved in:
Bibliographic Details
Published inInternational journal of reliable and quality e-healthcare Vol. 10; no. 4; pp. 58 - 75
Main Authors Sen Saxena, Vivek, Johri, Prashant, Kumar, Avneesh
Format Journal Article
LanguageEnglish
Published Hershey IGI Global 01.10.2021
Subjects
Algorithms
Artificial intelligence
Classification
Data mining
Decision making
Feature extraction
Image processing
Image segmentation
Lesions
Machine learning
Melanoma
Neural networks
Performance measurement
Skin
Skin cancer
Support systems
India
Online AccessGet full text

Cover

More Information
Summary:Skin lesion melanoma is the deadliest type of cancer. Artificial intelligence provides the power to classify skin lesions as melanoma and non-melanoma. The proposed system for melanoma detection and classification involves four steps: pre-processing, resizing all the images, removing noise and hair from dermoscopic images; image segmentation, identifying the lesion area; feature extraction, extracting features from segmented lesion and classification; and categorizing lesion as malignant (melanoma) and benign (non-melanoma). Modified GrabCut algorithm is employed to generate skin lesion. Segmented lesions are classified using machine learning algorithms such as SVM, k-NN, ANN, and logistic regression and evaluated on performance metrics like accuracy, sensitivity, and specificity. Results are compared with existing systems and achieved higher similarity index and accuracy.
ISSN:2160-9551
2160-956X
DOI:10.4018/IJRQEH.2021100104