Implementing DEWA framework for early diagnosis of melanoma
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This document presents a framework called DEWA for early diagnosis of melanoma. DEWA uses image segmentation, color transformation, morphological filtering, and other computer vision and image processing techniques. It analyzes images based on the ABCD rule for melanoma features. An experiment applying DEWA to skin images achieved 83% accuracy in diagnosis. While promising, the authors note DEWA could be improved by correcting inaccuracies in color detection. The goal is to create an easy-to-use melanoma diagnosis tool for non-experts using smartphones.
Implementing DEWA framework for early diagnosis of melanoma
- 1. Implementing DEWA Framework for Early Diagnosis of Melanoma Setiawan Hadi, Bernard Y Tumbelaka, Budi Irawan, Rudi Rosadi Universitas Padjadjaran
- 2. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015 AGENDA ⢠Overview ⢠DEWA Framework ⢠Experiment ⢠Result ⢠Conclusion and future works
- 3. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015 Overview ⢠As one type of skin cancer, Melanoma can be considered as a deadliest type of skin cancer. The number of people infected are increasing year by year and are geographically distributed world wide. ⢠Computer vision researchers are interested in the automatic, vision- based, early diagnostic system of skin cancer. By developing a such system which is easily used by non-paramedic educated person, the people can visually check their skin as initial diagnosis without supporting of formal trained or skillful people. ⢠In this paper, a lightweight, lowcost application has been designed, based on the previous developed, integrated computer vision and image processing algorithms, called DEWA.
- 4. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015
- 5. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015 Overview ⢠As one type of skin cancer, Melanoma can be considered as a deadliest type of skin cancer. The number of people infected are increasing year by year and are geographically distributed world wide. ⢠Computer vision researchers are interested in the automatic, vision- based, early diagnostic system of skin cancer. By developing a such system which is easily used by non-paramedic educated person, the people can visually check their skin as initial diagnosis without supporting of formal trained or skillful people. ⢠In this paper, a lightweight, lowcost application has been designed, based on the previous developed, integrated computer vision and image processing algorithms, called DEWA.
- 6. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015
- 7. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015 Overview ⢠As one type of skin cancer, Melanoma can be considered as a deadliest type of skin cancer. The number of people infected are increasing year by year and are geographically distributed world wide. ⢠Computer vision researchers are interested in the automatic, vision- based, early diagnostic system of skin cancer. By developing a such system which is easily used by non-paramedic educated person, the people can visually check their skin as initial diagnosis without supporting of formal trained or skillful people. ⢠In this paper, a lightweight, lowcost application has been designed, based on the previous developed, integrated computer vision and image processing algorithms, called DEWA.
- 8. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015
- 9. METHODS
- 10. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015 DEWA ⢠Image Segmentation ⢠Color Transformation ⢠Morphological Filter ⢠Image Filtering ⢠K-Means/Improved K-Means ⢠Connected Component Labeling ⢠Object Classification ⢠Ellips detection
- 11. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015 ABCD Rule ⢠Assymetric ⢠Border ⢠Color ⢠Diameter ⢠TDS Index
- 12. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015 Illustration
- 13. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015 Simple Algorithm Load skin cancer image Apply DEWA algorithm to obtain noise-free image Image analysis based on ABCD Rule ⢠Determine the asymmetric value (A) ⢠Calculate the border irregularity (B) ⢠Get the color distribution (C) of skin image ⢠Compute the diameter (D) Computer TDS Index
- 14. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015 Data for Experiment
- 15. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015
- 16. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015 Result
- 17. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015 SISIK
- 18. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015 Conclusion ⢠Early diagnosis of melanoma is important step that can be useful to decrease the danger of skin cancer. By using public device such as smart phone, the diagnosis mechanism can be done by common people. ⢠DEWA as framework, utilized three multi aspects and can be considered as light framework because it has been deployed on small portable device successfully. ⢠The integrated methods that have been applied, even though it has been tested, and give promising result (83%). Some problems still found in the methods, such as inaccuracy in detection especially in color aspect need to be corrected.
- 19. Implementing DEWA Framework for Early Diagnosis of Melanoma, presented at ICCSCI 2015 Thank you for your attention.