Intrinsic Melanin and Hemoglobin Colour Components for Skin Lesion Malignancy Detection

Intrinsic Melanin and Hemoglobin Colour Components for Skin Lesion Malignancy Detection Tu-1-MU- 33 Ali Madooei, Mark S. Drew, Maryam Sadeghi, and M. Stella Atkins School of Computing Science, Simon Fraser University oposed a new colour-space formation which is aimed at apprehending and hemoglobin biological components of dermoscopy images of skin l The new colour-space is used in supervised learning to achieve excellent malignant vs. benign skin lesion classification and skin lesion segmentation. Feature Extraction Malignant Benign Precision: 0.894 Recall: 0.894 F-measure: 0.894 AUC: 0.953 Logisti c Classif ier Separation of underlying Melanin Hemoglobin Geo-mean Lesion Segmentation Precision: 0.89 Recall: 0.90 F-measure: 0.89 Otsu Dermoscopy Image of Melanoma Imaging Model ICA Dermoscopy Image of Melanoma The most severe and potentially fatal form of Malignant skin cancer oposed a new colour-space formation which is aimed at apprehending and haemoglobin biological components of dermoscopy images of skin The new colour-space is used in supervised learning to achieve excellent malignant vs. benign skin lesion classification and skin lesion segmentation.

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Intrinsic Melanin and Hemoglobin Colour Components for Skin Lesion Malignancy Detection. Ali Madooei, Mark S. Drew, Maryam Sadeghi , and M . Stella Atkins School of Computing Science, Simon Fraser University. - PowerPoint PPT Presentation

Transcript of Intrinsic Melanin and Hemoglobin Colour Components for Skin Lesion Malignancy Detection

Intrinsic Melanin and Hemoglobin Colour Componentsfor Skin Lesion Malignancy Detection

Tu-1-MU-33

Ali Madooei, Mark S. Drew, Maryam Sadeghi, and M. Stella AtkinsSchool of Computing Science, Simon Fraser University

We have proposed a new colour-space formation which is aimed at apprehending underlyingmelanin and hemoglobin biological components of dermoscopy images of skin lesions.

The new colour-space is used in supervised learning to achieve excellent malignant vs. benign skin lesion classification and skin lesion segmentation.

Feature Extraction Malignant vs. BenignPrecision: 0.894Recall: 0.894F-measure: 0.894AUC: 0.953

Logistic Classifier

Separation of underlying

Melanin Hemoglobin

Geo-mean

Lesion SegmentationPrecision: 0.89Recall: 0.90F-measure: 0.89

Otsu

Dermoscopy Image of Melanoma

Imaging Model

ICA

Dermoscopy Image of Melanoma The most severe and potentially fatal form of Malignant skin cancer

We have proposed a new colour-space formation which is aimed at apprehending underlyingmelanin and haemoglobin biological components of dermoscopy images of skin lesions.

The new colour-space is used in supervised learning to achieve excellent malignant vs. benign skin lesion classification and skin lesion segmentation.