شماره ركورد كنفرانس :
3297
عنوان مقاله :
Melanoma skin cancer detection using color and new texture features
عنوان به زبان ديگر :
Melanoma skin cancer detection using color and new texture features
پديدآورندگان :
Kharaji Nezhadian Farzam Faculty of Biomedical Engineering Islamic Azad University - Science and Research branch Tehran - Iran , Rashidi Saeid Faculty of Biomedical Engineering Islamic Azad University - Science and Research branch Tehran - Iran
كليدواژه :
turn count , active counter model , Melanoma , cancer detection , Melanoma
عنوان كنفرانس :
نوزدهمين سمپوزيوم بين المللي هوش مصنوعي و پردازش سيگنال
چكيده لاتين :
Melanoma is the most prevalent skin cancer and
sometimes it is very difficult to diagnose. Noninvasive
dermatoscopy is used to diagnose type of cancer. Since proposed
method is based on eye-deduction, diagnosis of melanoma in
early stage is difficult for dermatologist. A new algorithm is
presented to classify dermoscopic images into malignant and
benign. Initially the images were segmented using active counter
model and two features such as texture and colorful components
were extracted. Texture-based features were first in this area
used to diagnose disease and its results indicated high-efficacy. In
the international skin imaging collaboration dataset we achieve
accuracy of 97% by support vector machine classifier.
