Computer aided diagnosis for thyroid cancer system based on internal and external characteristics
Author(s) -
Hanung Adi Nugroho,
Zulfanahri,
Eka Legya Frannita,
Igi Ardiyanto,
Lina Choridah
Publication year - 2019
Publication title -
journal of king saud university - computer and information sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.617
H-Index - 33
eISSN - 2213-1248
pISSN - 1319-1578
DOI - 10.1016/j.jksuci.2019.01.007
Subject(s) - computer aided diagnosis , thyroid nodules , artificial intelligence , nodule (geology) , computer science , thyroid cancer , support vector machine , malignancy , radiology , computer aided , perceptron , pattern recognition (psychology) , speckle noise , medicine , cancer , speckle pattern , artificial neural network , pathology , paleontology , biology , programming language
Background and aims Thyroid cancer is one of the fastest growing cancers worldwide. Thyroid ultrasound images are diagnosed based on several characteristics to determine the malignancy of the nodule. The characteristics are divided into two, i.e. external characteristics and internal characteristics. A computer-aided diagnosis (CADx) is necessary to assist radiologists in analysing these characteristics more objectively. Methods Firstly, a pre-processing step was applied to remove label and reduce speckle noise by applying adaptive median filter followed by bilateral filter. Secondly, active contour and morphology operation were applied to segment the nodules. Subsequently, geometric and texture features were extracted. In the final step, multilayer perceptron was used to classify internal characteristics while support vector machine was used for classifying external characteristics. Results The sensitivity, specificity and accuracy of nodule classification based on analysis of external characteristics were 100%, 95.45% and 97.78%, respectively, whereas classification results based on internal characteristics were 95.35%, 90.91% and 94.44%, respectively. Conclusion A computer-aided diagnosis (CADx) for thyroid cancer system based on analysis of external and internal characteristics has been developed. The sensitivity, specificity and level of accuracy for both characteristics showed that the proposed system was reliable to assist radiologist in classifying thyroid nodules.
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