title: Fusion of spatial gray level dependency and fractal texture features for the characterization of thyroid lesions.
abstract: Thyroid is a small gland situated at the anterior side of the neck and one of the largest glands of the endocrine system. The abrupt cell growth or malignancy in the thyroid gland may cause thyroid cancer. Ultrasound images distinctly represent benign and malignant lesions, but accuracy may be poor due to subjective interpretation. Computer Aided Diagnosis (CAD) can minimize the errors created due to subjective interpretation and assists to make fast accurate diagnosis. In this work, fusion of Spatial Gray Level Dependence Features (SGLDF) and fractal textures are used to decipher the intrinsic structure of benign and malignant thyroid lesions. These features are subjected to graph based Marginal Fisher Analysis (MFA) to reduce the number of features. The reduced features are subjected to various ranking methods and classifiers. We have achieved an average accuracy, sensitivity and specificity of 97.52%, 90.32% and 98.57% respectively using Support Vector Machine (SVM) classifier. The achieved maximum Area Under Curve (AUC) is 0.9445. Finally, Thyroid Clinical Risk Index (TCRI) a single number is developed using two MFA features to discriminate the two classes. This prototype system is ready to be tested with huge diverse database.
authors.affiliation: Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal University, Manipal 576104, India. Electronic address: raghavendra.u@manipal.edu.
authors.forename: U
authors.initials: U
authors.lastname: Raghavendra
authors.affiliation: Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Clementi 599489, Singapore; Department of Biomedical Engineering, School of Science and Technology, SIM University, Clementi 599491, Singapore; Department of Biomedical Engineering, Faculty of Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia.
authors.forename: U
authors.initials: U
authors.lastname: Rajendra Acharya
authors.affiliation: Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal University, Manipal 576104, India.
authors.forename: Anjan
authors.initials: A
authors.lastname: Gudigar
authors.affiliation: Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Clementi 599489, Singapore.
authors.forename: Jen
authors.initials: J
authors.lastname: Hong Tan
authors.affiliation: Iwate Prefectural University (IPU), Faculty of Software and Information Science, Iwate, Japan.
authors.forename: Hamido
authors.initials: H
authors.lastname: Fujita
authors.affiliation: Department of Electronics and Computer Engineering, Ngee Ann Polytechnic, Clementi 599489, Singapore.
authors.forename: Yuki
authors.initials: Y
authors.lastname: Hagiwara
authors.affiliation: Department of Electronics and Telecommunications, Politecnico di Torino, Italy.
authors.forename: Filippo
authors.initials: F
authors.lastname: Molinari
authors.affiliation: Department of Radiology, Faculty of Medicine, Chiang Mai University, Chiang Mai, 50200, Thailand.
authors.forename: Pailin
authors.initials: P
authors.lastname: Kongmebhol
authors.affiliation: Department of Biomedical Imaging, University of Malaya, Kuala Lumpur, Malaysia.
authors.forename: Kwan
authors.initials: K
authors.lastname: Hoong Ng
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D002648:Child; D003936:Diagnosis, Computer-Assisted; D003937:Diagnosis, Differential; D005260:Female; D017709:Fractals; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D012189:Retrospective Studies; D012680:Sensitivity and Specificity; D060388:Support Vector Machine; D013964:Thyroid Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology*; D014463:Ultrasonography / Q000379:methods*
keywords: CAD; Classification; Fractal features; Marginal fisher analysis; Thyroid