Title :
Thyroid Texture Representation via Noise Resistant Image Features
Author :
Keramidas, Eystratios G. ; Iakovidis, Dimitris K. ; Maroulis, Dimitris ; Dimitropoulos, Nikos
Author_Institution :
Dept. of Inf. & Telecommun., Athens Univ., Athens
Abstract :
The robustness of textural features on speckle noise is of vital importance for ultrasound imaging. A set of novel fuzzy features for thyroid ultrasound texture representation, demonstrating noise-resistant properties, is presented, analyzed and evaluated in this study. The textural feature extraction scheme is based on the fuzzyfication of the local binary pattern approach. The proposed features are evaluated on an annotated dataset of B-mode thyroid ultrasound images acquired from 75 patients. The experimental results illustrate that these features provide accurate representation of the thyroid texture. They can be effectively utilized for thyroid nodule detection outperforming other thyroid texture representation approaches that have been recently proposed in the literature.
Keywords :
biomedical ultrasonics; feature extraction; image representation; image texture; medical image processing; speckle; ultrasonic imaging; B-mode thyroid ultrasound images; fuzzy features; local binary pattern; noise resistant image features; noise-resistant properties; speckle noise; textural feature extraction; textural features; thyroid texture representation; thyroid ultrasound texture representation; ultrasound imaging; Biomedical imaging; Feature extraction; Fuzzy logic; Glands; Image texture analysis; Immune system; Medical diagnostic imaging; Speckle; Ultrasonic imaging; Uncertainty; Fuzzy; Local Binary Pattern; Noise; Texture; Thyroid; Ultrasound;
Conference_Titel :
Computer-Based Medical Systems, 2008. CBMS '08. 21st IEEE International Symposium on
Conference_Location :
Jyvaskyla
Print_ISBN :
978-0-7695-3165-6
DOI :
10.1109/CBMS.2008.108