Title
Shoulder lesion classification using shape and texture features via composite kernel.
Abstract
Axial proton density (PD) weighted magnetic resonance (MR) images of shoulder which has the ability to represent bone edema while preserving anatomical details, provides valuable information for the evaluation of traumatized shoulder. The low signal to noise ratio of PD weighted slices of MRI while being a powerful tool for the detection of the pathological conditions, can hamper the determination of the anatomical structures and has a negative effect on the classification success. This study focuses on the classification of pathologies of the humeral head resulting from trauma or instability. In order to diagnose the bone edema and structural changes of the humeral head by using images of low signal to noise ratio, the shape and texture information were used together and their contribution to the classification success was evaluated. The texture information was obtained from the gray-level co-occurrence matrix (GLCM) algorithm and shape information obtained from the pyramid of histogram of gradients (PHOG) algorithm were joined together by concatenation and composite kernel. The feature vectors obtained from experimental studies were utilized for classification purposes by support vector machines (SVM) and extreme learning machines (ELM) methods; the results were presented comparatively.
Year
Venue
Keywords
2017
Signal Processing and Communications Applications Conference
shoulder lesion,gray-level co-occurence matrix,pyramid of histogram of gradients,extreme learning machine,composite kernels,support vector machines,texture and shape information
Field
DocType
ISSN
Kernel (linear algebra),Computer vision,Histogram,Feature vector,Pattern recognition,Computer science,Support vector machine,Signal-to-noise ratio,Histogram of oriented gradients,Artificial intelligence,Concatenation,Pyramid
Conference
2165-0608
Citations 
PageRank 
References 
0
0.34
11
Authors
3
Name
Order
Citations
PageRank
Aysun Sezer153.51
Ibrahim Onur Sigirci211.39
Hasan Basri Sezer352.50