Content Based Image Retrieval of Brain MR Images across Different Classes


Autoria(s): Kannan, Balakrishnan; Abraham, Varghese; Reji, Varghese R; Joseph, Paul S
Data(s)

22/07/2014

22/07/2014

2013

Resumo

Magnetic Resonance Imaging play a vital role in the decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale information is used to retrieve similar slices of T1 weighted images from T2 weighted images or vice versa. The incorporation of additional gray scale information on LBP can extract more local texture information. The accuracy of retrieval can be improved by extracting moment features of LBP and reweighting the features based on users’ feedback. Here retrieval is done in a single subject scenario where similar images of a particular subject at a particular level are retrieved, and multiple subjects scenario where relevant images at a particular level across the subjects are retrieved

International Journal of Electrical, Robotics, Electronics and Communications Engineering Vol:7 No:8, 2013

Cochin University of Science and Technology

Identificador

http://dyuthi.cusat.ac.in/purl/4233

Idioma(s)

en

Publicador

World Academy of Science

Palavras-Chave #Local Binary pattern (LBP) #Modified Local Binary pattern (MOD-LBP) #T1 and T2 weighted images #Moment features
Tipo

Article