TY - GEN
T1 - Barcode annotations for medical image retrieval
T2 - IEEE International Conference on Image Processing, ICIP 2015
AU - Tizhoosh, H. R.
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/12/9
Y1 - 2015/12/9
N2 - This paper proposes to generate and to use barcodes to annotate medical images and/or their regions of interest such as organs, tumors and tissue types. A multitude of efficient feature-based image retrieval methods already exist that can assign a query image to a certain image class. Visual annotations may help to increase the retrieval accuracy if combined with existing feature-based classification paradigms. Whereas with annotations we usually mean textual descriptions, in this paper barcode annotations are proposed. In particular, Radon barcodes (RBC) are introduced. As well, local binary patterns (LBP) and local Radon binary patterns (LRBP) are implemented as barcodes. The IRMA x-ray dataset with 12,677 training images and 1,733 test images is used to verify how barcodes could facilitate image retrieval.
AB - This paper proposes to generate and to use barcodes to annotate medical images and/or their regions of interest such as organs, tumors and tissue types. A multitude of efficient feature-based image retrieval methods already exist that can assign a query image to a certain image class. Visual annotations may help to increase the retrieval accuracy if combined with existing feature-based classification paradigms. Whereas with annotations we usually mean textual descriptions, in this paper barcode annotations are proposed. In particular, Radon barcodes (RBC) are introduced. As well, local binary patterns (LBP) and local Radon binary patterns (LRBP) are implemented as barcodes. The IRMA x-ray dataset with 12,677 training images and 1,733 test images is used to verify how barcodes could facilitate image retrieval.
KW - Medical image retrieval
KW - Radon transform
KW - annotation
KW - barcodes
KW - binary codes
KW - local binary pattern
UR - http://www.scopus.com/inward/record.url?scp=84956653516&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84956653516&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2015.7350913
DO - 10.1109/ICIP.2015.7350913
M3 - Conference contribution
AN - SCOPUS:84956653516
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 818
EP - 822
BT - 2015 IEEE International Conference on Image Processing, ICIP 2015 - Proceedings
PB - IEEE Computer Society
Y2 - 27 September 2015 through 30 September 2015
ER -