TY - GEN
T1 - Acceleration of two point correlation function calculation for pathology image segmentation
AU - Cooper, Lee Alex Donald
AU - Saltz, Joel H.
AU - Catalyurek, Umit
AU - Huang, Kun
PY - 2011
Y1 - 2011
N2 - The segmentation of tissue regions in high-resolution microscopy is a challenging problem due to both the size and appearance of digitized pathology sections. The two point correlation function (TPCF) has proved to be an effective feature to address the textural appearance of tissues. However the calculation of the TPCF functions is computationally burdensome and often intractable in the gigapixel images produced by slide scanning devices for pathology application. In this paper we present several approaches for accelerating deterministic calculation of point correlation functions using theory to reduce computation, parallelization on distributed systems, and parallelization on graphics processors. Previously we show that the correlation updating method of calculation offers an 8-35x speedup over frequency domain methods and decouples efficient computation from the select scales of Fourier methods. In this paper, using distributed computation on 64 compute nodes provides a further 42x speedup. Finally, parallelization on graphics processors (GPU) results in an additional 11-16x speedup using an implementation capable of running on a single desktop machine.
AB - The segmentation of tissue regions in high-resolution microscopy is a challenging problem due to both the size and appearance of digitized pathology sections. The two point correlation function (TPCF) has proved to be an effective feature to address the textural appearance of tissues. However the calculation of the TPCF functions is computationally burdensome and often intractable in the gigapixel images produced by slide scanning devices for pathology application. In this paper we present several approaches for accelerating deterministic calculation of point correlation functions using theory to reduce computation, parallelization on distributed systems, and parallelization on graphics processors. Previously we show that the correlation updating method of calculation offers an 8-35x speedup over frequency domain methods and decouples efficient computation from the select scales of Fourier methods. In this paper, using distributed computation on 64 compute nodes provides a further 42x speedup. Finally, parallelization on graphics processors (GPU) results in an additional 11-16x speedup using an implementation capable of running on a single desktop machine.
KW - Digital Pathology
KW - Graphical Processing Unit
KW - Image Segmentation
KW - Microscopy
KW - Two Point Correlation Function
UR - http://www.scopus.com/inward/record.url?scp=81355163931&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=81355163931&partnerID=8YFLogxK
U2 - 10.1109/HISB.2011.10
DO - 10.1109/HISB.2011.10
M3 - Conference contribution
C2 - 30009263
AN - SCOPUS:81355163931
SN - 9780769544076
T3 - Proceedings - 2011 1st IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology, HISB 2011
SP - 174
EP - 181
BT - Proceedings - 2011 1st IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology, HISB 2011
T2 - 2011 1st IEEE International Conference on Healthcare Informatics, Imaging and Systems Biology, HISB 2011
Y2 - 26 July 2011 through 29 July 2011
ER -