TY - GEN
T1 - Registering sequences of in vivo microscopy images for cell tracking using dynamic programming and minimum spanning trees
AU - McArdle, Sara
AU - Acton, Scott T.
AU - Ley, Klaus
AU - Ray, Nilanjan
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014/1/28
Y1 - 2014/1/28
N2 - Registration of in vivo microscopy image sequences is important for tracking of cells. Registering a long sequence of in vivo microscopy images is particularly challenging for several reasons, which include motion artifacts created by the cardiac cycle and breathing movements of the living subject, occasional defocussing, illumination change, and noise in image acquisition. To accommodate these variations, we sample time points redundantly during microscopic image acquisition. Second, we use dynamic programming to select image frames with tolerable motion and eliminate those with large motion. Third, we employ a novel method based on the minimum spanning tree algorithm to register the selected image frames. Testing on actual in vivo image sequences reveals that our approach excels over three existing registration methods in terms of structural image similarity of the registered images.
AB - Registration of in vivo microscopy image sequences is important for tracking of cells. Registering a long sequence of in vivo microscopy images is particularly challenging for several reasons, which include motion artifacts created by the cardiac cycle and breathing movements of the living subject, occasional defocussing, illumination change, and noise in image acquisition. To accommodate these variations, we sample time points redundantly during microscopic image acquisition. Second, we use dynamic programming to select image frames with tolerable motion and eliminate those with large motion. Third, we employ a novel method based on the minimum spanning tree algorithm to register the selected image frames. Testing on actual in vivo image sequences reveals that our approach excels over three existing registration methods in terms of structural image similarity of the registered images.
KW - dynamic programming
KW - image sequence registration
KW - in vivo microscopy
KW - minimum spanning tree
UR - http://www.scopus.com/inward/record.url?scp=84949928910&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84949928910&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2014.7025720
DO - 10.1109/ICIP.2014.7025720
M3 - Conference contribution
AN - SCOPUS:84949928910
T3 - 2014 IEEE International Conference on Image Processing, ICIP 2014
SP - 3547
EP - 3551
BT - 2014 IEEE International Conference on Image Processing, ICIP 2014
PB - Institute of Electrical and Electronics Engineers Inc.
ER -