TY - GEN
T1 - Computing maximum association graph in microscopic nucleus images
AU - Stojkovic, Branislav
AU - Zhu, Yongding
AU - Xu, Jinhui
AU - Fritz, Andrew
AU - Zeitz, Michael J.
AU - Vecerova, Jaromira
AU - Berezney, Ronald
PY - 2010
Y1 - 2010
N2 - In this paper, we study the problem of finding organization patterns of chromosomes inside the cell nucleus from microscopic nucleus images. Emerging evidence from cell biology research suggests that global chromosome organization has a vital role in fundamental cell processes related to gene expression and regulation. To understand how chromosome territories are neighboring (or associated) to each other, in this paper we present a novel technique for computing a common association pattern, represented as a Maximum Association Graph (MAG), from the nucleus images of a population of cells. Our approach is based on an interesting integer linear programming formulation of the problem and utilizes inherent observations of the problem to yield optimal solutions. A two-stage technique is also introduced for producing near optimal approximations for large data sets.
AB - In this paper, we study the problem of finding organization patterns of chromosomes inside the cell nucleus from microscopic nucleus images. Emerging evidence from cell biology research suggests that global chromosome organization has a vital role in fundamental cell processes related to gene expression and regulation. To understand how chromosome territories are neighboring (or associated) to each other, in this paper we present a novel technique for computing a common association pattern, represented as a Maximum Association Graph (MAG), from the nucleus images of a population of cells. Our approach is based on an interesting integer linear programming formulation of the problem and utilizes inherent observations of the problem to yield optimal solutions. A two-stage technique is also introduced for producing near optimal approximations for large data sets.
UR - https://www.scopus.com/pages/publications/78349274388
U2 - 10.1007/978-3-642-15745-5_65
DO - 10.1007/978-3-642-15745-5_65
M3 - Conference contribution
C2 - 20879356
AN - SCOPUS:78349274388
SN - 3642157440
SN - 9783642157448
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 530
EP - 537
BT - Medical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings
T2 - 13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010
Y2 - 20 September 2010 through 24 September 2010
ER -