Automatic Framework for Processing Drosophila Embryonic Images (NSF
IIS)
Project Summary:
High resolution embryonic images, e.g., the data set BDGP (Berkley
Drosophila Genome Project), have been introduced as an important tool
for the discovery of gene-gene interaction. These images contain not
only temporal information of a gene but also precise spatial
information of expression regions of genes. So the biologic problem of
the discovery of gene-gene interaction can be characterized as a
computational problem of matching expression patterns of embryos at the
same developmental stage. It is, however, very challenging to design a
fully automatic computational system due to severe imaging and
artificial variations in embryonic images. Current research on
embryonic image processing involves significant manual manipulation or
addresses only a small subset of variations. In this project, I will
develop a comprehensive automatic framework to achieve the three
fundamental tasks: image standardization, stage determination, and
expression pattern modeling.
Undergraduate Students:
Current:
Former:
Publications:
- Qi Li: A Hybrid
Representation of Imbalanced Points for Two-Layer Matching. International
Conference on Image Analysis and Recognition, ICIAR (1) 2011:
232-241
- Qi Li
and Chang-Tien Lu: Appearance
Based Recognition Using Spatial and Discriminant Influence.
International
Conference on Machine Learning and Applications, ICMLA 2010: 78-83