Structured Correlation Detection with Application to Colocalization   Analysis in Dual-Channel Fluorescence Microscopic Imaging
  Motivated by the problem of colocalization analysis in fluorescence microscopic imaging, we study in this paper structured detection of correlated regions between two random processes observed on a common domain. We argue that although intuitive, direct use of the maximum log-likelihood statistic suffers from potential bias and substantially reduced power, and introduce a simple size-based normalization to overcome this problem. We show that scanning with the proposed size-corrected likelihood ratio statistics leads to optimal correlation detection over a large collection of structured correlation detection problems. 
Shulei Wang, Jianqing Fan, Ginger Pocock and Ming Yuan
math.ST stat.AP stat.ME stat.TH