PMID- 17970921
OWN - NLM
STAT- MEDLINE
DCOM- 20071214
LR  - 20100324
IS  - 0022-2720 (Print)
IS  - 0022-2720 (Linking)
VI  - 228
IP  - Pt 2
DP  - 2007 Nov
TI  - Image enhancement for increased dot-counting efficiency in FISH.
PG  - 211-26
AB  - BACKGROUND: The most commonly used molecular cytogenetic technique is 
      fluorescence in situ hybridization (FISH). It has been widely applied in many 
      areas of diagnosis and research, including pre-natal and post-natal screening of 
      chromosomal aberrations, pre-implantation genetic diagnosis, cancer cytogenetics, 
      gene mapping, molecular pathology and developmental molecular biology. The 
      analysis of FISH images consists of detecting fluorescent dots, after which the 
      number of dots per cell can be counted or their relative positions can be 
      measured. A major impediment in the analysis of FISH specimens is signal (dot) 
      quality, which is influenced by the hybridization efficiency and/or the 
      sensitivity of the camera that records the images. METHOD: In this paper, we 
      present an approach to improve the efficiency of detecting fluorescent signals in 
      FISH images by recovering the radiance map of the camera. This allows us to 
      generate a high-dynamic-range image wherein an extended range of the sample 
      radiance captured by the camera can be visualized at distinct intensity values. 
      The resulting higher-order numeric complexity of the transformed image is 
      adjusted (or simplified) by examining the intensity distribution in each of the 
      three colour channels (red, green and blue), and remapping the intensity values 
      to generate a high-contrast image with a lower-order (compressed) dynamic range. 
      The remapping is based on a criterion that optimizes the detection of the 
      hybridized signals, allowing attenuation of saturated intensity values while 
      amplifying low-intensity signals. RESULTS: A simple dot-counting algorithm is 
      used to automatically process 2000 FISH images. The images are taken for 
      lymphocytes from cultured blood specimens for cytogenetic testing. Images are 
      manually analyzed by an expert to obtain ground truth for dot counts. A 
      quantitative analysis is performed by comparing results of automated dot 
      detection on images before and after enhancement with the developed algorithms. 
      In addition, common errors in dot counting due to split dots, dust, poor 
      segmentation and overlapping signals are analyzed and the robustness of the 
      developed approach against these errors evaluated. It is observed that 
      dot-detection efficiency is increased by an average of 9% across all colour 
      channels while reducing errors in missed and false dot counts. CONCLUSIONS: Our 
      proposed method and results demonstrate that dot-counting specificity and 
      sensitivity can be improved by pre-processing and enhancing the image using the 
      radiance curve of the camera and generating a high-contrast, remapped 
      high-dynamic-range image prior to using any algorithm for dot counting.
FAU - Shah, Shishir
AU  - Shah S
AD  - University of Houston, Department of Computer Science, Houston, TX 77204-3010, 
      USA. shah@cs.uh.edu
LA  - eng
PT  - Journal Article
PL  - England
TA  - J Microsc
JT  - Journal of microscopy
JID - 0204522
SB  - IM
MH  - *Algorithms
MH  - Automation
MH  - Cells, Cultured
MH  - Humans
MH  - Image Enhancement/*methods
MH  - In Situ Hybridization, Fluorescence/*methods
MH  - Lymphocytes
EDAT- 2007/11/01 09:00
MHDA- 2007/12/15 09:00
CRDT- 2007/11/01 09:00
PHST- 2007/11/01 09:00 [pubmed]
PHST- 2007/12/15 09:00 [medline]
PHST- 2007/11/01 09:00 [entrez]
AID - JMI1842 [pii]
AID - 10.1111/j.1365-2818.2007.01842.x [doi]
PST - ppublish
SO  - J Microsc. 2007 Nov;228(Pt 2):211-26. doi: 10.1111/j.1365-2818.2007.01842.x.