Affiliations: Center for Bioengineering and School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK, USA | College of Precision Instrument and Opto-Electronics Engineering, Tianjin University, Tianjin, China | Department of Engineering and Physics, University of Central Oklahoma, Edmond, OK, USA | Department of Radiology, University of Pittsburgh, Pittsburgh, PA, USA | Department of Pediatrics, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
Note: [] Corresponding author: Hong Liu, Center for Bioengineering and School of Electrical and Computer Engineering, University of Oklahoma, 101 David L Boren Blvd, Norman, OK 73019, USA. Tel.: +1 405 325 4286; Fax: +1 405 325 7066; E-mail: liu@ou.edu
Abstract: BACKGROUND: Auto-focusing is an important operation in high throughput imaging scanning. Although many auto-focusing methods have been developed and tested for a variety of imaging modalities, few investigations have been performed on the selection of an optimal auto-focusing method that is suitable for the pathological metaphase chromosome analysis under a high resolution scanning microscopic system. OBJECTIVE: The purpose of this study is to investigate and identify an optimal auto-focusing method for the pathological metaphase chromosome analysis. METHODS: In this study, five auto-focusing methods were applied and tested using metaphase chromosome images acquired from bone marrow and blood specimens. These methods were assessed by measuring a number of indices including execution time, accuracy, number of false maxima, and full width at half maximum (FWHM). RESULTS: For the specific condition investigated in this study, the results showed that the Brenner gradient and threshold pixel counting methods were the optimal methods for acquiring high quality metaphase chromosome images from the bone marrow and blood specimens, respectively. CONCLUSIONS: Selecting an optimal auto-focusing method depends on the specific clinical tasks. This study also provides useful information for the design and implementation of the high throughput microscopic image scanning systems in the future digital pathology.
