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Proceedings Paper

Assessment of a CAD scheme in selecting the optimal focused microscopic scanning images of the metaphase chromosomes
Author(s): Xingwei Wang; Jun Tan; Yuchen Qiu; Yuhua Li; Hong Liu; Shibo Li; Bin Zheng
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Paper Abstract

Visually searching for analyzable metaphase chromosome cells under microscopes is a routine and timeconsuming task in genetic laboratories to diagnose cancer and genetic disorders. To improve detection efficiency, consistency, and accuracy, we developed an automated microscopic image scanning system using a 100X oil immersion objective lens to acquire images that has sufficient spatial resolution allowing clinicians to do diagnosis. Due to the highresolution, the field of image depth is very limited and multiple scans up to seven layers are required. Thus, a metaphase cell can spread over multiple images at different focal levels. Among them only one or two are adequate for the diagnosis and the others are typically fuzzy images. In this study, we developed and tested a computer-aided detection (CAD) scheme to automatically select one image with the sharpest image quality and discard all of the other fuzzy images based on the computed sharpness index. From three scanned bone marrow specimen slides, the on-line and offline metaphase finding modules automatically selected 100 chromosome cells with 534 images. These images were selected to build a testing dataset. For each cell, the CAD scheme selects one image with the maximum sharpness index. Three observers also independently visually selected one best image for diagnosis from each cell. The agreement rate between CAD and visually selected images ranges from 89% to 96%, which is also very comparable to the agreement rate between the two observers. This experiment demonstrated the feasibility of applying a CAD scheme to select the images with sharpest high-resolution metaphase chromosome cell and potentially improve diagnostic efficiency and accuracy in the future clinical practice.

Paper Details

Date Published: 3 March 2011
PDF: 7 pages
Proc. SPIE 7966, Medical Imaging 2011: Image Perception, Observer Performance, and Technology Assessment, 796618 (3 March 2011); doi: 10.1117/12.876864
Show Author Affiliations
Xingwei Wang, Univ. of Pittsburgh (United States)
Jun Tan, Univ. of Pittsburgh (United States)
Yuchen Qiu, The Univ. of Oklahoma (United States)
Yuhua Li, The Univ. of Oklahoma (United States)
Hong Liu, The Univ. of Oklahoma (United States)
Shibo Li, The Univ. of Oklahoma Health Sciences Ctr. (United States)
Bin Zheng, Univ. of Pittsburgh (United States)


Published in SPIE Proceedings Vol. 7966:
Medical Imaging 2011: Image Perception, Observer Performance, and Technology Assessment
David J. Manning; Craig K. Abbey, Editor(s)

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