Referenceless image quality evaluation for whole slide imaging

Objective: The image quality in whole slide imaging (WSI) is one of the most important issues for the practical use of WSI scanners. In this paper, we proposed an image quality evaluation method for scanned slide images in which no reference image is required. Methods: While most of the conventional...

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Main Authors: Noriaki Hashimoto (Author), Pinky A Bautista (Author), Masahiro Yamaguchi (Author), Nagaaki Ohyama (Author), Yukako Yagi (Author)
Format: Book
Published: Elsevier, 2012-01-01T00:00:00Z.
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042 |a dc 
100 1 0 |a Noriaki Hashimoto  |e author 
700 1 0 |a Pinky A Bautista  |e author 
700 1 0 |a Masahiro Yamaguchi  |e author 
700 1 0 |a Nagaaki Ohyama  |e author 
700 1 0 |a Yukako Yagi  |e author 
245 0 0 |a Referenceless image quality evaluation for whole slide imaging 
260 |b Elsevier,   |c 2012-01-01T00:00:00Z. 
500 |a 2153-3539 
500 |a 2153-3539 
500 |a 10.4103/2153-3539.93891 
520 |a Objective: The image quality in whole slide imaging (WSI) is one of the most important issues for the practical use of WSI scanners. In this paper, we proposed an image quality evaluation method for scanned slide images in which no reference image is required. Methods: While most of the conventional methods for no-reference evaluation only deal with one image degradation at a time, the proposed method is capable of assessing both blur and noise by using an evaluation index which is calculated using the sharpness and noise information of the images in a given training data set by linear regression analysis. The linear regression coefficients can be determined in two ways depending on the purpose of the evaluation. For objective quality evaluation, the coefficients are determined using a reference image with mean square error as the objective value in the analysis. On the other hand, for subjective quality evaluation, the subjective scores given by human observers are used as the objective values in the analysis. The predictive linear regression models for the objective and subjective image quality evaluations, which were constructed using training images, were then used on test data wherein the calculated objective values are construed as the evaluation indices. Results: The results of our experiments confirmed the effectiveness of the proposed image quality evaluation method in both objective and subjective image quality measurements. Finally, we demonstrated the application of the proposed evaluation method to the WSI image quality assessment and automatic rescanning in the WSI scanner. 
546 |a EN 
690 |a Digital pathology 
690 |a image quality evaluation 
690 |a linear regression analysis 
690 |a visualization 
690 |a whole slide imaging 
690 |a Computer applications to medicine. Medical informatics 
690 |a R858-859.7 
690 |a Pathology 
690 |a RB1-214 
655 7 |a article  |2 local 
786 0 |n Journal of Pathology Informatics, Vol 3, Iss 1, Pp 9-9 (2012) 
787 0 |n http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2012;volume=3;issue=1;spage=9;epage=9;aulast=Hashimoto 
787 0 |n https://doaj.org/toc/2153-3539 
787 0 |n https://doaj.org/toc/2153-3539 
856 4 1 |u https://doaj.org/article/4a958df7925e46d2b74f15f99a492f02  |z Connect to this object online.