Literature DB >> 19964807

Detection of tissue folds in whole slide images.

Pinky A Bautista1, Yukako Yagi.   

Abstract

In whole slide imaging (WSI) the quality of scanned images is an interplay between the hardware specifications of the scanning device and the condition of the tissue slide itself. Tissue artifacts such as folds and bubbles have been known to affect the efficiency of a whole slide scanning system in selecting the focus points wherein the presence of the said artifacts have been found to produce blur or unfocused images. Thus, for a whole slide scanning device to produce the best image quality, even with the presence of tissue artifacts, information on the location of these artifacts should be known such that they can be avoided in the selection of the focus points. In this paper we introduced an enhancement method to emphasize and detect the location of the tissue folds from whole slide images. Results of the experiments that we conducted on various H&E stained images that were scanned using different scanners show the robustness of the method to detect tissue folds.

Entities:  

Mesh:

Year:  2009        PMID: 19964807     DOI: 10.1109/IEMBS.2009.5334529

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  6 in total

1.  Pathology Imaging Informatics for Clinical Practice and Investigative and Translational Research.

Authors:  Evita T Sadimin; David J Foran
Journal:  N Am J Med Sci (Boston)       Date:  2012-04

2.  Improving the visualization and detection of tissue folds in whole slide images through color enhancement.

Authors:  Pinky A Bautista; Yukako Yagi
Journal:  J Pathol Inform       Date:  2010-11-29

3.  High-definition hematoxylin and eosin staining in a transition to digital pathology.

Authors:  Jamie D Martina; Christopher Simmons; Drazen M Jukic
Journal:  J Pathol Inform       Date:  2011-10-19

Review 4.  Pathology imaging informatics for quantitative analysis of whole-slide images.

Authors:  Sonal Kothari; John H Phan; Todd H Stokes; May D Wang
Journal:  J Am Med Inform Assoc       Date:  2013-08-19       Impact factor: 4.497

5.  Eliminating tissue-fold artifacts in histopathological whole-slide images for improved image-based prediction of cancer grade.

Authors:  Sonal Kothari; John H Phan; May D Wang
Journal:  J Pathol Inform       Date:  2013-08-31

Review 6.  Machine Learning Methods for Histopathological Image Analysis.

Authors:  Daisuke Komura; Shumpei Ishikawa
Journal:  Comput Struct Biotechnol J       Date:  2018-02-09       Impact factor: 7.271

  6 in total

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