Journal of Pathology Informatics

RESEARCH ARTICLE
Year
: 2018  |  Volume : 9  |  Issue : 1  |  Page : 48-

Super-resolution digital pathology image processing of bone marrow aspirate and cytology smears and tissue sections


Amol Singh, Robert S Ohgami 
 Department of Pathology, Stanford University, Stanford, CA 94305, USA

Correspondence Address:
Dr. Robert S Ohgami
Department of Pathology, Stanford University, 300 Pasteur Drive, L235, Stanford, CA 94305
USA

Background: Accurate digital pathology image analysis depends on high-quality images. As such, it is imperative to obtain digital images with high resolution for downstream data analysis. While hematoxylin and eosin (H&E)-stained tissue section slides from solid tumors contain three-dimensional information, these data have been ignored in digital pathology. In addition, in cytology and bone marrow aspirate smears, the three-dimensional nature of the specimen has precluded efficient analysis of such morphologic data. An individual image snapshot at a single focal distance is often not sufficient for accurate diagnoses and multiple whole-slide images at different focal distances are necessary for diagnostics. Materials and Methods: We describe a novel computational pipeline and processing program for obtaining a super-resolved image from multiple static images at different z-planes in overlapping but separate frames. This program, MULTI-Z, performs image alignment, Gaussian smoothing, and Laplacian filtering to construct a final super-resolution image from multiple images. Results: We applied this algorithm and program to images of cytology and H&E-stained sections and demonstrated significant improvements in both resolution and image quality by objective data analyses (24% increase in sharpness and focus). Conclusions: With the use of our program, super-resolved images of cytology and H&E-stained tissue sections can be obtained to potentially allow for more optimal downstream computational analysis. This method is applicable to whole-slide scanned images.


How to cite this article:
Singh A, Ohgami RS. Super-resolution digital pathology image processing of bone marrow aspirate and cytology smears and tissue sections.J Pathol Inform 2018;9:48-48


How to cite this URL:
Singh A, Ohgami RS. Super-resolution digital pathology image processing of bone marrow aspirate and cytology smears and tissue sections. J Pathol Inform [serial online] 2018 [cited 2019 Mar 22 ];9:48-48
Available from: http://www.jpathinformatics.org/article.asp?issn=2153-3539;year=2018;volume=9;issue=1;spage=48;epage=48;aulast=Singh;type=0