AUTOMATED CROPPING AND ARTIFACT REMOVAL FOR KNIFE-EDGE SCANNING MICROSCOPY Conference Paper

abstract

• Knife Edge Scanning Microscopy (KESM) is a high-throughput imaging technique used to obtain large-scale anatomical information (1cm3) at sub-micrometer resolution. Data acquisition has been fully automated, however significant post-processing and reconstruction must be done manually. KESM is unique in that illumination and tissue sectioning are performed using a diamond knife. Therefore many of the physical forces applied to the knife (e.g., vibration, slip, and light refraction) manifest as image artifacts and must be removed in post-processing. In this paper, we propose a fully automated framework to extract valid data from imaged sections and remove lighting artifacts, allowing reconstruction of the volumetric structures in multiple terabyte-scale data sets. 2011 IEEE.

name of conference

• 2011 IEEE International Symposium on Biomedical Imaging: From Nano to Macro

authors

• Choe, Yoonsuck

published proceedings

• 2011 8TH IEEE INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING: FROM NANO TO MACRO

author list (cited authors)

• Kwon, J., Mayerich, D., & Choe, Y.

citation count

• 0

complete list of authors

• Kwon, Jaerock||Mayerich, David||Choe, Yoonsuck

publication date

• January 2011

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

published in

• Proceedings / IEEE International Symposium on Biomedical Imaging: from nano to macro. IEEE International Symposium on Biomedical Imaging  Journal

keywords

• Cropping
• Kesm
• Knife-edge Scanning Microscopy
• Noise Removal
• Serial Sectioning Microscopy

Digital Object Identifier (DOI)

• 10.1109/isbi.2011.5872654

International Standard Book Number (ISBN) 13

• 9781424441280

start page

• 1366

end page

• 1369

URL

• http://dx.doi.org/10.1109/isbi.2011.5872654