Your Search Results

Use this resource - and many more! - in your textbook!

AcademicPub holds over eight million pieces of educational content for you to mix-and-match your way.

Experience the freedom of customizing your course pack with AcademicPub!
Not an educator but still interested in using this content? No problem! Visit our provider's page to contact the publisher and get permission directly.

Automated cropping and artifact removal for knife-edge scanning microscopy

By: Mayerich, D.; Jaerock Kwon; Yoonsuck Choe;

2011 / IEEE / 978-1-4244-4127-3

Description

This item was taken from the IEEE Conference ' Automated cropping and artifact removal for knife-edge scanning microscopy ' Knife Edge Scanning Microscopy (KESM) is a high-throughput imaging technique used to obtain large-scale anatomical information (H1cm3) 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.