Adaptive visual sort and summary of micrographic images of nanoparticles for forensic analysis

Details

• Personal Author:
  Baker N ; Hodas N ; Hoover, Mark D. ; Jurrus E ; Marrinan T
• Description:
  Image classification of nanoparticles from scanning electron microscopes for nuclear forensic analysis is a long, time consuming process. Months of analyst time may initially be required to sift through images in order to categorize morphological characteristics associated with nanoparticle identification. Subsequent assessment of newly acquired images against identified characteristics can be equally time consuming. We present INStINCt, our Intelligent Signature Canvas, as a framework for quickly organizing image data in a web-based canvas framework that partitions images based on features derived from convolutional neural networks. This work is demonstrated using particle images from an aerosol study conducted by Pacific Northwest National Laboratory under the auspices of the U.S. Army Public Health Command to determine depleted uranium aerosol doses and risks. [Description provided by NIOSH]
• Subjects:
  Aerosols Automation Engineering Microbiology Occupational Health Photography Safety Software
• Keywords:
  Analytical Processes Computer Applications Data Processing Imaging Techniques Intervention Microscopic Analysis Microscopy Morphology Nanoparticles Nanotechnology Neural Networks Nuclear Properties Risk Assessment Scanning Electron Microscopy Scanning Techniques Ultrafine Particles Uranium Visual Images Warning Systems

  More +
• ISBN:
  9781509007707
• Publisher:
  Institute of Electrical and Electronics Engineers
• Document Type:
  Text
• Genre:
  Proceedings
• Place as Subject:
  Colorado ; OSHA Region 10 ; OSHA Region 3 ; OSHA Region 8 ; Washington ; West Virginia
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Division:
  RHD - Respiratory Health Division
• Topic:
  Workplace Safety & Health
• Location:
  North America
• NIOSHTIC Number:
  nn:20048889
• Citation:
  2016 IEEE Symposium on Technologies for Homeland Security, HST 2016, May 10-11, 2016, Waltham, Massachusetts. New York: Institute of Electrical and Electronics Engineers, 2016 Sep; :7568959
• Contact Point Address:
  Elizabeth Jurrus, Pacific Northwest National Laboratory, Richland, WA 99352
• Email:
  liz@pnnl.gov
• CAS Registry Number:
  Uranium (CAS RN 7440-61-1)
• Federal Fiscal Year:
  2016
• NORA Priority Area:
  Manufacturing
• Peer Reviewed:
  False
• Source Full Name:
  2016 IEEE Symposium on Technologies for Homeland Security, HST 2016, May 10-11, 2016, Waltham, Massachusetts
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:bf11e2f34466e0678e6c934e1e9bdf521bce974be0fcf0fc5044050193a6e52136e8ae19f83f15abda849dba2a23d67eee8bd923e39e70a55fde4a53b7461b7f
• Download URL:
  https://stacks.cdc.gov/view/cdc/203509/cdc_203509_DS1.pdf
• File Type:
  [PDF - 950.60 KB ]