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Computer Vision Algorithms for 3D Reconstruction of Microscopic Data A C. Kammerud*, B. Abidi*, and M. Abidi*
 

Summary: Computer Vision Algorithms for 3D Reconstruction of Microscopic Data A
Review
C. Kammerud*, B. Abidi*, and M. Abidi*
*Department of Electrical and Computer Engineering, University of Tennessee, 1508 Middle
Drive, Knoxville, TN 37996
The ability to produce high quality images and 3D reconstructions of objects leads to better defect
detection and also a better understanding of the quantum effects that occur at the nano-level. This
presentation reviews recent advances in the use of raw microscope data for the creation of 3D
models representing real micro and nano-structures. The presentation is divided into five sections,
each section dealing with a different set of algorithms and microscopy technology. The different
technologies and algorithms include morphological reconstruction from atomic force microscopy
(AFM), tomographic reconstruction methods used in transmission electrom microscopy (TEM),
interferometry methods and optical microscopes, stereo imaging with scanning electron microscopy
(SEM), and multifocus methods using confocal and general optical microscopes.
Each microscope has unique advantages and disadvantages that have led to different
reconstruction algorithms. Distortions from the finite tip of an AFM can be reduced using
morphological reconstruction methods, and several different approaches are discussed in our
presentation [1]. Tomography methods, analogous to techniques developed to maturity in the field
of medicine, have since been applied to non-medical fields, one particular area being electron
microscopy [2].

  

Source: Abidi, Mongi A. - Department of Electrical and Computer Engineering, University of Tennessee

 

Collections: Computer Technologies and Information Sciences