Wavelets and fuzzy relational classifiers: A novel diffusion-weighted image analysis system for pediatric metabolic brain diseases

2011 ◽  
Vol 103 (2) ◽  
pp. 74-86 ◽  
Author(s):  
S. Zarei Mahmoodabadi ◽  
J. Alirezaie ◽  
P. Babyn ◽  
A. Kassner ◽  
E. Widjaja
Keyword(s):  
Image Analysis ◽  
Brain Diseases ◽  
Image Analysis System ◽  
Diffusion Weighted Image ◽  
Weighted Image ◽  
Metabolic Brain Diseases ◽  
Diffusion Weighted ◽  
Analysis System

scholarly journals Optimized bias and signal inference in diffusion‐weighted image analysis (OBSIDIAN)

2021 ◽  
Author(s):  
Stefan Kuczera ◽  
Mohammad Alipoor ◽  
Fredrik Langkilde ◽  
Stephan E. Maier
Keyword(s):  
Image Analysis ◽  
Diffusion Weighted Image ◽  
Weighted Image ◽  
Diffusion Weighted

Diffusion Orientation Histograms (DOH) for Diffusion Weighted Image Analysis

2018 ◽  
pp. 91-99
Author(s):  
Laurent Chauvin ◽  
Kuldeep Kumar ◽  
Christian Desrosiers ◽  
Jacques De Guise ◽  
Matthew Toews
Keyword(s):  
Image Analysis ◽  
Diffusion Weighted Image ◽  
Weighted Image ◽  
Diffusion Weighted

Chemical Classification and Particle Sizing of Foundry Sands

1985 ◽  
Vol 43 ◽  
pp. 388-389
Author(s):  
D.S. DeMiglio
Keyword(s):  
Image Analysis ◽  
Energy Dispersive Spectrometer ◽  
Image Analysis System ◽  
Representative Sampling ◽  
Foundry Sands ◽  
Large Atomic Number ◽  
Backscattered Electron ◽  
Sand Particles ◽  
Analysis System ◽  
Reclamation System

Much progress has been made in recent years towards the development of closed-loop foundry sand reclamation systems. However, virtually all work to date has determined the effectiveness of these systems to remove surface clay and metal oxide scales by a qualitative inspection of a representative sampling of sand particles. In this investigation, particles from a series of foundry sands were sized and chemically classified by a Lemont image analysis system (which was interfaced with an SEM and an X-ray energy dispersive spectrometer) in order to statistically document the effectiveness of a reclamation system developed by The Pangborn Company - a subsidiary of SOHIO.The following samples were submitted: unreclaimed sand; calcined sand; calcined & mechanically scrubbed sand and unused sand. Prior to analysis, each sample was sprinkled onto a carbon mount and coated with an evaporated film of carbon. A backscattered electron photomicrograph of a field of scale-covered particles is shown in Figure 1. Due to a large atomic number difference between sand particles and the carbon mount, the backscattered electron signal was used for image analysis since it had a uniform contrast over the shape of each particle.

SIGN IN Welcome!Log into your account your username your password Forgot your password Privacy policy PASSWORD RECOVERY Recover your password your email Struktol Home New fast measuring method for process optimization of sucrose crystallization New fast measuring method for process optimization of sucrose crystallization

2020 ◽  
pp. 49-52
Author(s):  
Trine Aabo Andersen
Keyword(s):  
Image Analysis ◽  
Process Optimization ◽  
Crystal Size ◽  
Measuring Method ◽  
Sieve Analysis ◽  
Image Analysis System ◽  
Line System ◽  
Non Invasive ◽  
Analysis System ◽  
User Friendly

A new fast measuring method for process optimization of sucrose crystallization using image analysis based on high quality images and algorithms is introduced. With the mobile, non-invasive at-line system all steps of the sucrose crystallization can be measured to determine the crystal size distribution. The image analysis system is easy to operate and is as well an efficient laboratory solution with user-friendly and customized software. In comparison to sieve analysis, image analyses performed with the ParticleTech Solution have been proven to be reliable.

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