scholarly journals An Automated Brain Image Analysis System for Brain Cancer using Shearlets

2022 ◽  
Vol 40 (1) ◽  
pp. 299-312
Author(s):  
R. Muthaiyan ◽  
Dr M. Malleswaran
Author(s):  
D.S. DeMiglio

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.


2020 ◽  
pp. 49-52
Author(s):  
Trine Aabo Andersen

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.


1986 ◽  
Vol 21 (1) ◽  
pp. 130-140 ◽  
Author(s):  
Da-hong Li ◽  
J. J. Ganczarczyk

Abstract The computerized image analysis system has been successfully used for determination and statistical processing of the following geometric characteristics of activated sludge flocs: longest dimension, breadth, equivalent diameter, cross-sectional area, perimeter, elongation, and circularity. These parameters could be effectively and precisely determined by the system applied. In addition, the studied method, as compared to direct microscope observation and photography floc-sizing methods, was found to be more accurate, less time-consuming, and less dependent on the investigators.


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