Particle volume correction using shape features

Author(s):  
Ra'eesah Mangera ◽  
Garry Morrison ◽  
Anthon Voigt
2020 ◽  
Vol 140 (12) ◽  
pp. 1367-1368
Author(s):  
Daisuke Saito ◽  
Hiroharu Kawanaka ◽  
V. B. Surya Prasath ◽  
Bruce J. Aronow
Keyword(s):  

1970 ◽  
Vol 5 (1) ◽  
pp. 1-8
Author(s):  
Gordon G.C. Robinson ◽  
Dennis J. Brown

Abstract A model “B” Coulter Counter with “J” plotter was used to determine the total volume of particulate matter and autotrophic and heterotrophic increments in particle volume in a small eutrophic lake, south of Lake Manitoba. Such increments were converted to more meaningful carbon values.


2006 ◽  
Vol 6 (1) ◽  
pp. 1-9
Author(s):  
V. Miska ◽  
J.H.J.M. van der Graaf ◽  
J. de Koning

Nowadays filtration processes are still monitored with conventional analyses like turbidity measurements and, in case of flocculation–filtration, with phosphorus analyses. Turbidity measurements have the disadvantage that breakthrough of small flocs cannot be displayed, because of the blindness regarding changes in the mass distributions. Additional particle volume distributions calculated from particle size distributions (PSDs) would provide a better assessment of filtration performance. Lab-scale experiments have been executed on a flocculation–filtration column fed with effluent from WWTP Beverwijk in The Netherlands. Besides particle counting at various sampling points, the effect of sample dilution on the accuracy of PSD measurements has been reflected. It was found that the dilution has a minor effect on PSD of low turbidity samples such as process filtrate. The correlation between total particle counts, total particle volume (TPV) and total particle surface is not high but is at least better for diluted measurements of particles in the range 2–10 μm. Furthermore, possible relations between floc-bound phosphorus and TPV removal had been investigated. A good correlation coefficient is found for TPV removal versus floc-bound phosphorus removal for the experiments with polyaluminiumchloride and the experiments with single denitrifying and blank filtration.


Author(s):  
Eaton E. Lattman ◽  
Thomas D. Grant ◽  
Edward H. Snell

In this chapter we note that solution scattering data can be divided into four regions. At zero scattering angle, the scattering provides information on molecular weight of the particle in solution. Beyond that, the scattering is influenced by the radius of gyration. As the scattering angle increases, the scattering is influenced by the particle shape, and finally by the interface with the particle and the solution. There are a number of important invariants that can be calculated directly from the data including molecular mass, radius of gyration, Porod invariant, particle volume, maximum particle dimension, particle surface area, correlation length, and volume of correlation. The meaning of these is described in turn along with their mathematical derivations.


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Mahsa Bank Tavakoli ◽  
Mahdi Orooji ◽  
Mehdi Teimouri ◽  
Ramita Shahabifar

Abstract Objective The most common histopathologic malignant and benign nodules are Adenocarcinoma and Granuloma, respectively, which have different standards of care. In this paper, we propose an automatic framework for the diagnosis of the Adenocarcinomas and the Granulomas in the CT scans of the chest from a private dataset. We use the radiomic features of the nodules and the attached vessel tortuosity for the diagnosis. The private dataset includes 22 CTs for each nodule type, i.e., adenocarcinoma and granuloma. The dataset contains the CTs of the non-smoker patients who are between 30 and 60 years old. To automatically segment the delineated nodule area and the attached vessels area, we apply a morphological-based approach. For distinguishing the malignancy of the segmented nodule, two texture features of the nodule, the curvature Mean and the number of the attached vessels are extracted. Results We compare our framework with the state-of-the-art feature selection methods for differentiating Adenocarcinomas from Granulomas. These methods employ only the shape features of the nodule, the texture features of the nodule, or the torsion features of the attached vessels along with the radiomic features of the nodule. The accuracy of our framework is improved by considering the four selected features.


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