SiteResearch on Spatiotemporal Behavior Changes of Pedestrians Based on Intelligent Image Analysis Data

2020 ◽  
Author(s):  
Li Liang ◽  
Wang Xin
Keyword(s):  
Image Analysis ◽  
Analysis Data ◽  
Behavior Changes ◽  
Spatiotemporal Behavior

scholarly journals Image data of crumb structure of bread from flour of czech spring wheat cultivars

2011 ◽  
Vol 22 (No. 4) ◽  
pp. 133-142 ◽  
Author(s):  
I. Švec ◽  
M. Hrušková
Keyword(s):  
Image Analysis ◽  
Image Data ◽  
Analysis Data ◽  
Wheat Cultivars ◽  
Rheological Measurements ◽  
Class A ◽  
Bread Volume ◽  
Class B ◽  
Crumb Structure

Abstract: Baking quality of flour from six wheat cultivars (harvest 2002 and 2003), belonging to the quality classes A and B, was evaluated using the fermented dough test. Analytical traits of kernel and flour showed differences between the classes which were confirmed by the baking test with the full-bread-formula according to Czech method. In addition to standard methods of the bread parameters description (specific bread volume and bread shape measurements) rheological measurements of penetrometer and image analysis were used in effort to differentiate wheat samples into the quality classes. The results of the baking test proved significant differences in specific bread volumes – the highest volume in class A was obtained with the cultivar Vinjet and in class B with SG-S1098 – approx. 410 and 420 ml/100 g. Although significant correlations among image analysis data and specific bread volume having been proved, any image analysis parameter did not distinguish the quality classes. Only the penetronetric measurements made with bread crumb were suitable for such purpose (r = 0.9083; for  = 0.01). Among image analysis data the total cell area of the crumb had the strongest correlation with specific bread volume (r = 0.7840; for α = 0.01).    

scholarly journals Quantitative analysis of subcellular distributions with an open-source, object-based tool

Biology Open ◽  
2020 ◽  
Vol 9 (10) ◽  
pp. bio055228 ◽  
Author(s):  
Pearl V. Ryder ◽  
Dorothy A. Lerit
Keyword(s):  
Image Analysis ◽  
Open Source ◽  
Three Dimensional ◽  
Analysis Data ◽  
Form And Function ◽  
Object Based Image Analysis ◽  
Object Based ◽  
And Function ◽  
Microscopy Images ◽  
Complete Process

ABSTRACTThe subcellular localization of objects, such as organelles, proteins, or other molecules, instructs cellular form and function. Understanding the underlying spatial relationships between objects through colocalization analysis of microscopy images is a fundamental approach used to inform biological mechanisms. We generated an automated and customizable computational tool, the SubcellularDistribution pipeline, to facilitate object-based image analysis from three-dimensional (3D) fluorescence microcopy images. To test the utility of the SubcellularDistribution pipeline, we examined the subcellular distribution of mRNA relative to centrosomes within syncytial Drosophila embryos. Centrosomes are microtubule-organizing centers, and RNA enrichments at centrosomes are of emerging importance. Our open-source and freely available software detected RNA distributions comparably to commercially available image analysis software. The SubcellularDistribution pipeline is designed to guide the user through the complete process of preparing image analysis data for publication, from image segmentation and data processing to visualization.This article has an associated First Person interview with the first author of the paper.

A methodology for comprehensive breast cancer Ki67 labeling index with intra-tumor heterogeneity appraisal based on hexagonal tiling of digital image analysis data

2015 ◽  
Vol 467 (6) ◽  
pp. 711-722 ◽  
Author(s):  
Benoit Plancoulaine ◽  
Aida Laurinaviciene ◽  
Paulette Herlin ◽  
Justinas Besusparis ◽  
Raimundas Meskauskas ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Image Analysis ◽  
Digital Image ◽  
Tumor Heterogeneity ◽  
Digital Image Analysis ◽  
Analysis Data ◽  
Labeling Index ◽  
Ki67 Labeling Index ◽  
Hexagonal Tiling

scholarly journals Pathology Quality Control for Multiplex Immunofluorescence and Image Analysis Assessment in Longitudinal Studies

2021 ◽  
Vol 8 ◽  
Author(s):  
Rossana Lazcano ◽  
Frank Rojas ◽  
Caddie Laberiano ◽  
Sharia Hernandez ◽  
Edwin Roger Parra
Keyword(s):  
Quality Control ◽  
Image Analysis ◽  
Inflammatory Cells ◽  
Analysis Data ◽  
Malignant Cells ◽  
Core Needle ◽  
Formalin Fixed Paraffin ◽  
Formalin Fixed Paraffin Embedded ◽  
Organ Site ◽  
Immune Profiling

Immune profiling of formalin-fixed, paraffin-embedded tissues using multiplex immunofluorescence (mIF) staining and image analysis methodology allows for the study of several biomarkers on a single slide. The pathology quality control (PQC) for tumor tissue immune profiling using digital image analysis of core needle biopsies is an important step in any laboratory to avoid wasting time and materials. Although there are currently no established inclusion and exclusion criteria for samples used in this type of assay, a PQC is necessary to achieve accurate and reproducible data. We retrospectively reviewed PQC data from hematoxylin and eosin (H&E) slides and from mIF image analysis samples obtained during 2019. We reviewed a total of 931 reports from core needle biopsy samples; 123 (13.21%) were excluded during the mIF PQC. The most common causes of exclusion were the absence of malignant cells or fewer than 100 malignant cells in the entire section (n = 42, 34.15%), tissue size smaller than 4 × 1 mm (n = 16, 13.01%), fibrotic tissue without inflammatory cells (n = 12, 9.76%), and necrotic tissue (n = 11, 8.94%). Baseline excluded samples had more fibrosis (90 vs 10%) and less necrosis (5 vs 90%) compared with post-treatment excluded samples. The most common excluded organ site of the biopsy was the liver (n = 19, 15.45%), followed by soft tissue (n = 17, 13.82%) and the abdominal region (n = 15, 12.20%). We showed that the PQC is an important step for image analysis and that the absence of malignant cells is the most limiting sample characteristic for mIF image analysis. We also discuss other challenges that pathologists need to consider to report reliable and reproducible image analysis data.

The Relation Among Porosity, Permeability, and Specific Surface of Chalk From the Gorm Field, Danish North Sea

1998 ◽  
Vol 1 (03) ◽  
pp. 245-251 ◽  
Author(s):  
Jeanette Mortensen ◽  
Finn Engstrom ◽  
Ida Lind
Keyword(s):  
Image Analysis ◽  
Specific Surface ◽  
North Sea ◽  
Laboratory Data ◽  
Total Porosity ◽  
Analysis Data ◽  
Air Permeability ◽  
Empirical Constant ◽  
Core Data ◽  
The Relationship

Summary The origin of the difference in the relationship between permeability and porosity for Danian and Maastrichtian chalk from the Gorm field offshore Denmark has been investigated. The investigation was based on 300 sets of core data (He-expansion porosity and air permeability) from Well Gorm N-22X. On 24 of the core plugs, the specific surface was determined by BET and, on 14 of these samples, image analysis was made. The data were rationalized by the use of the Kozeny equation and it was found that each geologic unit had a characteristic relationship among porosity, permeability, and specific surface. Furthermore, it was found that the nature of porosity (intrafossil, intergranular, etc.) had no significant influence on the air permeability, so that the permeability of the chalk can be calculated from total porosity and specific surface. Kozeny's empirical constant, c, was determined analytically from a simple porosity model and Poiseuille's law. Introduction Experience has illustrated that to a first approximation, porosity and the logarithm of permeability are well correlated in the North Sea chalk. However, different stratigraphical units have distinctly different porosity-permeability relations. For a given porosity, the permeability of chalk of Maastrichtian age is, e.g., on average, larger than the permeability of chalk of Danian age. The cause for the differences in porosity-permeability relationships between the chalk units is not well documented in literature, but the size of pores and particles, and the surface characteristics of the particles are likely controlling factors. This study was undertaken to obtain a simple model for the relationship among porosity, permeability, and specific surface for reservoir chalk irrespective of stratigraphic unit, and to evaluate the usefulness of image-analysis data relative to laboratory data. To meet this purpose, we have studied core data from a chalk field (the Gorm field) applying the Kozeny equation.

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