scholarly journals A simple method of image analysis to estimate CAM vascularization by APERIO ImageScope software

2015 ◽  
Vol 59 (4-5-6) ◽  
pp. 217-219 ◽  
Author(s):  
Christian Marinaccio ◽  
Domenico Ribatti
Keyword(s):  
Image Analysis ◽  
Simple Method

Measuring Coral Skeletal Architecture Using Image Analysis v1

2021 ◽  
Author(s):  
Rowan Mclachlan ◽  
Ashruti Patel ◽  
Andrea G Grottoli
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Image Analysis ◽  
Scleractinian Coral ◽  
Coral Species ◽  
Energy Materials ◽  
Simple Method ◽  
Coral Skeletons ◽  
Skeletal Structures ◽  
Scanning Electron

Coral morphology is influenced by genetics, the environment, or the interaction of both, and thus is highly variable. This protocol outlines a non-destructive and relatively simple method for measuring Scleractinian coral sub-corallite skeletal structures (such as the septa length, theca thickness, and corallite diameter, etc.) using digital images produced as a result of digital microscopy or from scanning electron microscopy. This method uses X and Y coordinates of points placed onto photomicrographs to automatically calculate the length and/or diameter of a variety of sub-corallite skeletal structures in the Scleractinian coral Porites lobata. However, this protocol can be easily adapted for other coral species - the only difference may be the specific skeletal structures that are measured (for example, not all coral species have a pronounced columella or pali, or even circular corallites). This protocol is adapted from the methods described in Forsman et al. (2015) & Tisthammer et al. (2018). There are 4 steps to this protocol: 1) Removal of Organic Tissue from Coral Skeletons 2) Imaging of Coral Skeletons 3) Photomicrograph Image Analysis 4) Calculation of Corallite Microstructure Size This protocol was written by Dr. Rowan McLachlan and was reviewed by Ashruti Patel and Dr. Andréa Grottoli. Acknowledgments Leica DMS 1000 and Scanning Electron Microscopy photomicrographs used in this protocol were acquired at the Subsurface Energy Materials Characterization and Analysis Laboratory (SEMCAL), School of Earth Sciences at The Ohio State University, Ohio, USA. I would like to thank Dr. Julie Sheets, Dr. Sue Welch, and Dr. David Cole for training me on the use of these instruments.

scholarly journals Pore system changes of damaged Brazilian oxisols and nitosols induced by wet-dry cycles as seen in 2-D micromorphologic image analysis

2009 ◽  
Vol 81 (1) ◽  
pp. 151-161 ◽  
Author(s):  
Luiz F. Pires ◽  
Klaus Reichardt ◽  
Miguel Cooper ◽  
Fabio A.M. Cássaro ◽  
Nivea M.P. Dias ◽  
...  
Keyword(s):  
Image Analysis ◽  
Size Distribution ◽  
Soil Structure ◽  
Tropical Soils ◽  
Transport Processes ◽  
Structure Characterization ◽  
Control Treatment ◽  
Simple Method ◽  
Wetting And Drying ◽  
Essential Information

Soil pore structure characterization using 2-D image analysis constitutes a simple method to obtain essential information related to soil porosity and pore size distribution (PSD). Such information is important to infer on soil quality, which is related to soil structure and transport processes inside the soil. Most of the time soils are submitted to wetting and drying cycles (W-D), which can cause important changes in soils with damaged structures. This report uses 2-D image analysis to evaluate possible modifications induced by W-D cycles on the structure of damaged soil samples. Samples of three tropical soils (Geric Ferralsol, GF; Eutric Nitosol, EN; and Rhodic Ferralsol, RF) were submitted to three treatments: 0WD, the control treatment in which samples were not submitted to any W-D cycle; 3WD and 9WD with samples submitted to 3 and 9 consecutive W-D cycles, respectively. It was observed that W-D cycles produced significant changes in large irregular pores of the GF and RF soils, and in rounded pores of the EN soil. Nevertheless, important changes in smaller pores (35, 75, and 150 µm) were also observed for all soils. As an overall consideration, it can be said that the use of image analysis helped to explain important changes in soil pore systems (shape, number, and size distribution) as consequence of W-D cycles.

scholarly journals A Very Simple Method for Quickly Making Large Numbers of Measurements on Micrographs

2009 ◽  
Vol 17 (3) ◽  
pp. 50-53
Author(s):  
Ron Anderson
Keyword(s):  
Thin Film ◽  
Grain Size ◽  
Image Analysis ◽  
Integrated Circuit ◽  
Ceramic Substrate ◽  
Raw Material ◽  
Material Particle ◽  
Simple Method ◽  
Plan View ◽  
Large Computer

It has been in the back of my mind to write this up for MT since I retired from a certain large computer company. Inasmuch as Paul's article above is a perfect lead-in, there is no time like the present. Our lab supported a semiconductor integrated circuit and a ceramic substrate manufacturing facility. We were continually required to measure circuit line widths on plan-view specimens and layer thicknesses on cross-section specimens for both semiconductor and ceramic substrate specimens and we were often asked to determine thin film grain size and ceramic raw material particle size data. A large number of measurements were required for each specimen to guarantee statistically sound data. We had image analysis software available that we used whenever we could, but often found that measuring things on a system using grey-level image analysis as input simply did not work. This is especially true for thin film grain size determination when using diffraction contrast TEM images for input.

Detection of Blobs Using Variable Windows

1995 ◽  
Vol 7 (5) ◽  
pp. 404-409
Author(s):  
Machi Saitoh ◽  
◽  
Hiroshi Katsulai ◽  
Keyword(s):  
Image Analysis ◽  
Simple Method ◽  
Blob Detection ◽  
Compact Region ◽  
Wide Range ◽  
Variable Window ◽  
Size Variable

A blob is a compact region in the image which is surrouded by a smoothly curved closed edge and, at the same time, is lighter or darker than the background. Many objects which are found in an image can be viewed as blobs. It is very important to quickly detect in an image the location of blobs for a wide range of applications of image analysis. In this paper, we propose a noniterative simple method of blob detection which is applicable to various forms of blobs by scanning an image with a size variable window, and does not require so much memory and time for computations because of its simplicity, and demonstrate its effectiveness through experiments.

Evolution of Multivariate Image Analysis in QSAR

2015 ◽  
pp. 84-122
Author(s):  
Matheus P. Freitas ◽  
Mariene H. Duarte
Keyword(s):  
Image Analysis ◽  
Biological Activities ◽  
Quantitative Structure Activity Relationship ◽  
Simple Method ◽  
Multivariate Image Analysis ◽  
Chemical Structures ◽  
Qsar Models ◽  
Chemical Descriptors ◽  
Multivariate Image

Multivariate Image Analysis applied in Quantitative Structure-Activity Relationship (MIA-QSAR) is a simple method to achieve, at least in a variety of examples, QSAR models with predictive abilities comparable to those of sophisticated tridimensional methodologies. MIA-QSAR is based on the correlation between properties (e.g. biological activities) and chemical descriptors, which are pixels of images representing chemical structures in a congeneric series of molecules. The MIA-QSAR approach has been improved since its creation, in 2005, both in terms of data analysis and development of more descriptive information. This chapter reports the MIA-QSAR method, including its augmented version, named aug-MIA-QSAR because of the introduction of new dimensions to better encode atomic properties. In addition, the application to a case study illustrates the main practical differences between traditional and augmented MIA-QSAR. The use of a neglected disease as example represents a challenge in QSAR, which is particularly focused on diseases with higher economical appearance.

Evaluation of a simple method for measuring the cellular DNA content of mouse oocytes and embryos, human fibroblasts and parthenogenetically activated human oocytes using a computerised image analysis system(Seescan)

Zygote ◽  
1995 ◽  
Vol 3 (1) ◽  
pp. 85-94 ◽  
Author(s):  
Alison S. Taylor ◽  
Peter R. Braude
Keyword(s):  
Image Analysis ◽  
Dna Content ◽  
Lung Fibroblasts ◽  
Short Exposure ◽  
Image Analysis System ◽  
Simple Method ◽  
Cytoplasmic Staining ◽  
Human Oocytes ◽  
Computerised Image Analysis ◽  
Analysis System

SummaryWe report the use of a simple, reproducible, photocytometric method for measuring nuclear DNA content of DAPI-stained cells, using a computerised image analysis system: Seescan. As this technique is non-destructive and uses very short exposure to ultraviolet light, it can be used for either fixed or vital material. After correcting for any background cytoplasmic staining, the intensity of nuclear stain was measured by the Seescan and compared with that of control cells of known ploidy. Fixed material was found to stain more intensely than live material initially, but demonstrated a rapid loss of nuclear intensity over the first 90 min following removal from DAPI, after which the level plateaued. In contrast, live cells showed no change in nuclear intensity with time. The system was validated by measuring the DNA content of carefully timed mouse blastomeres, human fetal lung fibroblasts and parthenogenetically activated human oocytes. The results obtained were appropriate for the developmental stage or phenotypic appearance of each of the cell types measured.

Sign in / Sign up

Export Citation Format

Share Document