scholarly journals Quantifying Fish Swimming Behavior in Response to Acute Exposure of Aqueous Copper Using Computer Assisted Video and Digital Image Analysis

10.3791/53477 ◽  
2016 ◽  
Author(s):  
Robin D. Calfee ◽  
Holly J. Puglis ◽  
Edward E. Little ◽  
William G. Brumbaugh ◽  
Christopher A. Mebane
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Swimming Behavior ◽  
Acute Exposure ◽  
Computer Assisted ◽  
Fish Swimming

scholarly journals Nondestructive Measurement of Vegetative Cover Using Digital Image Analysis

HortScience ◽  
2004 ◽  
Vol 39 (1) ◽  
pp. 55-59 ◽  
Author(s):  
Mercy A. Olmstead ◽  
Robert Wample ◽  
Stephanie Greene ◽  
Julie Tarara
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Cover Crops ◽  
Cover Crop ◽  
Digital Image Analysis ◽  
Ground Surface ◽  
Visual Assessment ◽  
Computer Assisted ◽  
Percent Cover ◽  
Vegetative Cover

Traditionally, vegetative cover has been subjectively assessed by visual assessment. However, visual assessment is thought to overestimate percent vegetative cover. Thus, a repeatable method to objectively quantify percent cover is desirable. In two vineyards near Prosser, Wash., the percentage of ground surface covered by up to 15 different cover crops was assessed both visually and by computer-assisted digital image analysis. Quadrats in the cover crop were photographed digitally and the images analyzed with commercially available software. Areas of green vegetation in each image were identified and measured. Weeds in some images were differentiated from the cover crop by user-defined thresholds. Subjective visual estimates of percent vegetative cover were generally higher than those digitally estimated. Values for the visual estimates ranged from 5% to 70% in 1998 (mean = 52.4%) and 7.5% to 55% in 1999 (mean = 30.7%), compared to digital readings ranging from 0.5% to 24% (mean = 11.1%) and 10.3% to 36.6% cover (mean = 20.1%), respectively. The visual assessments had lower coefficients of variability in 1998 (cv 28.1) than the digital image analysis (cv 52.3), but in 1999, the values for the two techniques were similar (cv 41.2 vs. cv 45.7). Despite initial variations between the two methods, the accuracy of digital image analysis for measuring percentage vegetative cover is superior.

scholarly journals The Histochemical Alterations of Mucin in Colorectal Carcinoma Quantified by Two Efficient Algorithms of Digital Image Analysis

2019 ◽  
Vol 20 (18) ◽  
pp. 4580 ◽  
Author(s):  
Kasprzak ◽  
Seraszek-Jaros ◽  
Jagielska ◽  
Helak-Łapaj ◽  
Siodła ◽  
...  
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Periodic Acid ◽  
Daily Practice ◽  
Blue Staining ◽  
Alcian Blue Staining ◽  
Computer Assisted ◽  
Periodic Acid Schiff ◽  
Tissue Samples

The practical use of knowledge on the diagnostic-prognostic role of polysaccharide components of mucins in colorectal cancer (CRC) has been difficult, due to the number of histochemical (HC) reaction types, as well as lack of standard methods of computer-assisted analysis of tissue expression of these molecules. Using two algorithms of digital image analysis (by application of Image-Pro Premier and our originally designed program Filter HSV), we evaluated the expression of polysaccharides in tissue samples of CRC patients (n = 33), and fragments of normal colorectal tissue from the same patients (control) using periodic acid Schiff reaction (PAS) (neutral mucins) and alcian blue staining (AB) (acidic mucins). Our results indicate lower expression of the PAS+ and AB+ mucins in CRC, as compared to the control samples. The higher expression of PAS+ polysaccharides was detected in flat tumors than in protruded CRC, while higher AB+ mucins expression was a feature of mucinous CRC subtypes. Positive correlation between mutual PAS+ and AB+ expression, as well as correlations with glucose concentration (PAS+ mucins), and hemoglobin level (AB+ mucins) were observed exclusively in unchanged colorectal samples (control). Both algorithms of digital image analysis (smart segmentation and Filter HSV) work properly and can be used interchangeably in daily practice of pathologists, as useful tools of quantitative evaluation of HC reaction in both normal and cancerous tissues.

Computer-assisted digital image analysis and evaluation of brood development in honey bee combs

2012 ◽  
Vol 51 (1) ◽  
pp. 63-73 ◽  
Author(s):  
Lukas Jeker ◽  
Lukas Schmid ◽  
Thomas Meschberger ◽  
Marco Candolfi ◽  
Stefan Pudenz ◽  
...  
Keyword(s):  
Image Analysis ◽  
Honey Bee ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Computer Assisted ◽  
Analysis And Evaluation ◽  
Brood Development

Computer-Assisted Digital Image Analysis to Quantify the Mass and Purity of Isolated Human Islets Before Transplantation

2008 ◽  
Vol 86 (11) ◽  
pp. 1603-1609 ◽  
Author(s):  
Nadja Niclauss ◽  
Antonino Sgroi ◽  
Philippe Morel ◽  
Reto Baertschiger ◽  
Mathieu Armanet ◽  
...  
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis ◽  
Human Islets ◽  
Computer Assisted

Digital Image Analysis of the Larynx

2000 ◽  
Vol 10 (2) ◽  
pp. 7-9
Author(s):  
Yaser Natour ◽  
Christine Sapienza ◽  
Mark Schmalz ◽  
Savita Collins
Keyword(s):  
Image Analysis ◽  
Digital Image ◽  
Digital Image Analysis
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