scholarly journals Development of image analysis techniques as a tool to detect and quantify morphological changes in anaerobic sludge: I. Application to a granulation process

2004 ◽  
Vol 87 (2) ◽  
pp. 184-193 ◽  
Author(s):  
P. Araya-Kroff ◽  
A.L. Amaral ◽  
L. Neves ◽  
E.C. Ferreira ◽  
M.-N. Pons ◽  
...  
Keyword(s):  
Image Analysis ◽  
Morphological Changes ◽  
Anaerobic Sludge ◽  
Granulation Process ◽  
Analysis Techniques ◽  
Image Analysis Techniques

A Review on Automatic Bill of Material Generation and Visual Inspection on PCBs

2019 ◽  
Author(s):  
Mukhil Azhagan M. S ◽  
Dhwani Mehta ◽  
Hangwei Lu ◽  
Sudarshan Agrawal ◽  
Mark Tehranipoor ◽  
...  
Keyword(s):  
Image Analysis ◽  
Visual Inspection ◽  
Automated System ◽  
Imaging Modalities ◽  
Future Research ◽  
Analysis Techniques ◽  
Bill Of Materials ◽  
Pros And Cons ◽  
Index Terms ◽  
Image Analysis Techniques

Abstract Globalization and complexity of the PCB supply chain has made hardware assurance a challenging task. An automated system to extract the Bill of Materials (BoM) can save time and resources during the authentication process, however, there are numerous imaging modalities and image analysis techniques that can be used to create such a system. In this paper we review different imaging modalities and their pros and cons for automatic PCB inspection. In addition, image analysis techniques commonly used for such images are reviewed in a systematic way to provide a direction for future research in this area. Index Terms—Component Detection, PCB, Authentication, Image Analysis, Machine Learning

scholarly journals Quality Evaluation of Potato Tubers Using Neural Image Analysis Method

Agriculture ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 112 ◽  
Author(s):  
Andrzej Przybylak ◽  
Radosław Kozłowski ◽  
Ewa Osuch ◽  
Andrzej Osuch ◽  
Piotr Rybacki ◽  
...  
Keyword(s):  
Image Analysis ◽  
Neural Model ◽  
Assessment Method ◽  
Analysis Method ◽  
Potato Tubers ◽  
Specialized Knowledge ◽  
Analysis Techniques ◽  
Quality Assessment Method ◽  
Sorting Process ◽  
Image Analysis Techniques

This paper describes the research aimed at developing an effective quality assessment method for potato tubers using neural image analysis techniques. Nowadays, the methods used to identify damage and diseases are time-consuming, require specialized knowledge, and often rely on subjective judgment. This study showed the use of the developed neural model as a tool supporting the evaluation of potato tubers during the sorting process in the storage room.

scholarly journals Using PhotoCube as an extensible demonstration platform for advanced image analysis techniques

2012 ◽  
Author(s):  
Grimur Tomasson ◽  
Gisli Kristjan Olafsson ◽  
Hlynur Sigurporsson ◽  
Bjorn Por Jonsson ◽  
Kristjan Runarsson ◽  
...  
Keyword(s):  
Image Analysis ◽  
Analysis Techniques ◽  
Image Analysis Techniques

Considerations for Whole-Slide Analysis of Murine Xenografts Experiments

2021 ◽  
Vol 69 (10) ◽  
pp. 627-631
Author(s):  
Abigail R. Bland ◽  
John C. Ashton
Keyword(s):  
Cell Death ◽  
Image Analysis ◽  
Cell Counting ◽  
Analysis Techniques ◽  
The Core ◽  
Necrotic Region ◽  
Areas Of Interest ◽  
Image Analysis Techniques ◽  
Immunohistochemical Analyses ◽  
Animal Models Of Cancer

Histochemistry of tumor sections is a widely employed technique utilized to examine cell death in preclinical xenograft animal models of cancer. However, this is under the assumption that tumors are homogeneous, leading to practices such as automatic cell counting across the entire section. We have noted that in our experiments the core of the tumor is largely or partially necrotic, and lacks evidence of vascularization (in contrast to the outer areas of the tumor). We note that this can bias and confound immunohistochemical analyses that do not take care to sample areas of interest in a way to take this into account. Design-based stereology with image analysis techniques is an alternative process that could be used to measure the volume of the necrotic region compared to the volume of the whole tumor.

scholarly journals AN AUTOMATED FRAMEWORK FOR CORONARY ANALYSIS FROM CORONARY CINE ANGIOGRAMS USING MACHINE LEARNING AND IMAGE ANALYSIS TECHNIQUES

2021 ◽  
Vol 9 (1) ◽  
pp. 1406-1412
Author(s):  
K. Santhi, A. Rama Mohan Reddy
Keyword(s):  
Machine Learning ◽  
Cardiovascular Disease ◽  
Image Analysis ◽  
Visual Assessment ◽  
Disease Diagnosis ◽  
Healthy Life ◽  
Common Cause ◽  
Analysis Techniques ◽  
Image Modality ◽  
Image Analysis Techniques

Cardiovascular disease (CVD) is one of the critical diseases and the most common cause of morbidity and mortality worldwide. Therefore, early detection and prediction of such a disease is extremely essential for a healthy life. Cardiac imaging plays an important role in the diagnosis of cardiovascular disease but its role has been limited to visual assessment of heart structure and its function. However, with the advanced techniques and tools of big data and machine learning, it become easier to clinician to diagnose the CVD. Stenosis with in the Coronary Arteries (CA) are often determined by using the Coronary Cine Angiogram (CCA). It comes under the invasive image modality. CCA is the effective method to detect and predict the stenosis. In this paper a coronary analysis automation method is proposed in disease diagnosis. The proposed method includes pre-processing, segmentation, identifying vessel path and statistical analysis.

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