Optimization based Tuberculosis Image Segmentation by Ant Colony Heuristic Method

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Shape Factor ◽  
Heuristic Method ◽  
Ground Truth ◽  
Ant Colony ◽  
Second Primary ◽  
Health Crisis ◽  
Acquisition Protocol ◽  
Immunodeficiency Virus ◽  
Segmented Images ◽  
Hybrid Segmentation

Tuberculosis (TB) is a worldwide health crisis and is the second primary infectious disease that causes death next to human immunodeficiency virus. In this work, an attempt has been made to detect the presence of bacilli in sputum smears. The smear images recorded under standard image acquisition protocol are subjected to hybrid Ant Colony Optimization (ACO)-morphological based segmentation procedure. This method is able to retain the shape of bacilli in TB images. The segmented images are validated with ground truth using overlap, distance and probability-based measures. Significant shape-based features such as area, perimeter, compactness, shape factor and tortuosity are extracted from the segmented images. It is observed that this method preserves more edges, detects the presence of bacilli and facilitates direct segmentation with reduced number of redundant searches to generate edges. Thus this hybrid segmentation technique aid in the diagnostic relevance of TB images in identifying the objects present in them.

Optimization based Tuberculosis Image Segmentation by Ant Colony Heuristic Method

2022 ◽  
Vol 13 (1) ◽  
pp. 0-0
Keyword(s):  
Shape Factor ◽  
Heuristic Method ◽  
Ground Truth ◽  
Ant Colony ◽  
Second Primary ◽  
Health Crisis ◽  
Acquisition Protocol ◽  
Immunodeficiency Virus ◽  
Segmented Images ◽  
Hybrid Segmentation

Tuberculosis (TB) is a worldwide health crisis and is the second primary infectious disease that causes death next to human immunodeficiency virus. In this work, an attempt has been made to detect the presence of bacilli in sputum smears. The smear images recorded under standard image acquisition protocol are subjected to hybrid Ant Colony Optimization (ACO)-morphological based segmentation procedure. This method is able to retain the shape of bacilli in TB images. The segmented images are validated with ground truth using overlap, distance and probability-based measures. Significant shape-based features such as area, perimeter, compactness, shape factor and tortuosity are extracted from the segmented images. It is observed that this method preserves more edges, detects the presence of bacilli and facilitates direct segmentation with reduced number of redundant searches to generate edges. Thus this hybrid segmentation technique aid in the diagnostic relevance of TB images in identifying the objects present in them.

A heuristic method to determine traffic bottlenecks based on ant colony: A case study of Iran

2018 ◽  
Vol 6 (4) ◽  
pp. 716-721 ◽  
Author(s):  
Alireza Mahpour ◽  
Amir Mohammadian Amiri ◽  
Milad Deldar ◽  
Mahmoud Saffarzadeh ◽  
Amin Nazifi
Keyword(s):  
Heuristic Method ◽  
Ant Colony

scholarly journals STUDY AND APPLY ACO ALGORITHM IN TIME-COST OPTIMIZATION OF CONSTRUCTION PROJECT

2010 ◽  
Vol 13 (1) ◽  
pp. 17-30
Author(s):  
Luan Hong Pham ◽  
Nhan Thanh Duong
Keyword(s):  
Cost Optimization ◽  
Construction Project ◽  
Heuristic Method ◽  
Ant Colony ◽  
Ant Colony System ◽  
Time Cost ◽  
Project Duration ◽  
Proposed Model ◽  
Feasible Solutions ◽  
Computational Resources

Time-cost optimization problem is one of the most important aspects of construction project management. In order to maximize the return, construction planners would strive to optimize the project duration and cost concurrently. Over the years, many researches have been conducted to model the time-cost relationships; the modeling techniques range from the heuristic method and mathematical approach to genetic algorithm. In this paper, an evolutionary-based optimization algorithm known as ant colony optimization (ACO) is applied to solve the multi-objective time-cost problem. By incorporating with the modified adaptive weight approach (MAWA), the proposed model will find out the most feasible solutions. The concept of the ACO-TCO model is developed by a computer program in the Visual Basic platforms. An example was analyzed to illustrate the capabilities of the proposed model and to compare against GA-based TCO model. The results indicate that ant colony system approach is able to generate better solutions without making the most of computational resources which can provide a useful means to support construction planners and managers in efficiently making better time-cost decisions.

scholarly journals Efficient Unsupervised Classification of Hyperspectral Images Using Voronoi Diagrams and Strong Patterns

Sensors ◽  
2020 ◽  
Vol 20 (19) ◽  
pp. 5684
Author(s):  
Laura Bianca Bilius ◽  
Ştefan Gheorghe Pentiuc
Keyword(s):  
Heuristic Method ◽  
Voronoi Diagrams ◽  
Ground Truth ◽  
Unsupervised Classification ◽  
Hyperspectral Data ◽  
Hyperspectral Images ◽  
Spectral Signature ◽  
Area Of Interest ◽  
Parafac Decomposition

Hyperspectral images (HSIs) are a powerful tool to classify the elements from an area of interest by their spectral signature. In this paper, we propose an efficient method to classify hyperspectral data using Voronoi diagrams and strong patterns in the absence of ground truth. HSI processing consumes a great deal of computing resources because HSIs are represented by large amounts of data. We propose a heuristic method that starts by applying Parafac decomposition for reduction and to construct the abundances matrix. Furthermore, the representative nodes from the abundances map are searched for. A multi-partition of these nodes is found, and based on this, strong patterns are obtained. Then, based on the hierarchical clustering of strong patterns, an optimum partition is found. After strong patterns are labeled, we construct the Voronoi diagram to extend the classification to the entire HSI.

scholarly journals Optimized registration based on an ant colony for markerless augmented reality systems

DYNA ◽  
2020 ◽  
Vol 87 (212) ◽  
pp. 259-266
Author(s):  
Gloria Elena Jaramillo-Rojas ◽  
John William Branch Bedoya
Keyword(s):  
Augmented Reality ◽  
Optimization Problem ◽  
A Priori ◽  
Heuristic Method ◽  
Ant Colony ◽  
Video Sequences ◽  
Average Error ◽  
A Priori Information ◽  
Registration Errors ◽  
Priori Information

Accurate registration in augmented reality systems is essential to guarantee the visual consistency of the augmented environment. Although error in the virtual-real alignment is almost unavoidable, different approaches have been proposed to quantify and reduce such errors. However, many of the existing solutions require a lot of a priori information, or they only focus on camera calibration to guarantee good results in the registration. This article presents a heuristic method that aims to reduce registration errors in markerless augmented reality systems. The proposed solution sees error reduction as a mono-objective optimization problem, which is addressed by means of the Ant Colony Optimization (ACO) algorithm. Experimental results reveal the validity of the proposed method, reaching an average error of 1.49 pixels for long video sequences.

scholarly journals Extraction of Blood Vessels in Fundus Images of Retina through Hybrid Segmentation Approach

Mathematics ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 169 ◽  
Author(s):  
Ramakrishnan Sundaram ◽  
Ravichandran KS ◽  
Premaladha Jayaraman ◽  
Venkatraman B
Keyword(s):  
Blood Vessels ◽  
Ground Truth ◽  
Segmentation Algorithm ◽  
Morphological Operations ◽  
Fundus Images ◽  
Fundus Image ◽  
Segmentation Approach ◽  
Vessel Enhancement ◽  
Morphological Operator ◽  
Hybrid Segmentation

A hybrid segmentation algorithm is proposed is this paper to extract the blood vesselsfrom the fundus image of retina. Fundus camera captures the posterior surface of the eye and thecaptured images are used to diagnose diseases, like Diabetic Retinopathy, Retinoblastoma, Retinalhaemorrhage, etc. Segmentation or extraction of blood vessels is highly required, since the analysisof vessels is crucial for diagnosis, treatment planning, and execution of clinical outcomes in the fieldof ophthalmology. It is derived from the literature review that no unique segmentation algorithm issuitable for images of different eye-related diseases and the degradation of the vessels differ frompatient to patient. If the blood vessels are extracted from the fundus images, it will make thediagnosis process easier. Hence, this paper aims to frame a hybrid segmentation algorithmexclusively for the extraction of blood vessels from the fundus image. The proposed algorithm ishybridized with morphological operations, bottom hat transform, multi-scale vessel enhancement(MSVE) algorithm, and image fusion. After execution of the proposed segmentation algorithm, thearea-based morphological operator is applied to highlight the blood vessels. To validate theproposed algorithm, the results are compared with the ground truth of the High-Resolution Fundus(HRF) images dataset. Upon comparison, it is inferred that the proposed algorithm segments theblood vessels with more accuracy than the existing algorithms.

scholarly journals Opioids and Infectious Diseases: A Converging Public Health Crisis

2019 ◽  
Vol 220 (3) ◽  
pp. 346-349 ◽  
Author(s):  
Tara A Schwetz ◽  
Thomas Calder ◽  
Elana Rosenthal ◽  
Sarah Kattakuzhy ◽  
Anthony S Fauci
Keyword(s):  
Public Health ◽  
Infectious Diseases ◽  
Opioid Use Disorder ◽  
Soft Tissue Infections ◽  
Opioid Use ◽  
Therapeutic Approaches ◽  
Predisposing Factor ◽  
Health Crisis ◽  
Public Health Crisis ◽  
Immunodeficiency Virus

Abstract A converging public health crisis is emerging because the opioid epidemic is fueling a surge in infectious diseases, such as human immunodeficiency virus infection with or without AIDS, the viral hepatitides, infective endocarditis, and skin and soft-tissue infections. An integrated strategy is needed to tailor preventive and therapeutic approaches toward infectious diseases in people who misuse and/or are addicted to opioids and to concurrently address the underlying predisposing factor for the infections—opioid use disorder. This commentary highlights the unique and complementary roles that the infectious diseases and substance use disorder communities can play in addressing this crisis of dual public health concerns.

scholarly journals Inhibition of Human Immunodeficiency Virus Type 1 Infection in SCID-hu Thy/Liv Mice by the G-Quartet-Forming Oligonucleotide, ISIS 5320

1998 ◽  
Vol 42 (8) ◽  
pp. 2113-2115 ◽  
Author(s):  
Cheryl A. Stoddart ◽  
Linda Rabin ◽  
Mara Hincenbergs ◽  
Mary e. Moreno ◽  
Valerie Linquist-Stepps ◽  
...  
Keyword(s):  
Human Immunodeficiency Virus ◽  
Human Immunodeficiency Virus Type ◽  
Virus Type ◽  
Second Primary ◽  
Dependent Manner ◽  
Phosphorothioate Oligonucleotide ◽  
Immunodeficiency Virus ◽  
Hiv 1

ABSTRACT Viral replication was inhibited in a dose-dependent manner after administration of the phosphorothioate oligonucleotide TTGGGGTT (ISIS 5320) to human immunodeficiency virus type 1 (HIV-1)-infected SCID-hu Thy/Liv mice. Potent in vivo antiviral activity was observed against the T-cell-tropic molecular clone NL4-3; the agent was found to have weak activity against one primary HIV-1 isolate, and the agent was inactive against a second primary isolate.

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