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Extraction and Segmentation of Sputum Cells for Lung Cancer Early Diagnosis
2013
Algorithms
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The present work deals with the attempt to design computer-aided detection or diagnosis (CAD) systems for early detection of lung cancer based on the analysis of sputum color images. ...
We present here a framework for the extraction and segmentation of sputum cells in sputum images using, respectively, a threshold classifier, a Bayesian classification and mean shift segmentation. ...
Following up the work of [15] , the authors in [16] came up with an automatic computer aided diagnosis (CAD) system for early detection of lung cancer based on the analysis of pathological sputum color ...
doi:10.3390/a6030512
fatcat:hln5w5evhrbwpkihnmj2l7cy5y
Computer Aided Diagnosis System for Early Lung Cancer Detection
2015
Algorithms
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This was the motivation behind the design and the development of a new computer aided diagnosis (CAD) system for early detection of lung cancer based on the analysis of sputum color images. ...
Lung cancer continues to rank as the leading cause of cancer deaths worldwide. One of the most promising techniques for early detection of cancerous cells relies on sputum cell analysis. ...
Acknowledgments We would like to thank Mohamad Al-Homssi the pathologist in the Medical College at University of Sharjah, UAE, for his kind collaboration. ...
doi:10.3390/a8041088
fatcat:ksmfx57isrdwzntb62fdbamlbq
Computer aided diagnosis system for early lung cancer detection
2015
2015 International Conference on Systems, Signals and Image Processing (IWSSIP)
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This was the motivation behind the design and the development of a new computer aided diagnosis (CAD) system for early detection of lung cancer based on the analysis of sputum color images. ...
Lung cancer continues to rank as the leading cause of cancer deaths worldwide. One of the most promising techniques for early detection of cancerous cells relies on sputum cell analysis. ...
Acknowledgments We would like to thank Mohamad Al-Homssi the pathologist in the Medical College at University of Sharjah, UAE, for his kind collaboration. ...
doi:10.1109/iwssip.2015.7313923
dblp:conf/iwssip/TaherWA15
fatcat:w2b6nu2yivf3zif54zebs76n3m
Lung Cancer Detection by Using Artificial Neural Network and Fuzzy Clustering Methods
2012
American Journal of Biomedical Engineering
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This paper presents two segmentation methods, Hopfield Neural Network (HNN) and a Fuzzy C-Mean (FCM) clustering algorithm, for segmenting sputum color images to detect the lung cancer in its early stages ...
The segmentation results will be used as a base for a Computer Aided Diagnosis (CAD) system for early detection of lung cancer which will improve the chances of survival for the patient. ...
In the future, we plan to consider a Bayesian decision theory for the detection of the lung cancer cells, followed by developing a model based on the idea of mean shift algorithm which combined the idea ...
doi:10.5923/j.ajbe.20120203.08
fatcat:fayxx6nsqncjphbxtegsypp32y
Lung cancer detection by using artificial neural network and fuzzy clustering methods
2011
2011 IEEE GCC Conference and Exhibition (GCC)
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This paper presents two segmentation methods, Hopfield Neural Network (HNN) and a Fuzzy C-Mean (FCM) clustering algorithm, for segmenting sputum color images to detect the lung cancer in its early stages ...
The segmentation results will be used as a base for a Computer Aided Diagnosis (CAD) system for early detection of lung cancer which will improve the chances of survival for the patient. ...
In the future, we plan to consider a Bayesian decision theory for the detection of the lung cancer cells, followed by developing a model based on the idea of mean shift algorithm which combined the idea ...
doi:10.1109/ieeegcc.2011.5752535
fatcat:edlofb6ijrhlnhk7jkkr2xxz2m
Cytology Image Analysis Techniques Towards Automation: Systematically Revisited
[article]
2020
arXiv
pre-print
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Cytology is the branch of pathology which deals with the microscopic examination of cells for diagnosis of carcinoma or inflammatory conditions. ...
Automation in cytology started in the early 1950s with the aim to reduce manual efforts in diagnosis of cancer. ...
Authors are also thankful to the members of "Theism Medical Diagnostics Centre", Kolkata, India and "Saroj Gupta Cancer Centre & Research Institute", Thakurpukur, Kolkata, India. ...
arXiv:2003.07529v1
fatcat:eossjujftzflbfnfhbsw55tlta
99-december-2995 survey paper.pdf
2022
figshare.com
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This paper analyzes various segmentation techniques available for medical images and lung chest X-Ray images ...
Based on proper accuracy and sensitivity of lung segmentation, lung cancer detection and diagnosis results in early treatment for patients and help to increase the life time of cancerous patients. ...
of CAD techniques in Lung cancer diagnosis [1] . ...
doi:10.6084/m9.figshare.20217716.v1
fatcat:uj3iktdxzjgf5gyhg63oj5weyu
Image Processing-Based Lung Cancer Detection Using Adaptive CNN Mixed Sine Cosine Crow Search Algorithm in Medical Applications
2022
International Journal on Future Revolution in Computer Science & Communication Engineering
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Medical image processing relies heavily on the diagnosis of lung cancer images. It aids doctors in determining the correct diagnosis and management. ...
In this study, an Adaptive CNN Mixed Sine Cosine Crow Search (ACNN-SCCS) strategy is proposed to assess the presence of lung cancer in CT images based on the imaging technique. ...
Figure 1: Lung cancer detection based on image processing In Figure 1 , we see how image processing may be used to detect lung cancer. ...
doi:10.17762/ijfrcsce.v8i1.2088
fatcat:og6wd5tkbbgolpasdmpxrnnhdy
A Review on Lung Cancer Detection Using PET/CT Scan
2017
International Journal of Advanced Research in Computer Science and Software Engineering
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The core variables for detection of lung cancer on the basis of image processing strategy are Image quality and accuracy. ...
For lung cancer prediction, Time factor is very important to find the abnormality issue in target images on the basis of variations. ...
In this paper we propose strategy for identification of Lung cancer utilizing image processing (mean shift) algorithm taken after by edge detection utilizing Morphological method.
II. ...
doi:10.23956/ijarcsse/v7i5/0120
fatcat:7tkqbljt3nbt3krhu7vpzcnfeu
Comparative Study on Automated Cell Nuclei Segmentation Methods for Cytology Pleural Effusion Images
2018
Journal of Healthcare Engineering
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Automated cell nuclei segmentation is the most crucial step toward the implementation of a computer-aided diagnosis system for cancer cells. ...
The findings of this study will be useful for current and potential future studies on cytology images of pleural effusion. ...
University, ailand, for the insightful suggestions, including their cooperation for the dataset and ground truth segmentation. ...
doi:10.1155/2018/9240389
pmid:30344991
pmcid:PMC6164204
fatcat:3lgiafvcxneehhfhckp5m4ts7y
An Evaluation of Features Extraction from Lung CT Images for the Classification Stage of Malignancy
2016
IOSR Journal of Computer Engineering
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Researchers have focused on developing an algorithm using image processing to detect the different types of cancer in its early stage. ...
To achieve this, preprocessing of the acquired original image is needed. This study evaluates CT images of lung, which contains noise. ...
This method is based on threshold selection criteria. Based on this method, threshold value will be between 0 and 1. After achieving this value we can segment an image based on it [11] . ...
doi:10.9790/0661-15010010178-83
fatcat:mewqfiibunboljteb3y4z7dt44
A Survey on AI Techniques for Thoracic Diseases Diagnosis Using Medical Images
2022
Diagnostics
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diseases (e.g., pneumonia, COVID-19, edema, fibrosis, tuberculosis, chronic obstructive pulmonary disease (COPD), and lung cancer); transfer learning background knowledge; ensemble learning; and future ...
Earlier, only highly experienced radiologists examined thoracic diseases, but recent developments in image processing and deep learning techniques are opening the door for the automated detection of these ...
[128] presented a cardiac segmentation and diagnosis through an automated pipeline based on a private MRI images dataset of 150 patients from the Dijon Hospital (Medical Image Computing and Computer ...
doi:10.3390/diagnostics12123034
pmid:36553041
pmcid:PMC9777249
fatcat:ypbpk75mj5ckbon5jnjumdazxu
Detection of COVID-19 Cases with Fuzzy Classifiers Using Chest Computed Tomography
2021
European Journal of Science and Technology
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In this paper, we present a new approach based on fuzzy classification for the detection of COVID-19 using 3D CT volumes. ...
As a result of examinations on CT scans, a radiological finding that is called ground-glass opacity, causing color, and texture change, was found in the lung of a person with COVID-19. ...
Statistical and gray level coformation matrix parameters calculated from segmented chest CT images were used in adaptive-network based fuzzy inference systems for the classification of lung cancer (Kuruvilla ...
doi:10.31590/ejosat.950941
fatcat:b54vthznhvgeba6dessjdfsypi
A Survey of Computer-Aided Tumor Diagnosis Based on Convolutional Neural Network
2021
Biology
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It introduces the segmentation and classification of tumor images as well as the diagnosis methods based on CNN to help doctors determine tumors. ...
The research on computer-aided diagnosis based on medical images of tumors has become a sharper focus in the industry. ...
Acknowledgments: Thanks to Si-Yuan Lu for his contribution to the revision of the manuscript.
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/biology10111084
pmid:34827077
pmcid:PMC8615026
fatcat:dr3b5ozqx5eppdqoara4wctefq
A comparative analysis of chronic obstructive pulmonary disease using machine learning, and deep learning
2023
International Journal of Power Electronics and Drive Systems (IJPEDS)
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<span lang="EN-US">Chronic obstructive pulmonary disease (COPD) is a general clinical issue in numerous countries considered the fifth reason for inability and the third reason for mortality on a global ...
This research aims to cover the detailed findings on pulmonary diseases or lung diseases, their causes, and symptoms, which will help treat infections with high performance and a swift response. ...
In the National Lung Cancer Screening Study, the suggested COPD and emphysema classification based on CNN indicates a cellular breakdown in the lungs. ...
doi:10.11591/ijece.v13i1.pp389-399
fatcat:omltpknnabaipk22peksvdk73e
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