Evaluation Performance of GLCM and Pixel Intensity Matrix for Liver Cirrhosis
Mainly due to liver diseases 216,865 people around the world die, which is about 2.44% of total deaths in the world. Cirrhosis is the one most dangerous liver disorder which adds up to this huge number. Cirrhosis is a condition where liver slowly deteriorates with formation of scar tissue and cannot...
Gespeichert in:
| Veröffentlicht in: | International journal of advanced networking and applications 2017-01, Vol.8 (4), p.72-74 |
|---|---|
| Hauptverfasser: | , , , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 74 |
|---|---|
| container_issue | 4 |
| container_start_page | 72 |
| container_title | International journal of advanced networking and applications |
| container_volume | 8 |
| creator | Arabi, Punal M Ramya, M R Pandey, Sanjaya Chinnabhandar, Varini |
| description | Mainly due to liver diseases 216,865 people around the world die, which is about 2.44% of total deaths in the world. Cirrhosis is the one most dangerous liver disorder which adds up to this huge number. Cirrhosis is a condition where liver slowly deteriorates with formation of scar tissue and cannot function normally due to long lasting or chronic injury. In this paper we have used novel methods GLCM (Gray Level Co-occurrence Matrix) and Pixel Intensity Matrix after obtaining CT scan images (Computed Tomography) of healthy liver and cirrhosis affected liver. Performance Evaluation of both matrices is carried out to analyze cirrhosis liver. |
| format | Article |
| fullrecord | <record><control><sourceid>proquest</sourceid><recordid>TN_cdi_proquest_journals_2762020967</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2762020967</sourcerecordid><originalsourceid>FETCH-proquest_journals_27620209673</originalsourceid><addsrcrecordid>eNqNir0KwjAURoMoWLTvcMG5ECMmzVzqD7TQwb0ETTGlJnqTlvr2dhBnz_Id-M6MRFSKfUJZyuY_l3RJYu9bOsEFTeU2ImU-qK5XwTgLlcbG4UPZqwbXwLHISlD2BpUZdQdnG7T1JryhVAHNCFMLhRk0QmYQ784bvyaLRnVex99dkc0hv2Sn5Inu1Wsf6tb1aKerZoIzyqjkYvdf9QHNED85</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2762020967</pqid></control><display><type>article</type><title>Evaluation Performance of GLCM and Pixel Intensity Matrix for Liver Cirrhosis</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Arabi, Punal M ; Ramya, M R ; Pandey, Sanjaya ; Chinnabhandar, Varini</creator><creatorcontrib>Arabi, Punal M ; Ramya, M R ; Pandey, Sanjaya ; Chinnabhandar, Varini</creatorcontrib><description>Mainly due to liver diseases 216,865 people around the world die, which is about 2.44% of total deaths in the world. Cirrhosis is the one most dangerous liver disorder which adds up to this huge number. Cirrhosis is a condition where liver slowly deteriorates with formation of scar tissue and cannot function normally due to long lasting or chronic injury. In this paper we have used novel methods GLCM (Gray Level Co-occurrence Matrix) and Pixel Intensity Matrix after obtaining CT scan images (Computed Tomography) of healthy liver and cirrhosis affected liver. Performance Evaluation of both matrices is carried out to analyze cirrhosis liver.</description><identifier>ISSN: 0975-0290</identifier><identifier>EISSN: 0975-0282</identifier><language>eng</language><publisher>Eswar Publications</publisher><subject>Bile ducts ; Chronic illnesses ; Computed tomography ; Engineering schools ; Expected values ; Hepatitis ; Hepatology ; Liver ; Liver cancer ; Liver cirrhosis ; Liver diseases ; Medical imaging ; Medical research ; Performance evaluation ; Pixels ; Scars ; Spleen ; Standard deviation ; Statistical analysis ; Ultrasonic imaging</subject><ispartof>International journal of advanced networking and applications, 2017-01, Vol.8 (4), p.72-74</ispartof><rights>2017. This work is published under http://www.ijana.in/index.php (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>315,782,786</link.rule.ids></links><search><creatorcontrib>Arabi, Punal M</creatorcontrib><creatorcontrib>Ramya, M R</creatorcontrib><creatorcontrib>Pandey, Sanjaya</creatorcontrib><creatorcontrib>Chinnabhandar, Varini</creatorcontrib><title>Evaluation Performance of GLCM and Pixel Intensity Matrix for Liver Cirrhosis</title><title>International journal of advanced networking and applications</title><description>Mainly due to liver diseases 216,865 people around the world die, which is about 2.44% of total deaths in the world. Cirrhosis is the one most dangerous liver disorder which adds up to this huge number. Cirrhosis is a condition where liver slowly deteriorates with formation of scar tissue and cannot function normally due to long lasting or chronic injury. In this paper we have used novel methods GLCM (Gray Level Co-occurrence Matrix) and Pixel Intensity Matrix after obtaining CT scan images (Computed Tomography) of healthy liver and cirrhosis affected liver. Performance Evaluation of both matrices is carried out to analyze cirrhosis liver.</description><subject>Bile ducts</subject><subject>Chronic illnesses</subject><subject>Computed tomography</subject><subject>Engineering schools</subject><subject>Expected values</subject><subject>Hepatitis</subject><subject>Hepatology</subject><subject>Liver</subject><subject>Liver cancer</subject><subject>Liver cirrhosis</subject><subject>Liver diseases</subject><subject>Medical imaging</subject><subject>Medical research</subject><subject>Performance evaluation</subject><subject>Pixels</subject><subject>Scars</subject><subject>Spleen</subject><subject>Standard deviation</subject><subject>Statistical analysis</subject><subject>Ultrasonic imaging</subject><issn>0975-0290</issn><issn>0975-0282</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqNir0KwjAURoMoWLTvcMG5ECMmzVzqD7TQwb0ETTGlJnqTlvr2dhBnz_Id-M6MRFSKfUJZyuY_l3RJYu9bOsEFTeU2ImU-qK5XwTgLlcbG4UPZqwbXwLHISlD2BpUZdQdnG7T1JryhVAHNCFMLhRk0QmYQ784bvyaLRnVex99dkc0hv2Sn5Inu1Wsf6tb1aKerZoIzyqjkYvdf9QHNED85</recordid><startdate>20170101</startdate><enddate>20170101</enddate><creator>Arabi, Punal M</creator><creator>Ramya, M R</creator><creator>Pandey, Sanjaya</creator><creator>Chinnabhandar, Varini</creator><general>Eswar Publications</general><scope>3V.</scope><scope>7SC</scope><scope>7XB</scope><scope>8AL</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K7-</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0N</scope><scope>P5Z</scope><scope>P62</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope></search><sort><creationdate>20170101</creationdate><title>Evaluation Performance of GLCM and Pixel Intensity Matrix for Liver Cirrhosis</title><author>Arabi, Punal M ; Ramya, M R ; Pandey, Sanjaya ; Chinnabhandar, Varini</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_27620209673</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Bile ducts</topic><topic>Chronic illnesses</topic><topic>Computed tomography</topic><topic>Engineering schools</topic><topic>Expected values</topic><topic>Hepatitis</topic><topic>Hepatology</topic><topic>Liver</topic><topic>Liver cancer</topic><topic>Liver cirrhosis</topic><topic>Liver diseases</topic><topic>Medical imaging</topic><topic>Medical research</topic><topic>Performance evaluation</topic><topic>Pixels</topic><topic>Scars</topic><topic>Spleen</topic><topic>Standard deviation</topic><topic>Statistical analysis</topic><topic>Ultrasonic imaging</topic><toplevel>online_resources</toplevel><creatorcontrib>Arabi, Punal M</creatorcontrib><creatorcontrib>Ramya, M R</creatorcontrib><creatorcontrib>Pandey, Sanjaya</creatorcontrib><creatorcontrib>Chinnabhandar, Varini</creatorcontrib><collection>ProQuest Central (Corporate)</collection><collection>Computer and Information Systems Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Computing Database (Alumni Edition)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>Computer Science Database</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Computing Database</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Access via ProQuest (Open Access)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><jtitle>International journal of advanced networking and applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Arabi, Punal M</au><au>Ramya, M R</au><au>Pandey, Sanjaya</au><au>Chinnabhandar, Varini</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Evaluation Performance of GLCM and Pixel Intensity Matrix for Liver Cirrhosis</atitle><jtitle>International journal of advanced networking and applications</jtitle><date>2017-01-01</date><risdate>2017</risdate><volume>8</volume><issue>4</issue><spage>72</spage><epage>74</epage><pages>72-74</pages><issn>0975-0290</issn><eissn>0975-0282</eissn><abstract>Mainly due to liver diseases 216,865 people around the world die, which is about 2.44% of total deaths in the world. Cirrhosis is the one most dangerous liver disorder which adds up to this huge number. Cirrhosis is a condition where liver slowly deteriorates with formation of scar tissue and cannot function normally due to long lasting or chronic injury. In this paper we have used novel methods GLCM (Gray Level Co-occurrence Matrix) and Pixel Intensity Matrix after obtaining CT scan images (Computed Tomography) of healthy liver and cirrhosis affected liver. Performance Evaluation of both matrices is carried out to analyze cirrhosis liver.</abstract><pub>Eswar Publications</pub><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0975-0290 |
| ispartof | International journal of advanced networking and applications, 2017-01, Vol.8 (4), p.72-74 |
| issn | 0975-0290 0975-0282 |
| language | eng |
| recordid | cdi_proquest_journals_2762020967 |
| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Bile ducts Chronic illnesses Computed tomography Engineering schools Expected values Hepatitis Hepatology Liver Liver cancer Liver cirrhosis Liver diseases Medical imaging Medical research Performance evaluation Pixels Scars Spleen Standard deviation Statistical analysis Ultrasonic imaging |
| title | Evaluation Performance of GLCM and Pixel Intensity Matrix for Liver Cirrhosis |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-01T23%3A53%3A49IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Evaluation%20Performance%20of%20GLCM%20and%20Pixel%20Intensity%20Matrix%20for%20Liver%20Cirrhosis&rft.jtitle=International%20journal%20of%20advanced%20networking%20and%20applications&rft.au=Arabi,%20Punal%20M&rft.date=2017-01-01&rft.volume=8&rft.issue=4&rft.spage=72&rft.epage=74&rft.pages=72-74&rft.issn=0975-0290&rft.eissn=0975-0282&rft_id=info:doi/&rft_dat=%3Cproquest%3E2762020967%3C/proquest%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2762020967&rft_id=info:pmid/&rfr_iscdi=true |