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<bibitem type="C">   <ARLID>0086850</ARLID> <utime>20240103184526.3</utime><mtime>20071012235959.9</mtime>         <title language="eng" primary="1">Medical Image Segmentation Using Cooccurrence Matrix Based Texture Features Calculated on Weighted Region</title>  <specification> <page_count>7 s.</page_count> </specification>   <serial><ARLID>cav_un_epca*0087411</ARLID><ISBN>978-0-88986-656-0</ISBN><title>Advances in Computer Science and Technology . IASTED international conference 2007 /3./</title><part_num/><part_title/><page_num>1-7</page_num><publisher><place>Phuket</place><name>ACTA Press</name><year>2007</year></publisher></serial>   <title language="cze" primary="0">Segmentace medicínských obrázků pomocí texturních příznaků založených na vážených kookurenčních maticích</title>    <keyword>medical image analysis</keyword>   <keyword>bioinformatics</keyword>   <keyword>pattern recognition</keyword>    <author primary="1"> <ARLID>cav_un_auth*0101211</ARLID> <name1>Tesař</name1> <name2>Ludvík</name2> <institution>UTIA-B</institution>  <fullinstit>Ústav teorie informace a automatizace AV ČR, v. v. i.</fullinstit> </author> <author primary="0"> <ARLID>cav_un_auth*0015541</ARLID> <name1>Smutek</name1> <name2>D.</name2> <country>CZ</country>  </author> <author primary="0"> <ARLID>cav_un_auth*0230998</ARLID> <name1>Shimizu</name1> <name2>A.</name2> <country>JP</country>  </author> <author primary="0"> <ARLID>cav_un_auth*0230999</ARLID> <name1>Kobatake</name1> <name2>H.</name2> <country>JP</country>  </author>        <cas_special> <project> <project_id>1ET101050403</project_id> <agency>GA AV ČR</agency> <ARLID>cav_un_auth*0001930</ARLID> </project> <project> <project_id>1M0572</project_id> <agency>GA MŠk</agency> <ARLID>cav_un_auth*0001814</ARLID> </project> <research> <research_id>CEZ:AV0Z10750506</research_id> </research>  <abstract language="eng" primary="1">An improvement of texture based 2D or 3D co-occurrence based image segmentation method is proposed, aimed at medical image analysis. The co-occurerrence matrix is calculated so that each cooccurrence is weighted by the function of distance from the original pixel of interest.</abstract> <abstract language="cze" primary="0">Navrhuje se vylepšení ko-okurenční metody pro 2D nebo 3D segmentaci medicínských obrázků. Ko-okurenční matice se počítá tak, že každá ko-okurence se váží vzdáleností od bodu, pro který se matice počítá.</abstract>  <action target="WRD"> <ARLID>cav_un_auth*0230977</ARLID> <name>IASTED International Conference on Advances in Computer Science and Technology 2007 /3./</name> <place>Phuket</place> <dates>02.04.2007-04.04.2007</dates>  <country>TH</country> </action>    <reportyear>2008</reportyear>  <RIV>IN</RIV>      <permalink>http://hdl.handle.net/11104/0149001</permalink>       <arlyear>2007</arlyear>       <unknown tag="mrcbU63"> cav_un_epca*0087411 Advances in Computer Science and Technology . IASTED international conference 2007 /3./ 978-0-88986-656-0 1 7 Phuket ACTA Press 2007 </unknown> </cas_special> </bibitem>