Breast Segmentation with Pectoral Muscle Suppression on Digital Mammograms
Previous works on breast tissue identification and abnormalities detection notice that the feature extraction process is affected if the region processed is not well focused. Thereby, it is important to split the mammogram into interesting regions to achieve optimal breast parenchyma measurements, b...
Gespeichert in:
| Hauptverfasser: | , , , , |
|---|---|
| Format: | Tagungsbericht |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 478 |
|---|---|
| container_issue | |
| container_start_page | 471 |
| container_title | |
| container_volume | |
| creator | Raba, David Oliver, Arnau Martí, Joan Peracaula, Marta Espunya, Joan |
| description | Previous works on breast tissue identification and abnormalities detection notice that the feature extraction process is affected if the region processed is not well focused. Thereby, it is important to split the mammogram into interesting regions to achieve optimal breast parenchyma measurements, breast registration or to put into focus a technique when we search for abnormalities. In this paper, we review most of the relevant work that has been presented from 80’s to nowadays. Secondly, an automated technique for segmenting a digital mammogram into breast region and background, with pectoral muscle suppression is presented. |
| doi_str_mv | 10.1007/11492542_58 |
| format | Conference Proceeding |
| fullrecord | <record><control><sourceid>pascalfrancis_sprin</sourceid><recordid>TN_cdi_pascalfrancis_primary_16895019</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>16895019</sourcerecordid><originalsourceid>FETCH-LOGICAL-c261t-f8a702d985d126a4b7e8fa81bbb2d23dc694820421d6b1dac0d1a4c80732a1e83</originalsourceid><addsrcrecordid>eNpNkEtLxDAUheMLrOOs_APduHBRzb1J22Sp45sRhdF1uU3TWu2LpIP47-0wIsKBu_g-LofD2Anwc-A8vQCQGmOJWax22FynSsSSC0ShcJcFkABEQki998cwgVjKfRZwwTHSqRSH7Mj7D845phoD9njlLPkxXNmqtd1IY9134Vc9vocv1oy9oyZ8WnvT2HC1HgZnvd8IU67rqh43lNq2rxy1_pgdlNR4O_-9M_Z2e_O6uI-Wz3cPi8tlZKY2Y1QqSjkWWsUFYEIyT60qSUGe51igKEyipUIuEYokh4IML4CkUTwVSGCVmLHT7d-BvKGmdNSZ2meDq1ty3xkkSscc9OSdbT0_oa6yLsv7_tNnwLPNmNm_McUPQJ9hTQ</addsrcrecordid><sourcetype>Index Database</sourcetype><iscdi>true</iscdi><recordtype>conference_proceeding</recordtype></control><display><type>conference_proceeding</type><title>Breast Segmentation with Pectoral Muscle Suppression on Digital Mammograms</title><source>Springer Books</source><creator>Raba, David ; Oliver, Arnau ; Martí, Joan ; Peracaula, Marta ; Espunya, Joan</creator><contributor>Pina, Pedro ; Pérez de la Blanca, Nicolás ; Marques, Jorge S.</contributor><creatorcontrib>Raba, David ; Oliver, Arnau ; Martí, Joan ; Peracaula, Marta ; Espunya, Joan ; Pina, Pedro ; Pérez de la Blanca, Nicolás ; Marques, Jorge S.</creatorcontrib><description>Previous works on breast tissue identification and abnormalities detection notice that the feature extraction process is affected if the region processed is not well focused. Thereby, it is important to split the mammogram into interesting regions to achieve optimal breast parenchyma measurements, breast registration or to put into focus a technique when we search for abnormalities. In this paper, we review most of the relevant work that has been presented from 80’s to nowadays. Secondly, an automated technique for segmenting a digital mammogram into breast region and background, with pectoral muscle suppression is presented.</description><identifier>ISSN: 0302-9743</identifier><identifier>ISBN: 9783540261544</identifier><identifier>ISBN: 3540261540</identifier><identifier>ISBN: 9783540261537</identifier><identifier>ISBN: 3540261532</identifier><identifier>EISSN: 1611-3349</identifier><identifier>EISBN: 9783540322382</identifier><identifier>EISBN: 3540322388</identifier><identifier>DOI: 10.1007/11492542_58</identifier><language>eng</language><publisher>Berlin, Heidelberg: Springer Berlin Heidelberg</publisher><subject>Active Contour ; Applied sciences ; Artificial intelligence ; Computer science; control theory; systems ; Digital Mammography ; Exact sciences and technology ; Mammographic Density ; Mammographic Image ; Pattern recognition. Digital image processing. Computational geometry ; Pectoral Muscle</subject><ispartof>Lecture notes in computer science, 2005, p.471-478</ispartof><rights>Springer-Verlag Berlin Heidelberg 2005</rights><rights>2005 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c261t-f8a702d985d126a4b7e8fa81bbb2d23dc694820421d6b1dac0d1a4c80732a1e83</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/11492542_58$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/11492542_58$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>309,310,779,780,784,789,790,793,4040,4041,27916,38246,41433,42502</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=16895019$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><contributor>Pina, Pedro</contributor><contributor>Pérez de la Blanca, Nicolás</contributor><contributor>Marques, Jorge S.</contributor><creatorcontrib>Raba, David</creatorcontrib><creatorcontrib>Oliver, Arnau</creatorcontrib><creatorcontrib>Martí, Joan</creatorcontrib><creatorcontrib>Peracaula, Marta</creatorcontrib><creatorcontrib>Espunya, Joan</creatorcontrib><title>Breast Segmentation with Pectoral Muscle Suppression on Digital Mammograms</title><title>Lecture notes in computer science</title><description>Previous works on breast tissue identification and abnormalities detection notice that the feature extraction process is affected if the region processed is not well focused. Thereby, it is important to split the mammogram into interesting regions to achieve optimal breast parenchyma measurements, breast registration or to put into focus a technique when we search for abnormalities. In this paper, we review most of the relevant work that has been presented from 80’s to nowadays. Secondly, an automated technique for segmenting a digital mammogram into breast region and background, with pectoral muscle suppression is presented.</description><subject>Active Contour</subject><subject>Applied sciences</subject><subject>Artificial intelligence</subject><subject>Computer science; control theory; systems</subject><subject>Digital Mammography</subject><subject>Exact sciences and technology</subject><subject>Mammographic Density</subject><subject>Mammographic Image</subject><subject>Pattern recognition. Digital image processing. Computational geometry</subject><subject>Pectoral Muscle</subject><issn>0302-9743</issn><issn>1611-3349</issn><isbn>9783540261544</isbn><isbn>3540261540</isbn><isbn>9783540261537</isbn><isbn>3540261532</isbn><isbn>9783540322382</isbn><isbn>3540322388</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2005</creationdate><recordtype>conference_proceeding</recordtype><recordid>eNpNkEtLxDAUheMLrOOs_APduHBRzb1J22Sp45sRhdF1uU3TWu2LpIP47-0wIsKBu_g-LofD2Anwc-A8vQCQGmOJWax22FynSsSSC0ShcJcFkABEQki998cwgVjKfRZwwTHSqRSH7Mj7D845phoD9njlLPkxXNmqtd1IY9134Vc9vocv1oy9oyZ8WnvT2HC1HgZnvd8IU67rqh43lNq2rxy1_pgdlNR4O_-9M_Z2e_O6uI-Wz3cPi8tlZKY2Y1QqSjkWWsUFYEIyT60qSUGe51igKEyipUIuEYokh4IML4CkUTwVSGCVmLHT7d-BvKGmdNSZ2meDq1ty3xkkSscc9OSdbT0_oa6yLsv7_tNnwLPNmNm_McUPQJ9hTQ</recordid><startdate>2005</startdate><enddate>2005</enddate><creator>Raba, David</creator><creator>Oliver, Arnau</creator><creator>Martí, Joan</creator><creator>Peracaula, Marta</creator><creator>Espunya, Joan</creator><general>Springer Berlin Heidelberg</general><general>Springer</general><scope>IQODW</scope></search><sort><creationdate>2005</creationdate><title>Breast Segmentation with Pectoral Muscle Suppression on Digital Mammograms</title><author>Raba, David ; Oliver, Arnau ; Martí, Joan ; Peracaula, Marta ; Espunya, Joan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c261t-f8a702d985d126a4b7e8fa81bbb2d23dc694820421d6b1dac0d1a4c80732a1e83</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Active Contour</topic><topic>Applied sciences</topic><topic>Artificial intelligence</topic><topic>Computer science; control theory; systems</topic><topic>Digital Mammography</topic><topic>Exact sciences and technology</topic><topic>Mammographic Density</topic><topic>Mammographic Image</topic><topic>Pattern recognition. Digital image processing. Computational geometry</topic><topic>Pectoral Muscle</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Raba, David</creatorcontrib><creatorcontrib>Oliver, Arnau</creatorcontrib><creatorcontrib>Martí, Joan</creatorcontrib><creatorcontrib>Peracaula, Marta</creatorcontrib><creatorcontrib>Espunya, Joan</creatorcontrib><collection>Pascal-Francis</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Raba, David</au><au>Oliver, Arnau</au><au>Martí, Joan</au><au>Peracaula, Marta</au><au>Espunya, Joan</au><au>Pina, Pedro</au><au>Pérez de la Blanca, Nicolás</au><au>Marques, Jorge S.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Breast Segmentation with Pectoral Muscle Suppression on Digital Mammograms</atitle><btitle>Lecture notes in computer science</btitle><date>2005</date><risdate>2005</risdate><spage>471</spage><epage>478</epage><pages>471-478</pages><issn>0302-9743</issn><eissn>1611-3349</eissn><isbn>9783540261544</isbn><isbn>3540261540</isbn><isbn>9783540261537</isbn><isbn>3540261532</isbn><eisbn>9783540322382</eisbn><eisbn>3540322388</eisbn><abstract>Previous works on breast tissue identification and abnormalities detection notice that the feature extraction process is affected if the region processed is not well focused. Thereby, it is important to split the mammogram into interesting regions to achieve optimal breast parenchyma measurements, breast registration or to put into focus a technique when we search for abnormalities. In this paper, we review most of the relevant work that has been presented from 80’s to nowadays. Secondly, an automated technique for segmenting a digital mammogram into breast region and background, with pectoral muscle suppression is presented.</abstract><cop>Berlin, Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/11492542_58</doi><tpages>8</tpages></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0302-9743 |
| ispartof | Lecture notes in computer science, 2005, p.471-478 |
| issn | 0302-9743 1611-3349 |
| language | eng |
| recordid | cdi_pascalfrancis_primary_16895019 |
| source | Springer Books |
| subjects | Active Contour Applied sciences Artificial intelligence Computer science control theory systems Digital Mammography Exact sciences and technology Mammographic Density Mammographic Image Pattern recognition. Digital image processing. Computational geometry Pectoral Muscle |
| title | Breast Segmentation with Pectoral Muscle Suppression on Digital Mammograms |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-15T06%3A15%3A48IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-pascalfrancis_sprin&rft_val_fmt=info:ofi/fmt:kev:mtx:book&rft.genre=proceeding&rft.atitle=Breast%20Segmentation%20with%20Pectoral%20Muscle%20Suppression%20on%20Digital%20Mammograms&rft.btitle=Lecture%20notes%20in%20computer%20science&rft.au=Raba,%20David&rft.date=2005&rft.spage=471&rft.epage=478&rft.pages=471-478&rft.issn=0302-9743&rft.eissn=1611-3349&rft.isbn=9783540261544&rft.isbn_list=3540261540&rft.isbn_list=9783540261537&rft.isbn_list=3540261532&rft_id=info:doi/10.1007/11492542_58&rft_dat=%3Cpascalfrancis_sprin%3E16895019%3C/pascalfrancis_sprin%3E%3Curl%3E%3C/url%3E&rft.eisbn=9783540322382&rft.eisbn_list=3540322388&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |