https://m2.mtmt.hu/ hun 2026-09-21 14:49 JournalArticle 31810968 VALIDATED true 0 false 2026-05-20T12:31:20.667+0000 2026-04-20T09:37:55.676+0000 2021-01-14T13:56:43.329+0000 true 10015546 Berhidi Anna /api/admin/10015546 Admin true 10015546 2026-04-20T09:23:13.800+0000 2026-04-20T09:23:13.800+0000 2026-04-20T09:37:55.843+0000 true 10062062 Gere Tamásné /api/admin/10062062 Admin true 10062062 true false true 24 24 /api/publicationtype/24 PublicationType 1 true 24 JournalArticle true 10000059 Article true 24 24 /api/publicationtype/24 PublicationType 1 true 24 JournalArticle /api/subtype/10000059 Szakcikk SubType 101 true 10000059 true 1 /api/category/1 Category true 1 Marosán, Péter Automated seeding for ultrasound skin lesion segmentation true true /api/journal/4344 REVIEWED true false 4344 false 4344 true 0041-624X 1874-9968 Journal FOREIGN 110 106268 106268 13 2021 The segmentation of cancer-suspicious skin lesions using ultrasound may help their differential diagnosis and treatment planning. Active contour models (ACM) require an initial seed, which when manually chosen may cause variations in segmentation accuracy. Fully-automated skin segmentation typically employs layer-by-layer segmentation using a combination of methods; however, such segmentation has not yet been applied on cancerous lesions. In the current work, fully automated segmentation is achieved in two steps: an automated seeding (AS) step using a layer-by-layer method followed by a growing step using an ACM. The method was tested on images of nevi, melanomas, and basal cell carcinomas from two ultrasound imaging systems (N = 60), with all lesions being successfully located. For the seeding step, manual seeding (MS) was used as a reference. AS approached the accuracy of MS when the latter used an optimal bounding rectangle based on the ground truth (Sorensen-Dice coefficient (SDC) of 72.3 vs 74.6, respectively). The effect of varying the manual seed was also investigated; a 0.7 decrease in seed height and width caused a mean SDC of 54.6. 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Egyetem">PPKE</span>/<span title="Információs Technológiai és Bionikai Kar">ITK</span>/Roska Tamás Műszaki és Természettudományi Doktori Iskola</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10076076"><a href="/gui2/?type=authors&mode=browse&sel=10076076" target="_blank">Szalai Klára (<span class="authorship-author-name">Szalai Klára</span> <span class="authorAux-mtmt"> bőrgyógyászat, radiológia</span>) </a> </span> <span class="author-affil"><span title="Semmelweis Egyetem">SE</span>/<span title="Általános Orvostudományi Kar">AOK</span>/<span title="Klinikum">K</span>/Bőr-, Nemikórtani és Bőronkológiai Klinika</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" >Csabai Domonkos </span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10051304"><a href="/gui2/?type=authors&mode=browse&sel=10051304" target="_blank">Csány Gergely (<span class="authorship-author-name">Csány Gergely</span> <span class="authorAux-mtmt"> Ultrahang diagnosztika</span>) </a> </span> <span class="author-affil"><span title="Pázmány Péter Katolikus Egyetem">PPKE</span>/<span title="Információs Technológiai és Bionikai Kar">ITK</span>/Roska Tamás Műszaki és Természettudományi Doktori Iskola</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10029872"><a href="/gui2/?type=authors&mode=browse&sel=10029872" target="_blank">Horváth András (<span class="authorship-author-name">Horváth András</span> <span class="authorAux-mtmt"> mérnöki tudományok</span>) </a> </span> <span class="author-affil"><span title="Pázmány Péter Katolikus Egyetem">PPKE</span>/Információs Technológiai és Bionikai Kar</span> ;&nbsp;&nbsp;&nbsp; <span class="author-name" mtid="10020416"><a href="/gui2/?type=authors&mode=browse&sel=10020416" target="_blank">Gyöngy Miklós (<span class="authorship-author-name">Gyöngy Miklós</span> <span class="authorAux-mtmt"> Jelfeldolgozás</span>) </a> </span> <span class="author-affil"><span title="Pázmány Péter Katolikus Egyetem">PPKE</span>/Információs Technológiai és Bionikai Kar</span> </div> </div> <div class="title"><a href="/gui2/?mode=browse&params=publication;31810968" target="_blank">Automated seeding for ultrasound skin lesion segmentation</a></div> <div> <span class="journal-title">ULTRASONICS</span> <span class="journal-issn">(<a target="_blank" href="https://portal.issn.org/resource/ISSN/0041-624X">0041-624X</a> <a target="_blank" href="https://portal.issn.org/resource/ISSN/1874-9968">1874-9968</a>)</span>: <span class="journal-volume">110</span> <span class="page"> Paper 106268. 13 p. </span> <span class="year">(2021)</span> </div> <div class="pub-footer"> <span class="language" xmlns="http://www.w3.org/1999/html">Nyelv: Angol | </span> <span class="identifiers"> <span class="id identifier oa_GOLD" title=" Gold "> <a style="color:blue" title="10.1016/j.ultras.2020.106268" target="_blank" href="https://doi.org/10.1016/j.ultras.2020.106268"> DOI </a> </span> <span class="id identifier oa_none" title="none"> <a 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19</span> | Független: 18 | Függő: 1 | Nem jelölt: 0 | WoS jelölt: 12 | Scopus jelölt:&nbsp;10 | WoS/Scopus jelölt:&nbsp;12 | DOI jelölt:&nbsp;12 </div> <div class="publication-citation"> <a target="_blank" href="/api/publication?cond=citations.related;eq;31810968&sort=publishedYear,desc&sort=title"> Idézett közlemények száma: 1 </a> </div> <div class="mtid"><span class="long-pub-mtid">Közlemény: 31810968</span> | <span class="status-data status-VALIDATED"> Egyeztetett </span> Forrás Idéző | <span class="type-subtype">Folyóiratcikk ( Szakcikk ) </span> | <span class="pub-category">Tudományos</span> | <span class="publication-sourceOfData">WOS TAGGED</span> </div> <div class="lastModified">Utolsó módosítás: 2026.04.20. 11:37 Gere Tamásné (SE_KK_Admin5_GT, admin) </div> </div></div>