<Record><identifier xmlns="http://purl.org/dc/elements/1.1/">URN:NBN:SI:DOC-HODJT6AN</identifier><date>2020</date><creator>Kos, Anton</creator><creator>Sun, Yingming</creator><creator>Yang, Xinyu</creator><creator>Zhang, Yuan</creator><relation>documents/doc/H/URN_NBN_SI_doc-HODJT6AN_001.pdf</relation><relation>documents/doc/H/URN_NBN_SI_doc-HODJT6AN_001.txt</relation><format format_type="issue">1/2</format><format format_type="volume">87</format><format format_type="type">article</format><format format_type="extent">str. 68-73</format><identifier identifier_type="ISSN">0013-5852</identifier><identifier identifier_type="COBISSID_HOST">12930644</identifier><identifier identifier_type="URN">URN:NBN:SI:doc-HODJT6AN</identifier><language>eng</language><publisher>Strokovna zadruga koncesijoniranih elektrotehnikov</publisher><source>Elektrotehniški vestnik</source><rights>InC</rights><subject language_type_id="eng">cardiac MRI</subject><subject language_type_id="slv">globoka nevronska mreža</subject><subject language_type_id="eng">medical image segmentation</subject><subject language_type_id="eng">neural networks</subject><subject language_type_id="slv">razčlenitev mediciske slike</subject><subject language_type_id="slv">srčna magnetna resonanca</subject><title>Automatic segmentation based on the cardiac magnetic resonance image using a modified fully convolutional network</title></Record>