AMIA Annu Symp Proc - Towards the creation of a visual ontology of biomedical imaging entities.

Tópicos

{ concept(1167) ontolog(924) domain(897) }
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{ method(2212) result(1239) propos(1039) }
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{ inform(2794) health(2639) internet(1427) }
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{ high(1669) rate(1365) level(1280) }
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{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
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{ group(2977) signific(1463) compar(1072) }
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{ structur(1116) can(940) graph(676) }
{ cancer(2502) breast(956) screen(824) }
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{ survey(1388) particip(1329) question(1065) }
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{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }

Resumo

Image content is frequently the target of biomedical information extraction systems. However, the meaning of this content cannot be easily understood without some associated text. In order to improve the integration of textual and visual information, we are developing a visual ontology for biomedical image retrieval. Our visual ontology maps the appearance of image regions to concepts in an existing textual ontology, thereby inheriting relationships among the visual entities. Such a resource creates a bridge between the visual characteristics of important image regions and their semantic interpretation. We automatically populate our visual ontology by pairing image regions with their associated descriptions. To demonstrate the usefulness of this resource, we have developed a classification method that automatically labels image regions with appropriate concepts based solely on their appearance. Our results for thoracic imaging terms show that our methods are promising first steps towards the creation of a biomedical visual ontology.

Resumo Limpo

imag content frequent target biomed inform extract system howev mean content easili understood without associ text order improv integr textual visual inform develop visual ontolog biomed imag retriev visual ontolog map appear imag region concept exist textual ontolog therebi inherit relationship among visual entiti resourc creat bridg visual characterist import imag region semant interpret automat popul visual ontolog pair imag region associ descript demonstr use resourc develop classif method automat label imag region appropri concept base sole appear result thorac imag term show method promis first step toward creation biomed visual ontolog

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