J Am Med Inform Assoc - DCMDSM: a DICOM decomposed storage model.

Tópicos

{ search(2224) databas(1162) retriev(909) }
{ model(2341) predict(2261) use(1141) }
{ data(1714) softwar(1251) tool(1186) }
{ imag(2675) segment(2577) method(1081) }
{ concept(1167) ontolog(924) domain(897) }
{ result(1111) use(1088) new(759) }
{ take(945) account(800) differ(722) }
{ extract(1171) text(1153) clinic(932) }
{ cost(1906) reduc(1198) effect(832) }
{ imag(2830) propos(1344) filter(1198) }
{ control(1307) perform(991) simul(935) }
{ studi(1410) differ(1259) use(1210) }
{ sampl(1606) size(1419) use(1276) }
{ process(1125) use(805) approach(778) }
{ method(2212) result(1239) propos(1039) }
{ network(2748) neural(1063) input(814) }
{ model(2656) set(1616) predict(1553) }
{ patient(1821) servic(1111) care(1106) }
{ can(981) present(881) function(850) }
{ structur(1116) can(940) graph(676) }
{ use(1733) differ(960) four(931) }
{ survey(1388) particip(1329) question(1065) }
{ imag(1947) propos(1133) code(1026) }
{ data(1737) use(1416) pattern(1282) }
{ patient(2315) diseas(1263) diabet(1191) }
{ chang(1828) time(1643) increas(1301) }
{ clinic(1479) use(1117) guidelin(835) }
{ general(901) number(790) one(736) }
{ data(3963) clinic(1234) research(1004) }
{ risk(3053) factor(974) diseas(938) }
{ research(1085) discuss(1038) issu(1018) }
{ system(1050) medic(1026) inform(1018) }
{ compound(1573) activ(1297) structur(1058) }
{ perform(1367) use(1326) method(1137) }
{ studi(1119) effect(1106) posit(819) }
{ first(2504) two(1366) second(1323) }
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{ inform(2794) health(2639) internet(1427) }
{ system(1976) rule(880) can(841) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ bind(1733) structur(1185) ligand(1036) }
{ sequenc(1873) structur(1644) protein(1328) }
{ method(1219) similar(1157) match(930) }
{ featur(3375) classif(2383) classifi(1994) }
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{ motion(1329) object(1292) video(1091) }
{ assess(1506) score(1403) qualiti(1306) }
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{ surgeri(1148) surgic(1085) robot(1054) }
{ framework(1458) process(801) describ(734) }
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{ error(1145) method(1030) estim(1020) }
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{ method(1557) propos(1049) approach(1037) }
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{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ method(984) reconstruct(947) comput(926) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
{ howev(809) still(633) remain(590) }
{ perform(999) metric(946) measur(919) }
{ import(1318) role(1303) understand(862) }
{ visual(1396) interact(850) tool(830) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ model(3480) simul(1196) paramet(876) }
{ monitor(1329) mobil(1314) devic(1160) }
{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ medic(1828) order(1363) alert(1069) }
{ signal(2180) analysi(812) frequenc(800) }
{ group(2977) signific(1463) compar(1072) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ use(2086) technolog(871) perceiv(783) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ implement(1333) system(1263) develop(1122) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ method(1969) cluster(1462) data(1082) }

Resumo

JECTIVE: To design, build, and evaluate a storage model able to manage heterogeneous digital imaging and communications in medicine (DICOM) images. The model must be simple, but flexible enough to accommodate variable content without structural modifications; must be effective on answering query/retrieval operations according to the DICOM standard; and must provide performance gains on querying/retrieving content to justify its adoption by image-related projects.METHODS: The proposal adapts the original decomposed storage model, incorporating structural and organizational characteristics present in DICOM image files. Tag values are stored according to their data types/domains, in a schema built on top of a standard relational database management system (RDBMS). Evaluation includes storing heterogeneous DICOM images, querying metadata using a variable number of predicates, and retrieving full-content images for different hierarchical levels.RESULTS AND DISCUSSION: When compared to a well established DICOM image archive, the proposal is 0.6-7.2 times slower in storing content; however, in querying individual tags, it is about 48.0% faster. In querying groups of tags, DICOM decomposed storage model (DCMDSM) is outperformed in scenarios with a large number of tags and low selectivity (being 66.5% slower); however, when the number of tags is balanced with better selectivity predicates, the performance gains are up to 79.1%. In executing full-content retrieval, in turn, the proposal is about 48.3% faster.CONCLUSIONS: DCMDSM is a model built for the storage of heterogeneous DICOM content, based on a straightforward database design. The results obtained through its evaluation attest its suitability as a storage layer for projects where DICOM images are stored once, and queried/retrieved whenever necessary.

Resumo Limpo

jectiv design build evalu storag model abl manag heterogen digit imag communic medicin dicom imag model must simpl flexibl enough accommod variabl content without structur modif must effect answer queryretriev oper accord dicom standard must provid perform gain queryingretriev content justifi adopt imagerel projectsmethod propos adapt origin decompos storag model incorpor structur organiz characterist present dicom imag file tag valu store accord data typesdomain schema built top standard relat databas manag system rdbms evalu includ store heterogen dicom imag queri metadata use variabl number predic retriev fullcont imag differ hierarch levelsresult discuss compar well establish dicom imag archiv propos time slower store content howev queri individu tag faster queri group tag dicom decompos storag model dcmdsm outperform scenario larg number tag low select slower howev number tag balanc better select predic perform gain execut fullcont retriev turn propos fasterconclus dcmdsm model built storag heterogen dicom content base straightforward databas design result obtain evalu attest suitabl storag layer project dicom imag store queriedretriev whenev necessari

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