IEEE Trans Image Process - Real-time continuous image registration enabling ultraprecise 2-D motion tracking.

Tópicos

{ imag(1057) registr(996) error(939) }
{ algorithm(1844) comput(1787) effici(935) }
{ estim(2440) model(1874) function(577) }
{ motion(1329) object(1292) video(1091) }
{ imag(2830) propos(1344) filter(1198) }
{ imag(1947) propos(1133) code(1026) }
{ data(3963) clinic(1234) research(1004) }
{ take(945) account(800) differ(722) }
{ method(984) reconstruct(947) comput(926) }
{ implement(1333) system(1263) develop(1122) }
{ concept(1167) ontolog(924) domain(897) }
{ general(901) number(790) one(736) }
{ medic(1828) order(1363) alert(1069) }
{ use(1733) differ(960) four(931) }
{ system(1976) rule(880) can(841) }
{ measur(2081) correl(1212) valu(896) }
{ treatment(1704) effect(941) patient(846) }
{ extract(1171) text(1153) clinic(932) }
{ model(2341) predict(2261) use(1141) }
{ visual(1396) interact(850) tool(830) }
{ spatial(1525) area(1432) region(1030) }
{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ signal(2180) analysi(812) frequenc(800) }
{ high(1669) rate(1365) level(1280) }
{ cancer(2502) breast(956) screen(824) }
{ method(2212) result(1239) propos(1039) }
{ detect(2391) sensit(1101) algorithm(908) }
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{ can(774) often(719) complex(702) }
{ data(1737) use(1416) pattern(1282) }
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{ network(2748) neural(1063) input(814) }
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{ framework(1458) process(801) describ(734) }
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{ control(1307) perform(991) simul(935) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
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{ studi(1119) effect(1106) posit(819) }
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{ record(1888) medic(1808) patient(1693) }
{ health(3367) inform(1360) care(1135) }
{ model(3480) simul(1196) paramet(876) }
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{ research(1218) medic(880) student(794) }
{ patient(2837) hospit(1953) medic(668) }
{ model(2656) set(1616) predict(1553) }
{ data(2317) use(1299) case(1017) }
{ age(1611) year(1155) adult(843) }
{ cost(1906) reduc(1198) effect(832) }
{ group(2977) signific(1463) compar(1072) }
{ sampl(1606) size(1419) use(1276) }
{ gene(2352) biolog(1181) express(1162) }
{ data(3008) multipl(1320) sourc(1022) }
{ first(2504) two(1366) second(1323) }
{ intervent(3218) particip(2042) group(1664) }
{ activ(1138) subject(705) human(624) }
{ time(1939) patient(1703) rate(768) }
{ patient(1821) servic(1111) care(1106) }
{ use(2086) technolog(871) perceiv(783) }
{ can(981) present(881) function(850) }
{ analysi(2126) use(1163) compon(1037) }
{ health(1844) social(1437) communiti(874) }
{ structur(1116) can(940) graph(676) }
{ use(976) code(926) identifi(902) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ survey(1388) particip(1329) question(1065) }
{ decis(3086) make(1611) patient(1517) }
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{ activ(1452) weight(1219) physic(1104) }
{ method(1969) cluster(1462) data(1082) }

Resumo

In this paper, we present a novel continuous image registration method (CIRM), which yields near-zero bias and has high computational efficiency. It can be realized for real-time position estimation to enable ultraprecise 2-D motion tracking and motion control over a large motion range. As the two variables of the method are continuous in spatial domain, pixel-level image registration is unnecessary, thus the CIRM can continuously track the moving target according to the incoming target image. When applied to a specific target object, measurement resolution of the method is predicted according to the reference image model of the object along with the variance of the camera's overall image noise. The maximum permissible target speed is proportional to the permissible frame rate, which is limited by the required computational time. The precision, measurement resolution, and computational efficiency of the method are verified through computer simulations and experiments. Specifically, the CIRM is implemented and integrated with a visual sensing system. Near-zero bias, measurement resolution of 0.1 nm (0.0008 pixels), and measurement of one nanometer stepping are demonstrated.

Resumo Limpo

paper present novel continu imag registr method cirm yield nearzero bias high comput effici can realiz realtim posit estim enabl ultraprecis d motion track motion control larg motion rang two variabl method continu spatial domain pixellevel imag registr unnecessari thus cirm can continu track move target accord incom target imag appli specif target object measur resolut method predict accord refer imag model object along varianc camera overal imag nois maximum permiss target speed proport permiss frame rate limit requir comput time precis measur resolut comput effici method verifi comput simul experi specif cirm implement integr visual sens system nearzero bias measur resolut nm pixel measur one nanomet step demonstr

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