Comput. Biol. Med. - An efficient and secure medical image protection scheme based on chaotic maps.

Tópicos

{ imag(2830) propos(1344) filter(1198) }
{ system(1050) medic(1026) inform(1018) }
{ control(1307) perform(991) simul(935) }
{ import(1318) role(1303) understand(862) }
{ monitor(1329) mobil(1314) devic(1160) }
{ patient(2837) hospit(1953) medic(668) }
{ sampl(1606) size(1419) use(1276) }
{ high(1669) rate(1365) level(1280) }
{ method(2212) result(1239) propos(1039) }
{ imag(1947) propos(1133) code(1026) }
{ motion(1329) object(1292) video(1091) }
{ framework(1458) process(801) describ(734) }
{ chang(1828) time(1643) increas(1301) }
{ method(1557) propos(1049) approach(1037) }
{ perform(1367) use(1326) method(1137) }
{ data(2317) use(1299) case(1017) }
{ patient(1821) servic(1111) care(1106) }
{ can(981) present(881) function(850) }
{ process(1125) use(805) approach(778) }
{ can(774) often(719) complex(702) }
{ system(1976) rule(880) can(841) }
{ sequenc(1873) structur(1644) protein(1328) }
{ network(2748) neural(1063) input(814) }
{ patient(2315) diseas(1263) diabet(1191) }
{ data(1714) softwar(1251) tool(1186) }
{ research(1085) discuss(1038) issu(1018) }
{ model(2341) predict(2261) use(1141) }
{ studi(1119) effect(1106) posit(819) }
{ blood(1257) pressur(1144) flow(957) }
{ spatial(1525) area(1432) region(1030) }
{ record(1888) medic(1808) patient(1693) }
{ medic(1828) order(1363) alert(1069) }
{ first(2504) two(1366) second(1323) }
{ health(1844) social(1437) communiti(874) }
{ method(1969) cluster(1462) data(1082) }
{ model(3404) distribut(989) bayesian(671) }
{ data(1737) use(1416) pattern(1282) }
{ inform(2794) health(2639) internet(1427) }
{ measur(2081) correl(1212) valu(896) }
{ imag(1057) registr(996) error(939) }
{ bind(1733) structur(1185) ligand(1036) }
{ method(1219) similar(1157) match(930) }
{ featur(3375) classif(2383) classifi(1994) }
{ imag(2675) segment(2577) method(1081) }
{ take(945) account(800) differ(722) }
{ studi(2440) review(1878) systemat(933) }
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{ surgeri(1148) surgic(1085) robot(1054) }
{ problem(2511) optim(1539) algorithm(950) }
{ error(1145) method(1030) estim(1020) }
{ learn(2355) train(1041) set(1003) }
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{ clinic(1479) use(1117) guidelin(835) }
{ algorithm(1844) comput(1787) effici(935) }
{ extract(1171) text(1153) clinic(932) }
{ design(1359) user(1324) use(1319) }
{ model(2220) cell(1177) simul(1124) }
{ care(1570) inform(1187) nurs(1089) }
{ general(901) number(790) one(736) }
{ method(984) reconstruct(947) comput(926) }
{ search(2224) databas(1162) retriev(909) }
{ featur(1941) imag(1645) propos(1176) }
{ case(1353) use(1143) diagnosi(1136) }
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{ data(3963) clinic(1234) research(1004) }
{ studi(1410) differ(1259) use(1210) }
{ risk(3053) factor(974) diseas(938) }
{ perform(999) metric(946) measur(919) }
{ visual(1396) interact(850) tool(830) }
{ compound(1573) activ(1297) structur(1058) }
{ health(3367) inform(1360) care(1135) }
{ model(3480) simul(1196) paramet(876) }
{ ehr(2073) health(1662) electron(1139) }
{ state(1844) use(1261) util(961) }
{ research(1218) medic(880) student(794) }
{ model(2656) set(1616) predict(1553) }
{ age(1611) year(1155) adult(843) }
{ signal(2180) analysi(812) frequenc(800) }
{ cost(1906) reduc(1198) effect(832) }
{ 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) }
{ structur(1116) can(940) graph(676) }
{ cancer(2502) breast(956) screen(824) }
{ use(976) code(926) identifi(902) }
{ use(1733) differ(960) four(931) }
{ drug(1928) target(777) effect(648) }
{ result(1111) use(1088) new(759) }
{ implement(1333) system(1263) develop(1122) }
{ survey(1388) particip(1329) question(1065) }
{ estim(2440) model(1874) function(577) }
{ decis(3086) make(1611) patient(1517) }
{ activ(1452) weight(1219) physic(1104) }
{ detect(2391) sensit(1101) algorithm(908) }

Resumo

Recently, the increasing demand for telemedicine services has raised interest in the use of medical image protection technology. Conventional block ciphers are poorly suited to image protection due to the size of image data and increasing demand for real-time teleradiology and other online telehealth applications. To meet this challenge, this paper presents a novel chaos-based medical image encryption scheme. To address the efficiency problem encountered by many existing permutation-substitution type image ciphers, the proposed scheme introduces a substitution mechanism in the permutation process through a bit-level shuffling algorithm. As the pixel value mixing effect is contributed by both the improved permutation process and the original substitution process, the same level of security can be achieved in a fewer number of overall rounds. The results indicate that the proposed approach provides an efficient method for real-time secure medical image transmission over public networks.

Resumo Limpo

recent increas demand telemedicin servic rais interest use medic imag protect technolog convent block cipher poor suit imag protect due size imag data increas demand realtim teleradiolog onlin telehealth applic meet challeng paper present novel chaosbas medic imag encrypt scheme address effici problem encount mani exist permutationsubstitut type imag cipher propos scheme introduc substitut mechan permut process bitlevel shuffl algorithm pixel valu mix effect contribut improv permut process origin substitut process level secur can achiev fewer number overal round result indic propos approach provid effici method realtim secur medic imag transmiss public network

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