Algoritm segmentacii OKT izobrazhenij makuly dlya analiza pacientov s vozrastnoj makulyarnoj degeneraciej
نویسندگان
چکیده
Odnoj iz osnovnyh prichin slepoty i slabovideniya u lic starshego trudosposobnogo vozrasta yavlyaetsya vozrastnaya makulyarnaya degeneraciya (VMD), dlya diagnostiki kotoroj krajne vazhny rezul'taty opticheskoj kogerentnoj tomografii (OKT). Sozdanie rekomendatel'noj sistemy analiza OKT-snimkov pozvolit sokratit' vremya na obrabotku vizual'noj informacii snizit' veroyatnost' oshibok v processe raboty vracha. Cel'yu issledovaniya bylo razrabotat' algoritm segmentacii dannyh OKT makuly pacientov s VMD, pozvolyayushchij, osnovyvayas' forme vydelennyh patologij, korrektno predskazyvat' stadiyu razvitiya VMD. Razrabotana programma yazyke programmirovaniya Python ispol'zovaniem biblioteki PyTorch TensorFlow. Kachestvo programmy ocenili OKT-izobrazheniyah 51 pacienta VMD rannej, promezhutochnoj pozdnej stadij. Razrabotan OKT-snimkov, osnovannyj svertochnoj nejronnoj seti. V kachestve arhitektury seti byla vybrana set' UNet. Nejronnaya obuchena OKT-snimkah 125 (197 glaz). Avtorskij prodemonstriroval 98,1% verno segmentirovannyh oblastej OKT-snimkah, naibolee vazhnyh opredeleniya stadii Vzveshennaya chuvstvitel'nost' specifichnost' klassifikatora stadij sostavili sootvetstvenno 83,8% 84,9%. Razrabotannyj perspektiven sistemy, realizuyushchej klassifikaciyu osnove dannyh, sposobstvuyushchej prinyatiyu reshenij o taktike lecheniya pacientov.
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ژورنال
عنوان ژورنال: Vestnik RGMU
سال: 2022
ISSN: ['2070-7320', '2070-7339']
DOI: https://doi.org/10.24075/vrgmu.2022.062