{"id":6370,"date":"2023-10-12T11:09:32","date_gmt":"2023-10-12T11:09:32","guid":{"rendered":"https:\/\/dailyai.com\/?p=6370"},"modified":"2023-10-12T11:09:32","modified_gmt":"2023-10-12T11:09:32","slug":"mindeye-retrieves-and-reconstructs-images-from-brain-scans","status":"publish","type":"post","link":"https:\/\/dailyai.com\/da\/2023\/10\/mindeye-retrieves-and-reconstructs-images-from-brain-scans\/","title":{"rendered":"MindEye henter og rekonstruerer billeder fra hjernescanninger"},"content":{"rendered":"

MedARC udvikler grundl\u00e6ggende AI-modeller til medicin, og deres seneste model, MindEye, kan fort\u00e6lle, hvad du har kigget p\u00e5.<\/strong><\/p>\n

MindEye er en fMRI-til-billed AI-model, der kan kortl\u00e6gge funktionel magnetisk resonans-billeddannelse (fMRI) af hjerneaktivitet til OpenAI's CLIP-billedrum.<\/p>\n

De fMRI-scanninger, de brugte, kom fra Natural Scenes Dataset (NSD). NSD best\u00e5r af fMRI-scanninger af hele hjernen i h\u00f8j opl\u00f8sning af 8 raske voksne fors\u00f8gspersoner, mens de kiggede p\u00e5 tusindvis af naturlige farvescener i l\u00f8bet af 30-40 scanningssessioner.<\/p>\n

MindEye kan analysere en fMRI-scanning og derefter hente det n\u00f8jagtige originale billede, som personen kiggede p\u00e5, fra listen over testbilleder. Selv hvis billederne er meget ens, f.eks. forskellige fotos af zebraer, identificerer MindEye stadig det rigtige billede i 93,2% af tilf\u00e6ldene.<\/p>\n

Den kan endda identificere lignende billeder fra en enorm billeddatabase med milliarder af billeder som LAION-5B-databasen.<\/p>\n

\"Billedgenkendelse
Billedidentifikation baseret p\u00e5 fMRI-hjerneskanninger. Kilde: MedARC<\/a><\/figcaption><\/figure>\n

N\u00e5r MindEye har oversat fMRI-scanningerne til CLIP-billedrummet, kan de f\u00f8res ind i en forudtr\u00e6net billedgenereringsmodel som Stable Diffusion eller lignende modeller. MedARC brugte Versatile Diffusion til at fors\u00f8ge at genskabe det oprindelige billede, som fors\u00f8gspersonen kiggede p\u00e5.<\/p>\n

MindEye f\u00e5r ikke denne del 100% rigtigt, men det er stadig virkelig imponerende. Her er deres resultater sammenlignet med resultaterne af tidligere unders\u00f8gelser.<\/p>\n

\"Billedrekonstruktion
Rekonstruktioner side om side med output fra andre fMRI-til-billedrekonstruktionsmodeller. Kilde: MedARC<\/a><\/figcaption><\/figure>\n

Potentiale og sp\u00f8rgsm\u00e5l<\/h2>\n

At sige, at MindEye kan vide, hvad du har kigget p\u00e5, er lidt af en forsimpling. For at f\u00e5 fMRI-dataene m\u00e5tte fors\u00f8gspersonerne tilbringe omkring 40 timer i en MR-maskine, og de billeder, modellen blev tr\u00e6net p\u00e5, var begr\u00e6nsede.<\/p>\n

Alligevel vil det v\u00e6re af stor interesse for hjerneforskere at kunne f\u00e5 et indblik i, hvordan en person opfatter visuel stimulation.<\/p>\n

Hvis man viser et billede til en patient, scanner deres hjerne og derefter genskaber deres opfattelse af billedet, kan det hj\u00e6lpe med den kliniske diagnose. Forskningsartiklen forklarede, at \"patienter, der lider af sv\u00e6r depression, kan producere rekonstruktioner, hvor f\u00f8lelsesm\u00e6ssigt negative aspekter af billeder er mere fremtr\u00e6dende.\"<\/p>\n

Forskningen kan ogs\u00e5 hj\u00e6lpe med at kommunikere med patienter, der lider af locked-in-syndrom (pseudokoma).<\/p>\n

For at f\u00e5 det fulde udbytte af disse anvendelser m\u00e5 vi vente p\u00e5 bedre hjerne-computer-gr\u00e6nseflader eller wearables, som ikke kr\u00e6ver, at man ligger i en MR-maskine i timevis.<\/p>\n

MedARC anerkender, at deres forskning ogs\u00e5 giver anledning til forsigtighed. \"Evnen til n\u00f8jagtigt at rekonstruere opfattelsen ud fra hjerneaktivitet rejser sp\u00f8rgsm\u00e5l om bredere samfundsm\u00e6ssige konsekvenser\", hedder det i deres forskningsartikel.<\/p>\n

Hvis der til sidst blev udviklet effektive ikke-invasive metoder, kunne man potentielt l\u00e6se en persons tanker og vide, hvad de kiggede p\u00e5.<\/p>\n

Fremskridt i brugen af AI i neurovidenskab<\/a> er fascinerende og vil uden tvivl hj\u00e6lpe klinikere inden for mental sundhed<\/a>. Men det rejser ogs\u00e5 en r\u00e6kke etiske og privatlivsrelaterede sp\u00f8rgsm\u00e5l om, hvordan vi forts\u00e6tter med at holde vores tanker for os selv.<\/p>","protected":false},"excerpt":{"rendered":"

MedARC udvikler grundl\u00e6ggende AI-modeller til medicin, og deres seneste model, MindEye, kan fort\u00e6lle, hvad du har kigget p\u00e5. MindEye er en fMRI-til-billed AI-model, der kan kortl\u00e6gge funktionel magnetisk resonans-billeddannelse (fMRI) af hjerneaktivitet til OpenAI's CLIP-billedrum. De fMRI-scanninger, de brugte, kom fra Natural Scenes Dataset (NSD). NSD best\u00e5r af fMRI-scanninger af hele hjernen i h\u00f8j opl\u00f8sning af 8 raske voksne fors\u00f8gspersoner, mens de kiggede p\u00e5 tusindvis af naturlige farvescener i l\u00f8bet af 30-40 scanningssessioner. MindEye kan analysere en fMRI-scanning og derefter hente det n\u00f8jagtige originale billede, som personen kiggede p\u00e5.<\/p>","protected":false},"author":6,"featured_media":6375,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[84],"tags":[203,107,165],"class_list":["post-6370","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-industry","tag-biotech","tag-generative-ai","tag-image-generation"],"yoast_head":"\nMindEye retrieves and reconstructs images from brain scans | DailyAI<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/dailyai.com\/da\/2023\/10\/mindeye-retrieves-and-reconstructs-images-from-brain-scans\/\" \/>\n<meta property=\"og:locale\" content=\"da_DK\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"MindEye retrieves and reconstructs images from brain scans | DailyAI\" \/>\n<meta property=\"og:description\" content=\"MedARC develops foundational AI models for medicine and their latest model, MindEye, can tell what you\u2019ve been looking at. 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