Some content of this application is unavailable at the moment.
If this situation persists, please contact us atFeedback&Contact
1. (WO2017095014) CELL ABNORMALITY DIAGNOSING SYSTEM USING DNN LEARNING, AND DIAGNOSIS MANAGING METHOD OF SAME
Latest bibliographic data on file with the International Bureau

Pub. No.: WO/2017/095014 International Application No.: PCT/KR2016/011331
Publication Date: 08.06.2017 International Filing Date: 11.10.2016
IPC:
A61B 10/02 (2006.01) ,G06N 3/08 (2006.01) ,G06F 19/00 (2011.01)
A HUMAN NECESSITIES
61
MEDICAL OR VETERINARY SCIENCE; HYGIENE
B
DIAGNOSIS; SURGERY; IDENTIFICATION
10
Other methods or instruments for diagnosis, e.g. for vaccination diagnosis; Sex determination; Ovulation-period determination; Throat striking implements
02
Instruments for taking cell samples or for biopsy
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
N
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3
Computer systems based on biological models
02
using neural network models
08
Learning methods
G PHYSICS
06
COMPUTING; CALCULATING; COUNTING
F
ELECTRIC DIGITAL DATA PROCESSING
19
Digital computing or data processing equipment or methods, specially adapted for specific applications
Applicants:
임욱빈 IM, Wook-Bin [KR/KR]; KR
Inventors:
임욱빈 IM, Wook-Bin; KR
Agent:
김도형 KIM, Do-Hyoung; KR
Priority Data:
10-2015-016852430.11.2015KR
Title (EN) CELL ABNORMALITY DIAGNOSING SYSTEM USING DNN LEARNING, AND DIAGNOSIS MANAGING METHOD OF SAME
(FR) SYSTÈME DE DIAGNOSTIC D’ANOMALIE CELLULAIRE UTILISANT UN APPRENTISSAGE DNN, ET PROCÉDÉ DE GESTION DE DIAGNOSTIC DE CELUI-CI
(KO) DNN 학습을 이용한 세포이상 여부 진단시스템 및 그 진단관리 방법
Abstract:
(EN) The present invention is a technology that relates to a diagnosis system for diagnosing whether there is cell abnormality by using DNN learning, the system comprising: a cell diagnosis inspecting device disposed in a separate hospital for determining whether cells in a cell photograph to be inspected are normal cells or dangerous cells, on the basis of a neural network; and a neural network learning server connected to the internet and carrying out DNN learning on a neural network of the cell diagnosis inspecting device. In particular, the present invention relates to a technology in which: an upload of a cell photograph to be inspected and diagnosis results and data, which are acquired from a separate hospital, are provided to a neural network learning server; on the basis of this information, the learning server carries out DNN learning on a neural network model installed in the cell diagnosis inspecting device of the hospital, generates an upgraded neural network model, and provides a download of same again to the cell diagnosis inspecting device, so that the cell diagnosis inspecting device is able to form an upgrade of an optimized neural network model in a diagnosis environment of the hospital in which the device is installed.
(FR) La présente invention concerne une technologie qui est associée à un système de diagnostic pour diagnostiquer la présence ou non d’une anomalie cellulaire en utilisant l’apprentissage DNN, le système comprenant : un dispositif d’inspection de diagnostic cellulaire disposé dans un hôpital séparé pour déterminer si des cellules dans une photographie de cellules devant être inspectée sont des cellules normales ou des cellules dangereuses, sur la base d’un réseau neuronal ; et un serveur d’apprentissage de réseau neuronal connecté à Internet et conduisant un apprentissage DNN sur un réseau neuronal du dispositif d’inspection de diagnostic cellulaire. En particulier, la présente invention concerne une technologie dans laquelle : un transfert d’une photographie de cellules devant être inspectée et des résultats et des données de diagnostic, qui sont acquis depuis un hôpital séparé, sont fournis à un serveur d’apprentissage de réseau neuronal ; sur la base de ces informations, le serveur d’apprentissage effectue un apprentissage DNN sur un modèle de réseau neuronal installé dans le dispositif d’inspection de diagnostic cellulaire de l’hôpital, génère un modèle de réseau neuronal mis à niveau, et fournit un téléchargement de celui-ci à nouveau au dispositif d’inspection de diagnostic cellulaire, de sorte que le dispositif d’inspection de diagnostic cellulaire soit en mesure de former une mise à niveau d’un modèle de réseau neuronal optimisé dans un environnement de diagnostic de l’hôpital dans lequel le dispositif est installé.
(KO) 본 발명은 검사대상 세포사진에 대해 정상세포인지 아니면 위험세포인지 여부를 뉴럴 네트워크에 기초하여 판단하기 위한 개별 병원에 구비된 세포진단 검사장치 및 인터넷으로 연결되어 그 세포진단 검사장치의 뉴럴 네트워크에 대한 DNN 학습을 수행하는 뉴럴 네트워크 학습서버를 포함하여 구성되는 DNN 학습을 이용한 세포이상 여부 진단시스템에 관한 기술이다. 특히, 본 발명은 개별 병원에서 획득한 검사대상 세포사진 및 진단결과 데이터를 뉴럴 네트워크 학습서버에 업로드 제공하면 학습서버는 이러한 정보에 기초하여 그 병원의 세포진단 검사장치에 설치된 뉴럴 네트워크 모델에 대해 DNN 학습을 실행하여 업그레이드 뉴럴 네트워크 모델을 생성하고 이를 다시 해당 세포진단 검사장치에 다운로드 제공함으로써 세포진단 검사장치는 그 설치된 병원의 진단 환경에 최적화된 뉴럴 네트워크 모델을 업그레이드 형성할 수 있게 되는 기술에 관한 것이다.
front page image
Designated States: AE, AG, AL, AM, AO, AT, AU, AZ, BA, BB, BG, BH, BN, BR, BW, BY, BZ, CA, CH, CL, CN, CO, CR, CU, CZ, DE, DJ, DK, DM, DO, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, GT, HN, HR, HU, ID, IL, IN, IR, IS, JP, KE, KG, KN, KP, KW, KZ, LA, LC, LK, LR, LS, LU, LY, MA, MD, ME, MG, MK, MN, MW, MX, MY, MZ, NA, NG, NI, NO, NZ, OM, PA, PE, PG, PH, PL, PT, QA, RO, RS, RU, RW, SA, SC, SD, SE, SG, SK, SL, SM, ST, SV, SY, TH, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, ZA, ZM, ZW
African Regional Intellectual Property Organization (ARIPO) (BW, GH, GM, KE, LR, LS, MW, MZ, NA, RW, SD, SL, ST, SZ, TZ, UG, ZM, ZW)
Eurasian Patent Organization (AM, AZ, BY, KG, KZ, RU, TJ, TM)
European Patent Office (AL, AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HR, HU, IE, IS, IT, LT, LU, LV, MC, MK, MT, NL, NO, PL, PT, RO, RS, SE, SI, SK, SM, TR)
African Intellectual Property Organization (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, KM, ML, MR, NE, SN, TD, TG)
Publication Language: Korean (KO)
Filing Language: Korean (KO)
Also published as:
CN108366788EP3384856US20180350467