WO2022269352 - METHODS AND SYSTEMS FOR ESTIMATING VISUAL FIELD SENSITIVITIES FROM RETINAL OPTICAL TEXTURE ANALYSIS (ROTA) MAPS
National phase entry:
Publication Number
WO/2022/269352
Publication Date
29.12.2022
International Application No.
PCT/IB2022/000351
International Filing Date
22.06.2022
Title **
[English]
METHODS AND SYSTEMS FOR ESTIMATING VISUAL FIELD SENSITIVITIES FROM RETINAL OPTICAL TEXTURE ANALYSIS (ROTA) MAPS
[French]
PROCÉDÉS ET SYSTÈMES D'ESTIMATION DE SENSIBILITÉS DE CHAMP VISUEL À PARTIR DE CARTES D'ANALYSE DE TEXTURE OPTIQUE RÉTINIENNE (ROTA)
Applicants **
AIROTA DIAGNOSTICS LIMITED
Room 622, 6/f, Building 17w
17 Science Park West Ave., Hong Kong Science Park
Pak Shek Kok, Nt, Hong Kong, CN
Inventors
LEUNG, Kai-shun, Christopher
Room 622, 6/f, Building 17w
17 Science Park West Ave., Hong Kong Science Park
Pak Shekkok, Nt, Hong Kong, CN
LAM, Ka-ngai, Alexander
Room 622, 6/f, Building 17w
17 Science Park West Ave., Hong Kong Science Park
Pak Shekkok, Nt, Hong Kong, CN
Priority Data
63/213,469
22.06.2021
US
17/845,852
21.06.2022
US
Application details
| Total Number of Claims/PCT | * |
| Number of Independent Claims | * |
| Number of Priorities | * |
| Number of Multi-Dependent Claims | * |
| Number of Drawings | * |
| Pages for Publication | * |
| Number of Pages with Drawings | * |
| Pages of Specification | * |
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International Searching Authority |
EPO
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| Applicant's Legal Status |
Legal Entity
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| * | |
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| Entry into National Phase under |
Chapter I
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| Translation |
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Recalculate
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Quotation for National Phase entry
| Country | Stages | Total | |
|---|---|---|---|
| China | Filing | 1748 | |
| EPO | Filing, Examination | 8330 | |
| Japan | Filing | 591 | |
| South Korea | Filing | 607 | |
| USA | Filing, Examination | 3310 |
Total: 14586 USD
The term for entry into the National Phase has expired. This quotation is for informational purposes only
Abstract[English]
Disclosed techniques evaluate the visual field of a patient's eye using deep learning techniques. A computer system obtains a plurality of cross-sectional scan images of a retina captured by an optical coherence tomography (OCT) device. The retina has an inner retinal layer. A retinal optical texture analysis (ROTA) map of the inner retinal layer is generated from the plurality of cross-sectional scan images. The ROTA map includes a plurality of pixels, and each pixel of the ROTA map corresponds to a respective optical texture signature value S providing information about tissue composition and optical density of the inner retinal layer at a respective retinal location. The computer system applies a machine learning model to process the ROTA map of the inner retinal layer to determine visual field sensitivity of the retina.[French]
L'invention divulgue des techniques permettant d'évaluer le champ visuel de l'œil d'un patient au moyen de techniques d'apprentissage profond. Un système informatique obtient une pluralité d'images de balayage en coupe transversale d'une rétine capturées par un dispositif de tomographie par cohérence optique (OCT). La rétine présente une couche rétinienne interne. Une carte d'analyse de texture optique rétinienne (ROTA) de la couche rétinienne interne est générée à partir de la pluralité d'images de balayage en coupe transversale. La carte ROTA comprend une pluralité de pixels, et chaque pixel de la carte ROTA correspond à une valeur de signature de texture optique respective S fournissant des informations concernant la composition tissulaire et la densité optique de la couche rétinienne interne à un emplacement rétinien respectif. Le système informatique applique un modèle d'apprentissage machine pour traiter la carte ROTA de la couche rétinienne interne pour déterminer la sensibilité de champ visuel de la rétine.