{"id":787246,"date":"2021-10-22T08:44:30","date_gmt":"2021-10-22T15:44:30","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-project&p=787246"},"modified":"2023-10-26T23:55:47","modified_gmt":"2023-10-27T06:55:47","slug":"smartkc-a-smartphone-based-corneal-topographer","status":"publish","type":"msr-project","link":"https:\/\/www.microsoft.com\/en-us\/research\/project\/smartkc-a-smartphone-based-corneal-topographer\/","title":{"rendered":"SmartKC: A Smartphone-based Corneal Topographer"},"content":{"rendered":"
\n\t
\n\t\t
\n\t\t\t\"Low-cost\t\t<\/div>\n\t\t\n\t\t
\n\t\t\t\n\t\t\t
\n\t\t\t\t\n\t\t\t\t
\n\t\t\t\t\t\n\t\t\t\t\t
\n\t\t\t\t\t\t
\n\t\t\t\t\t\t\t\n\t\t\t\t\t\t\t\n\n

SmartKC: A Smartphone-based Corneal Topographer<\/h1>\n\n\n\n

<\/p>\n\n\t\t\t\t\t\t<\/div>\n\t\t\t\t\t<\/div>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t<\/div>\n\t<\/div>\n<\/section>\n\n\n\n\n\n

Keratoconus is a severe eye disease affecting the cornea (the clear, dome-shaped outer surface of the eye), causing it to become thin and develop a conical bulge. If not treated in time, keratoconus can lead to near-complete blindness. <\/p>\n\n\n\n

The diagnosis of keratoconus requires sophisticated ophthalmic corneal topographers which are non-portable and very expensive. This makes early detection of keratoconus inaccessible to large populations in low- and middle-income countries, making it a leading cause for partial\/complete blindness among such populations.<\/p>\n\n\n\n

We have developed SmartKC, a low-cost, smartphone-based keratoconus diagnosis system comprising of a 3D-printed placido’s disc attachment, a LED light strip, and a smartphone app to capture the reflection of the placido rings on the cornea. An image processing pipeline analyzes the corneal image and uses the smartphone’s camera parameters, the placido rings’ 3D location, the pixel location of the reflected placido rings and the setup’s working distance to construct the corneal surface, via the Arc-Step method and Zernike polynomials based surface fitting.<\/p>\n\n\n\n

In a pilot clinical study in collaboration with the Sankara Eye Hospital in Bengaluru we found that SmartKC achieves a sensitivity of 87.8% and a specificity of 80.4%. <\/p>\n\n\n\n

We are now working towards deploying SmartKC at health-centers across India for mass screening of Keratoconus.<\/p>\n\n\n\n

Arxiv link: [2111.01354v2] SmartKC: Smartphone-based Corneal Topographer for Keratoconus Detection (arxiv.org) (opens in new tab)<\/span><\/a><\/p>\n\n\n\n

PDF:  (opens in new tab)<\/span><\/a>SmartKC: Smartphone-based Corneal Topographer for Keratoconus Detection (arxiv.org) (opens in new tab)<\/span><\/a><\/p>\n\n\n\n

Code: https:\/\/github.com\/microsoft\/SmartKC-A-Smartphone-based-Corneal-Topographer (opens in new tab)<\/span><\/a><\/p>\n\n\n","protected":false},"excerpt":{"rendered":"

Keratoconus is a severe eye disease affecting the cornea (the clear, dome-shaped outer surface of the eye), causing it to become thin and develop a conical bulge. If not treated in time, keratoconus can lead to near-complete blindness. The diagnosis of keratoconus requires sophisticated ophthalmic corneal topographers which are non-portable and very expensive. This makes […]<\/p>\n","protected":false},"featured_media":787249,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"research-area":[13562,13554,13553,13568],"msr-locale":[268875],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-787246","msr-project","type-msr-project","status-publish","has-post-thumbnail","hentry","msr-research-area-computer-vision","msr-research-area-human-computer-interaction","msr-research-area-medical-health-genomics","msr-research-area-technology-for-emerging-markets","msr-locale-en_us","msr-archive-status-active"],"msr_project_start":"","related-publications":[787486,857817],"related-downloads":[],"related-videos":[],"related-groups":[],"related-events":[],"related-opportunities":[],"related-posts":[],"related-articles":[],"tab-content":[],"slides":[],"related-researchers":[{"type":"guest","display_name":"Siddhartha Gairola","user_id":787258,"people_section":"Section name 0","alias":""},{"type":"user_nicename","display_name":"Mohit Jain","user_id":38769,"people_section":"Section name 0","alias":"mohja"},{"type":"user_nicename","display_name":"Nipun Kwatra","user_id":37634,"people_section":"Section name 0","alias":"nkwatra"}],"msr_research_lab":[199562],"msr_impact_theme":[],"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/787246"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-project"}],"version-history":[{"count":8,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/787246\/revisions"}],"predecessor-version":[{"id":986751,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/787246\/revisions\/986751"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media\/787249"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=787246"}],"wp:term":[{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=787246"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=787246"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=787246"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=787246"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}