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An infrared image‐enhancement algorithm in simulated prosthetic vision: Enlarging working environment of future retinal prostheses
Background Most existing retinal prostheses contain a built‐in visible‐light camera module that captures images of the surrounding environment. Thus, in case of insufficient or lack of visible light, the camera fails to work, and the retinal prostheses enter a dormant or “OFF” state. A simple and ef...
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| Published in: | Artificial organs 2022-11, Vol.46 (11), p.2147-2158 |
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| cites | cdi_FETCH-LOGICAL-c3537-1e9b0be5b47af33387b1b7a4af8aed74f3a0e271e07aec1ae015f85107c3f3073 |
| container_end_page | 2158 |
| container_issue | 11 |
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| container_title | Artificial organs |
| container_volume | 46 |
| creator | Liang, Junling Li, Heng Chen, Jianpin Zhai, Zhenzhen Wang, Jing Di, Liqing Chai, Xinyu |
| description | Background
Most existing retinal prostheses contain a built‐in visible‐light camera module that captures images of the surrounding environment. Thus, in case of insufficient or lack of visible light, the camera fails to work, and the retinal prostheses enter a dormant or “OFF” state. A simple and effective solution is replacing the visible‐light camera with a dual‐mode camera. The present research aimed to achieve two main purposes: (1) to explore whether the dual‐mode camera in prosthesis recipients works under no visible‐light conditions and (2) to assess its performance.
Methods
To accomplish these aims, we enrolled subjects in a psychophysical experiment under simulated prosthetic vision conditions. We found that the subjects could complete some simple visual tasks, but the recognition performance under the infrared mode was significantly inferior to that under the visible‐light mode. These results inspired us to develop and propose a feasible infrared image‐enhancement processing algorithm. Another psychophysical experiment was performed to verify the feasibility of the algorithm.
Results
The obtained results showed that the average efficiency of the subjects completing visual tasks using our enhancement algorithm (0.014 ± 0.001) was significantly higher (p |
| doi_str_mv | 10.1111/aor.14247 |
| format | article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2646944463</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2729932440</sourcerecordid><originalsourceid>FETCH-LOGICAL-c3537-1e9b0be5b47af33387b1b7a4af8aed74f3a0e271e07aec1ae015f85107c3f3073</originalsourceid><addsrcrecordid>eNp1kc1KxDAQx4Moun4cfAEJeNFDNWnSZuttEb9AEETBW5l2J7vRNtGkXfHmwQfwGX0Ss656EJzLXH75zWT-hGxzdsBjHYLzB1ymUi2RAc_SLOFZIZfJgPGcJVku79bIegj3jDElWb5K1kQmlJK5GJC3kaXGag8ex9S0MMGP13e0U7A1tmg7Cs3EedNN24jRYNq-gS6ij96FboqdqenMBOPsET2xDfiJsRP67PzDvKOdGe_sl8dpqvuu90h9fGWh-VEEDJtkRUMTcOu7b5Db05Ob4_Pk8urs4nh0mdTzhROORcUqzCqpQAshhqrilQIJegg4VlILYJgqjkwB1hyQ8UwPM85ULbRgSmyQvYU3jn7qMXRla0KNTQMWXR_KNJd5IWU8TER3_6D3rvdx7UiptChEKiWL1P6CquNfgkddPvp4RP9SclbOoyljNOVXNJHd-Tb2VYvjX_IniwgcLoBn0-DL_6ZydHW9UH4CUlycIQ</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2729932440</pqid></control><display><type>article</type><title>An infrared image‐enhancement algorithm in simulated prosthetic vision: Enlarging working environment of future retinal prostheses</title><source>Wiley-Blackwell Read & Publish Collection</source><creator>Liang, Junling ; Li, Heng ; Chen, Jianpin ; Zhai, Zhenzhen ; Wang, Jing ; Di, Liqing ; Chai, Xinyu</creator><creatorcontrib>Liang, Junling ; Li, Heng ; Chen, Jianpin ; Zhai, Zhenzhen ; Wang, Jing ; Di, Liqing ; Chai, Xinyu</creatorcontrib><description>Background
Most existing retinal prostheses contain a built‐in visible‐light camera module that captures images of the surrounding environment. Thus, in case of insufficient or lack of visible light, the camera fails to work, and the retinal prostheses enter a dormant or “OFF” state. A simple and effective solution is replacing the visible‐light camera with a dual‐mode camera. The present research aimed to achieve two main purposes: (1) to explore whether the dual‐mode camera in prosthesis recipients works under no visible‐light conditions and (2) to assess its performance.
Methods
To accomplish these aims, we enrolled subjects in a psychophysical experiment under simulated prosthetic vision conditions. We found that the subjects could complete some simple visual tasks, but the recognition performance under the infrared mode was significantly inferior to that under the visible‐light mode. These results inspired us to develop and propose a feasible infrared image‐enhancement processing algorithm. Another psychophysical experiment was performed to verify the feasibility of the algorithm.
Results
The obtained results showed that the average efficiency of the subjects completing visual tasks using our enhancement algorithm (0.014 ± 0.001) was significantly higher (p < 0.001) than that of subjects using direct pixelization (0.007 ± 0.001).
Conclusions
We concluded that a dual‐mode camera could be a feasible solution to improving the performance of retinal prostheses as the camera adapted better to the specific existing ambient light conditions. Dual‐mode cameras combined with this infrared image‐enhancement algorithm could provide a promising direction for the design of future retinal prostheses.
This study found that subjects could complete some simple visual tasks, but the recognition performance under the infrared mode was significantly inferior to that under the visible‐light mode. This research developed and proposed a feasible infrared image‐enhancement processing algorithm. We concluded that a dual‐mode camera could be a feasible solution to improving the performance of retinal prostheses as the camera adapted better to the specific existing ambient light conditions.</description><identifier>ISSN: 0160-564X</identifier><identifier>EISSN: 1525-1594</identifier><identifier>DOI: 10.1111/aor.14247</identifier><identifier>PMID: 35377463</identifier><language>eng</language><publisher>United States: Wiley Subscription Services, Inc</publisher><subject>Algorithms ; Cameras ; dual‐mode camera ; Feasibility ; Image enhancement ; Infrared imagery ; infrared image‐processing algorithm ; Light ; Neural prostheses ; Prostheses ; Prosthetics ; Psychophysics ; Retina ; retinal prosthesis ; simulated prosthetic vision ; Vision ; Visual tasks ; Working conditions</subject><ispartof>Artificial organs, 2022-11, Vol.46 (11), p.2147-2158</ispartof><rights>2022 International Center for Artificial Organ and Transplantation (ICAOT) and Wiley Periodicals LLC.</rights><rights>2022 International Center for Artificial Organs and Transplantation and Wiley Periodicals LLC.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3537-1e9b0be5b47af33387b1b7a4af8aed74f3a0e271e07aec1ae015f85107c3f3073</citedby><cites>FETCH-LOGICAL-c3537-1e9b0be5b47af33387b1b7a4af8aed74f3a0e271e07aec1ae015f85107c3f3073</cites><orcidid>0000-0002-1303-8898</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35377463$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Liang, Junling</creatorcontrib><creatorcontrib>Li, Heng</creatorcontrib><creatorcontrib>Chen, Jianpin</creatorcontrib><creatorcontrib>Zhai, Zhenzhen</creatorcontrib><creatorcontrib>Wang, Jing</creatorcontrib><creatorcontrib>Di, Liqing</creatorcontrib><creatorcontrib>Chai, Xinyu</creatorcontrib><title>An infrared image‐enhancement algorithm in simulated prosthetic vision: Enlarging working environment of future retinal prostheses</title><title>Artificial organs</title><addtitle>Artif Organs</addtitle><description>Background
Most existing retinal prostheses contain a built‐in visible‐light camera module that captures images of the surrounding environment. Thus, in case of insufficient or lack of visible light, the camera fails to work, and the retinal prostheses enter a dormant or “OFF” state. A simple and effective solution is replacing the visible‐light camera with a dual‐mode camera. The present research aimed to achieve two main purposes: (1) to explore whether the dual‐mode camera in prosthesis recipients works under no visible‐light conditions and (2) to assess its performance.
Methods
To accomplish these aims, we enrolled subjects in a psychophysical experiment under simulated prosthetic vision conditions. We found that the subjects could complete some simple visual tasks, but the recognition performance under the infrared mode was significantly inferior to that under the visible‐light mode. These results inspired us to develop and propose a feasible infrared image‐enhancement processing algorithm. Another psychophysical experiment was performed to verify the feasibility of the algorithm.
Results
The obtained results showed that the average efficiency of the subjects completing visual tasks using our enhancement algorithm (0.014 ± 0.001) was significantly higher (p < 0.001) than that of subjects using direct pixelization (0.007 ± 0.001).
Conclusions
We concluded that a dual‐mode camera could be a feasible solution to improving the performance of retinal prostheses as the camera adapted better to the specific existing ambient light conditions. Dual‐mode cameras combined with this infrared image‐enhancement algorithm could provide a promising direction for the design of future retinal prostheses.
This study found that subjects could complete some simple visual tasks, but the recognition performance under the infrared mode was significantly inferior to that under the visible‐light mode. This research developed and proposed a feasible infrared image‐enhancement processing algorithm. We concluded that a dual‐mode camera could be a feasible solution to improving the performance of retinal prostheses as the camera adapted better to the specific existing ambient light conditions.</description><subject>Algorithms</subject><subject>Cameras</subject><subject>dual‐mode camera</subject><subject>Feasibility</subject><subject>Image enhancement</subject><subject>Infrared imagery</subject><subject>infrared image‐processing algorithm</subject><subject>Light</subject><subject>Neural prostheses</subject><subject>Prostheses</subject><subject>Prosthetics</subject><subject>Psychophysics</subject><subject>Retina</subject><subject>retinal prosthesis</subject><subject>simulated prosthetic vision</subject><subject>Vision</subject><subject>Visual tasks</subject><subject>Working conditions</subject><issn>0160-564X</issn><issn>1525-1594</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><recordid>eNp1kc1KxDAQx4Moun4cfAEJeNFDNWnSZuttEb9AEETBW5l2J7vRNtGkXfHmwQfwGX0Ss656EJzLXH75zWT-hGxzdsBjHYLzB1ymUi2RAc_SLOFZIZfJgPGcJVku79bIegj3jDElWb5K1kQmlJK5GJC3kaXGag8ex9S0MMGP13e0U7A1tmg7Cs3EedNN24jRYNq-gS6ij96FboqdqenMBOPsET2xDfiJsRP67PzDvKOdGe_sl8dpqvuu90h9fGWh-VEEDJtkRUMTcOu7b5Db05Ob4_Pk8urs4nh0mdTzhROORcUqzCqpQAshhqrilQIJegg4VlILYJgqjkwB1hyQ8UwPM85ULbRgSmyQvYU3jn7qMXRla0KNTQMWXR_KNJd5IWU8TER3_6D3rvdx7UiptChEKiWL1P6CquNfgkddPvp4RP9SclbOoyljNOVXNJHd-Tb2VYvjX_IniwgcLoBn0-DL_6ZydHW9UH4CUlycIQ</recordid><startdate>202211</startdate><enddate>202211</enddate><creator>Liang, Junling</creator><creator>Li, Heng</creator><creator>Chen, Jianpin</creator><creator>Zhai, Zhenzhen</creator><creator>Wang, Jing</creator><creator>Di, Liqing</creator><creator>Chai, Xinyu</creator><general>Wiley Subscription Services, Inc</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7QO</scope><scope>8FD</scope><scope>FR3</scope><scope>K9.</scope><scope>P64</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-1303-8898</orcidid></search><sort><creationdate>202211</creationdate><title>An infrared image‐enhancement algorithm in simulated prosthetic vision: Enlarging working environment of future retinal prostheses</title><author>Liang, Junling ; Li, Heng ; Chen, Jianpin ; Zhai, Zhenzhen ; Wang, Jing ; Di, Liqing ; Chai, Xinyu</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3537-1e9b0be5b47af33387b1b7a4af8aed74f3a0e271e07aec1ae015f85107c3f3073</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Algorithms</topic><topic>Cameras</topic><topic>dual‐mode camera</topic><topic>Feasibility</topic><topic>Image enhancement</topic><topic>Infrared imagery</topic><topic>infrared image‐processing algorithm</topic><topic>Light</topic><topic>Neural prostheses</topic><topic>Prostheses</topic><topic>Prosthetics</topic><topic>Psychophysics</topic><topic>Retina</topic><topic>retinal prosthesis</topic><topic>simulated prosthetic vision</topic><topic>Vision</topic><topic>Visual tasks</topic><topic>Working conditions</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liang, Junling</creatorcontrib><creatorcontrib>Li, Heng</creatorcontrib><creatorcontrib>Chen, Jianpin</creatorcontrib><creatorcontrib>Zhai, Zhenzhen</creatorcontrib><creatorcontrib>Wang, Jing</creatorcontrib><creatorcontrib>Di, Liqing</creatorcontrib><creatorcontrib>Chai, Xinyu</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>Biotechnology Research Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>Artificial organs</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liang, Junling</au><au>Li, Heng</au><au>Chen, Jianpin</au><au>Zhai, Zhenzhen</au><au>Wang, Jing</au><au>Di, Liqing</au><au>Chai, Xinyu</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An infrared image‐enhancement algorithm in simulated prosthetic vision: Enlarging working environment of future retinal prostheses</atitle><jtitle>Artificial organs</jtitle><addtitle>Artif Organs</addtitle><date>2022-11</date><risdate>2022</risdate><volume>46</volume><issue>11</issue><spage>2147</spage><epage>2158</epage><pages>2147-2158</pages><issn>0160-564X</issn><eissn>1525-1594</eissn><abstract>Background
Most existing retinal prostheses contain a built‐in visible‐light camera module that captures images of the surrounding environment. Thus, in case of insufficient or lack of visible light, the camera fails to work, and the retinal prostheses enter a dormant or “OFF” state. A simple and effective solution is replacing the visible‐light camera with a dual‐mode camera. The present research aimed to achieve two main purposes: (1) to explore whether the dual‐mode camera in prosthesis recipients works under no visible‐light conditions and (2) to assess its performance.
Methods
To accomplish these aims, we enrolled subjects in a psychophysical experiment under simulated prosthetic vision conditions. We found that the subjects could complete some simple visual tasks, but the recognition performance under the infrared mode was significantly inferior to that under the visible‐light mode. These results inspired us to develop and propose a feasible infrared image‐enhancement processing algorithm. Another psychophysical experiment was performed to verify the feasibility of the algorithm.
Results
The obtained results showed that the average efficiency of the subjects completing visual tasks using our enhancement algorithm (0.014 ± 0.001) was significantly higher (p < 0.001) than that of subjects using direct pixelization (0.007 ± 0.001).
Conclusions
We concluded that a dual‐mode camera could be a feasible solution to improving the performance of retinal prostheses as the camera adapted better to the specific existing ambient light conditions. Dual‐mode cameras combined with this infrared image‐enhancement algorithm could provide a promising direction for the design of future retinal prostheses.
This study found that subjects could complete some simple visual tasks, but the recognition performance under the infrared mode was significantly inferior to that under the visible‐light mode. This research developed and proposed a feasible infrared image‐enhancement processing algorithm. We concluded that a dual‐mode camera could be a feasible solution to improving the performance of retinal prostheses as the camera adapted better to the specific existing ambient light conditions.</abstract><cop>United States</cop><pub>Wiley Subscription Services, Inc</pub><pmid>35377463</pmid><doi>10.1111/aor.14247</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-1303-8898</orcidid></addata></record> |
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| subjects | Algorithms Cameras dual‐mode camera Feasibility Image enhancement Infrared imagery infrared image‐processing algorithm Light Neural prostheses Prostheses Prosthetics Psychophysics Retina retinal prosthesis simulated prosthetic vision Vision Visual tasks Working conditions |
| title | An infrared image‐enhancement algorithm in simulated prosthetic vision: Enlarging working environment of future retinal prostheses |
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