{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T11:09:26Z","timestamp":1788952166843,"version":"build-2803163510"},"reference-count":43,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T00:00:00Z","timestamp":1788912000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Biomimetics"],"abstract":"<jats:p>Images from high-resolution cameras are mapped onto a sparse pattern of low spatial resolution and intensity in the retina, which limits visual perception in retinal prosthetic vision. When the entire scene is converted into phosphenes, it may allow unnecessary background information to be retained and may cause visual clutter, which may make it hard for prosthetic vision users to interpret the scene. In order to tackle this issue, this paper presents a context-, depth-, and user-preference-aware method for selecting the objects of interest in the generation of phosphene images. The proposed method does not show all the objects equally but learns to sort the objects according to their relevance to prosthetic vision. Manual annotation of a subset of COCO images was conducted where the most salient object was selected based on environment type, scene type, user mode, safety, navigation relevance, task importance, and distance. All of the candidate objects are described by full-scene visual features, object-crop features, handcrafted priority features, context embeddings, and monocular depth features. To predict object-level importance scores and identify the Top-1 and Top-4 important objects in unseen scenes, a hybrid deep learning model combining twin ResNet-18 backbones for scene and object feature extraction with embedding-based context encoding was trained. Priority maps and phosphene images were then created using the selected object masks and were depth-weighted. Two types of phosphene representations were also produced: Canny-edge-based and direct full images. The proposed framework is designed to suppress irrelevant background areas and improve important and closer objects in order to obtain a simplified and informative prosthetic-vision representation of the scene. The experimental evaluation, including Top-1 accuracy, Top-3 accuracy, mean reciprocal rank (MRR), and visual comparison, demonstrates the effectiveness of the proposed framework, achieving a Top-1 accuracy of 90.12%, a Top-3 accuracy of 97.45%, and an MRR of 0.9368. Furthermore, the proposed Canny-priority phosphene representation achieved an average human-participant recognition accuracy of approximately 86%. The proposed method offers a user-adaptive strategy for selecting and visualizing the information of a scene under the severe constraint of the bandwidth of retinal prosthetic vision.<\/jats:p>","DOI":"10.3390\/biomimetics11090649","type":"journal-article","created":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T09:24:02Z","timestamp":1788945842000},"page":"649","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Intelligent Visual Prioritization for Retinal Prostheses via Context-Aware Object Ranking and Depth-Aware Phosphene Generation"],"prefix":"10.3390","volume":"11","author":[{"given":"Xinwei","family":"Li","sequence":"first","affiliation":[{"name":"Department of Mathematics and Information Engineering, Liaocheng University Dongchang College, Liaocheng 252000, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8044-6779","authenticated-orcid":false,"given":"Irshad","family":"Khalil","sequence":"additional","affiliation":[{"name":"Department of Smart Security, Gachon University, Seongnam-si 13120, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-4678-3161","authenticated-orcid":false,"given":"Faisal","family":"Rahman","sequence":"additional","affiliation":[{"name":"Department of Information Technology Management, Southwest Baptist University, Bolivar, MO 65613, USA"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"investigation","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"project-administration","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6682-7049","authenticated-orcid":false,"given":"Muhammad Nawaz","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Smart Security, Gachon University, Seongnam-si 13120, Republic of Korea"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"validation","vocabulary":"credit"},{"role":"software","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,9]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1405","DOI":"10.1007\/s11136-011-0061-y","article-title":"The impact of low vision on activities of daily living, symptoms of depression, feelings of anxiety and social support in community-living older adults seeking vision rehabilitation services","volume":"21","author":"Kempen","year":"2012","journal-title":"Qual. Life Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"2377","DOI":"10.1016\/j.ophtha.2013.05.025","article-title":"Global prevalence of vision impairment and blindness: Magnitude and temporal trends, 1990\u20132010","volume":"120","author":"Stevens","year":"2013","journal-title":"Ophthalmology"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1191","DOI":"10.1126\/science.abd7435","article-title":"Shape perception via a high-channel-count neuroprosthesis in monkey visual cortex","volume":"370","author":"Chen","year":"2020","journal-title":"Science"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Fern\u00e1ndez, E., Alfaro, A., and Gonz\u00e1lez-L\u00f3pez, P. (2020). Toward long-term communication with the brain in the blind by intracortical stimulation: Challenges and future prospects. Front. Neurosci., 14.","DOI":"10.3389\/fnins.2020.00681"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1091","DOI":"10.1016\/S0042-6989(03)00013-0","article-title":"Position, size and luminosity of phosphenes generated by direct optic nerve stimulation","volume":"43","author":"Delbeke","year":"2003","journal-title":"Vis. Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"20130077","DOI":"10.1098\/rspb.2013.0077","article-title":"Artificial vision with wirelessly powered subretinal electronic implant Alpha-IMS","volume":"280","author":"Stingl","year":"2013","journal-title":"Proc. R. Soc. B"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"779","DOI":"10.1016\/j.ophtha.2011.09.028","article-title":"Interim results from the international trial of Second Sight\u2019s visual prosthesis","volume":"119","author":"Humayun","year":"2012","journal-title":"Ophthalmology"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1080\/02713683.2016.1270326","article-title":"Advances in retinal prosthetic research: A systematic review of engineering and clinical characteristics of current prosthetic initiatives","volume":"42","author":"Cheng","year":"2017","journal-title":"Curr. Eye Res."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Zrenner, E., Wilke, R., Bartz-Schmidt, K.U., Gekeler, F., Besch, D., Benav, H., Bruckmann, A., Porubska, K., Kusnyerik, A., and Sachs, H. (2009). Subretinal microelectrode arrays allow blind retinitis pigmentosa patients to recognize letters and combine them to words. Proceedings of the 2nd International Conference on Biomedical Engineering and Informatics, Tianjin, China, IEEE.","DOI":"10.1109\/BMEI.2009.5305315"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Ayton, L.N., Blamey, P.J., Guymer, R.H., Luu, C.D., Nayagam, D.A.X., Sinclair, N.C., Shivdasani, M.N., Yeoh, J., McCombe, M.F., and Briggs, R.J. (2014). First-in-human trial of a novel suprachoroidal retinal prosthesis. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0115239"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"479","DOI":"10.1113\/jphysiol.1968.sp008519","article-title":"The sensations produced by electrical stimulation of the visual cortex","volume":"196","author":"Brindley","year":"1968","journal-title":"J. Physiol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"4948","DOI":"10.1167\/iovs.15-18991","article-title":"The appearance of phosphenes elicited using a suprachoroidal retinal prosthesis","volume":"57","author":"Sinclair","year":"2016","journal-title":"Investig. Ophthalmol. Vis. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"S92","DOI":"10.1088\/1741-2560\/4\/1\/S11","article-title":"Real and virtual mobility performance in simulated prosthetic vision","volume":"4","author":"Dagnelie","year":"2007","journal-title":"J. Neural Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"035008","DOI":"10.1088\/1741-2560\/6\/3\/035008","article-title":"Detection, eye\u2013hand coordination and virtual mobility performance in simulated vision for a cortical visual prosthesis device","volume":"6","author":"Srivastava","year":"2009","journal-title":"J. Neural Eng."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3283","DOI":"10.1007\/s00417-023-06052-x","article-title":"Artificial intelligence in retinal disease: Clinical application, challenges, and future directions","volume":"261","author":"Sen","year":"2023","journal-title":"Graefe\u2019s Arch. Clin. Exp. Ophthalmol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"511","DOI":"10.1186\/s12951-022-01717-x","article-title":"Nanoparticles-mediated CRISPR-Cas9 gene therapy in inherited retinal diseases: Applications, challenges, and emerging opportunities","volume":"20","author":"Chien","year":"2022","journal-title":"J. Nanobiotechnology"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Mehmood, A., Ko, J., Kim, H., and Kim, J. (2024). Optimizing image enhancement: Feature engineering for improved classification in AI-assisted artificial retinas. Sensors, 24.","DOI":"10.3390\/s24092678"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"3198342","DOI":"10.1155\/2018\/3198342","article-title":"Optimization of visual information presentation for visual prosthesis","volume":"2018","author":"Guo","year":"2018","journal-title":"Int. J. Biomed. Imaging"},{"key":"ref_19","first-page":"E102","article-title":"Simulated prosthetic vision: The benefits of computer-based object recognition and localization","volume":"39","author":"Guivarch","year":"2015","journal-title":"Artif. Organs"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.artmed.2017.11.001","article-title":"Image processing strategies based on saliency segmentation for object recognition under simulated prosthetic vision","volume":"84","author":"Li","year":"2018","journal-title":"Artif. Intell. Med."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"1241","DOI":"10.1167\/iovs.05-0157","article-title":"Paragraph text reading using a pixelized prosthetic vision simulator: Parameter dependence and task learning in free-viewing conditions","volume":"47","author":"Dagnelie","year":"2006","journal-title":"Investig. Ophthalmol. Vis. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"McKone, E., Robbins, R.A., He, X., and Barnes, N. (2018). Caricaturing faces to improve identity recognition in low vision simulations: How effective is current-generation automatic assignment of landmark points?. PLoS ONE, 13.","DOI":"10.1371\/journal.pone.0204361"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"852","DOI":"10.1111\/aor.12868","article-title":"Simplification of visual rendering in simulated prosthetic vision facilitates navigation","volume":"41","author":"Vergnieux","year":"2017","journal-title":"Artif. Organs"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Perez-Yus, A., Bermudez-Cameo, J., Lopez-Nicolas, G., and Guerrero, J.J. (2017). Depth and motion cues with phosphene patterns for prosthetic vision. Proceedings of the IEEE International Conference on Computer Vision Workshops (ICCVW), Venice, Italy, IEEE.","DOI":"10.1109\/ICCVW.2017.179"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Sanchez-Garcia, M., Martinez-Cantin, R., and Guerrero, J.J. (2020). Semantic and structural image segmentation for prosthetic vision. PLoS ONE, 15.","DOI":"10.1371\/journal.pone.0227677"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Han, N., Srivastava, S., Xu, A., Klein, D., and Beyeler, M. (2021). Deep learning-based scene simplification for bionic vision. Proceedings of the Augmented Humans International Conference, Rovaniemi, Finland, ACM.","DOI":"10.1145\/3458709.3458982"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Dai, J., He, K., and Sun, J. (2016). Instance-aware semantic segmentation via multi-task network cascades. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Las Vegas, NV, USA, IEEE.","DOI":"10.1109\/CVPR.2016.343"},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Nejad, A., K\u00fc\u00e7\u00fcko\u011flu, B., de Ruyter van Steveninck, J., Bedrossian, S., Heutink, J., de Haan, G.A., Cornelissen, F.W., and van Gerven, M. (2025). Point-SPV: End-to-end enhancement of object recognition in simulated prosthetic vision using synthetic viewing points. Front. Hum. Neurosci., 19.","DOI":"10.3389\/fnhum.2025.1549698"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"McCarthy, C., Feng, D., and Barnes, N. (2013). Augmenting intensity to enhance scene structure in prosthetic vision. Proceedings of the IEEE International Conference on Multimedia and Expo Workshops (ICMEW), San Jose, CA, USA, IEEE.","DOI":"10.1109\/ICMEW.2013.6618430"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"016003","DOI":"10.1088\/1741-2560\/12\/1\/016003","article-title":"Mobility and low contrast trip hazard avoidance using augmented depth","volume":"12","author":"McCarthy","year":"2015","journal-title":"J. Neural Eng."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Lin, T.-Y., Maire, M., Belongie, S., Hays, J., Perona, P., Ramanan, D., Doll\u00e1r, P., and Zitnick, C.L. (2014). Microsoft COCO: Common objects in context. Proceedings of the European Conference on Computer Vision (ECCV), Zurich, Switzerland, Springer.","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Kirillov, A., Mintun, E., Ravi, N., Mao, H., Rolland, C., Gustafson, L., Xiao, T., Whitehead, S., Berg, A.C., and Lo, W.-Y. (2023). Segment Anything. Proceedings of the IEEE\/CVF International Conference on Computer Vision (ICCV), Paris, France, IEEE.","DOI":"10.1109\/ICCV51070.2023.00371"},{"key":"ref_33","unstructured":"Birkl, R., Wofk, D., and M\u00fcller, M. (2023). MiDaS v3.1\u2014A model zoo for robust monocular relative depth estimation. arXiv."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Vurro, M., Crowell, A.M., and Pezaris, J.S. (2014). Simulation of thalamic prosthetic vision: Reading accuracy, speed, and acuity in sighted humans. Front. Hum. Neurosci., 8.","DOI":"10.3389\/fnhum.2014.00816"},{"key":"ref_35","first-page":"1","article-title":"A real-time image optimization strategy based on global saliency detection for artificial retinal prostheses","volume":"415","author":"Li","year":"2017","journal-title":"Inf. Sci."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Xu, Z., Xu, B., and Wu, G. (2017). Canny edge detection based on OpenCV. Proceedings of the 13th IEEE International Conference on Electronic Measurement & Instruments (ICEMI), Yangzhou, China, IEEE.","DOI":"10.1109\/ICEMI.2017.8265710"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Nanduri, D., Humayun, M.S., Greenberg, R.J., McMahon, M.J., and Weiland, J.D. (2008). Retinal prosthesis phosphene shape analysis. Proceedings of the 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Vancouver, BC, Canada, IEEE.","DOI":"10.1109\/IEMBS.2008.4649524"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"2573","DOI":"10.1016\/S0042-6989(03)00457-7","article-title":"Visual perception in a blind subject with a chronic microelectronic retinal prosthesis","volume":"43","author":"Humayun","year":"2003","journal-title":"Vis. Res."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"512","DOI":"10.1016\/j.ins.2014.02.136","article-title":"Moving object recognition under simulated prosthetic vision using background-subtraction-based image processing strategies","volume":"277","author":"Wang","year":"2014","journal-title":"Inf. Sci."},{"key":"ref_40","first-page":"3493826","article-title":"Extraspectral imaging for improving the perceived information presented in retinal prosthesis","volume":"2018","author":"Degenaar","year":"2018","journal-title":"J. Healthc. Eng."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Biederman, I. (2017). On the semantics of a glance at a scene. Perceptual Organization, Routledge.","DOI":"10.4324\/9781315512372-8"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1994","DOI":"10.1109\/LRA.2017.2715400","article-title":"Single-view and multi-view depth fusion","volume":"2","author":"Concha","year":"2017","journal-title":"IEEE Robot. Autom. Lett."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"051003","DOI":"10.1088\/1741-2552\/aa795e","article-title":"Learning to see again: Biological constraints on cortical plasticity and the implications for sight restoration technologies","volume":"14","author":"Beyeler","year":"2017","journal-title":"J. Neural Eng."}],"container-title":["Biomimetics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2313-7673\/11\/9\/649\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,9]],"date-time":"2026-09-09T10:13:15Z","timestamp":1788948795000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2313-7673\/11\/9\/649"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9,9]]},"references-count":43,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2026,9]]}},"alternative-id":["biomimetics11090649"],"URL":"https:\/\/doi.org\/10.3390\/biomimetics11090649","relation":{},"ISSN":["2313-7673"],"issn-type":[{"value":"2313-7673","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,9,9]]}}}