{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T20:49:00Z","timestamp":1743108540436,"version":"3.40.3"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031737473"},{"type":"electronic","value":"9783031737480"}],"license":[{"start":{"date-parts":[[2024,10,25]],"date-time":"2024-10-25T00:00:00Z","timestamp":1729814400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,10,25]],"date-time":"2024-10-25T00:00:00Z","timestamp":1729814400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025]]},"DOI":"10.1007\/978-3-031-73748-0_14","type":"book-chapter","created":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T19:02:33Z","timestamp":1729796553000},"page":"134-143","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Enhancing Retinal Disease Classification from\u00a0OCTA Images via\u00a0Active Learning Techniques"],"prefix":"10.1007","author":[{"given":"Jacob","family":"Thrasher","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Annahita","family":"Amireskandari","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Prashnna","family":"Gyawali","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,10,25]]},"reference":[{"unstructured":"\u201cEye conditions and diseases.\u201d National Eye Institute. https:\/\/www.nei.nih.gov\/learn-about-eye-health\/eye-conditions-and-diseases. Accessed 27 Jun 2024","key":"14_CR1"},{"unstructured":"Kim, L., et al.: \u201cChoroidal neovascularization: Oct angiography findings.\u201d Eyewiki. https:\/\/eyewiki.org\/Choroidal_Neovascularization:_OCT_Angiography_Findings. Accessed 27 Jun 2024","key":"14_CR2"},{"unstructured":"\u201cEye health statistics.\u201d American Academy of Opthalmology. https:\/\/www.aao.org\/newsroom\/eye-health-statistics. Accessed 27 Jun 2024","key":"14_CR3"},{"key":"14_CR4","doi-asserted-by":"publisher","first-page":"1492","DOI":"10.1016\/j.ophtha.2018.04.013","volume":"125","author":"TR Fricke","year":"2018","unstructured":"Fricke, T.R., et al.: Global prevalence of presbyopia and vision impairment from uncorrected presbyopia. Ophthalmology 125, 1492\u20131499 (2018)","journal-title":"Ophthalmology"},{"key":"14_CR5","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1038\/sj.neo.7900071","volume":"2","author":"JG Fujimoto","year":"2000","unstructured":"Fujimoto, J.G., Pitris, C., Boppart, S.A., Brezinski, M.E.: Optical coherence tomography: an emerging technology for biomedical imaging and optical biopsy. Neoplasia 2, 9\u201325 (2000)","journal-title":"Neoplasia"},{"key":"14_CR6","doi-asserted-by":"publisher","first-page":"1024","DOI":"10.1109\/TMI.2017.2780115","volume":"37","author":"R Rasti","year":"2018","unstructured":"Rasti, R., Rabbani, H., Mehridehnavi, A., Hajizadeh, F.: Macular oct classification using a multi-scale convolutional neural network ensemble. IEEE Trans. Med. Imaging 37, 1024\u20131034 (2018)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"14_CR7","first-page":"1","volume":"11","author":"D Wang","year":"2019","unstructured":"Wang, D., Wang, L.: On oct image classification via deep learning. IEEE Photonics J. 11, 1\u201314 (2019)","journal-title":"IEEE Photonics J."},{"key":"14_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1038\/s41586-023-06555-x","volume":"622","author":"Y Zhou","year":"2023","unstructured":"Zhou, Y., et al.: A foundation model for generalizable disease detection from retinal images. Nature 622, 1\u20138 (2023)","journal-title":"Nature"},{"key":"14_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.preteyeres.2017.11.003","volume":"64","author":"RF Spaide","year":"2018","unstructured":"Spaide, R.F., Fujimoto, J.G., Waheed, N.K., Sadda, S.R., Staurenghi, G.: Optical coherence tomography angiography. Prog. Retin. Eye Res. 64, 1\u201355 (2018)","journal-title":"Prog. Retin. Eye Res."},{"issue":"2","key":"14_CR10","doi-asserted-by":"publisher","first-page":"307","DOI":"10.1038\/s41433-019-0513-0","volume":"34","author":"DC Sousa","year":"2020","unstructured":"Sousa, D.C., et al.: Optical coherence tomography angiography study of the retinal vascular plexuses in type 1 diabetes without retinopathy. Eye 34(2), 307\u2013311 (2020)","journal-title":"Eye"},{"key":"14_CR11","doi-asserted-by":"publisher","first-page":"103092","DOI":"10.1016\/j.media.2024.103092","volume":"93","author":"M Li","year":"2024","unstructured":"Li, M., et al.: Octa-500: a retinal dataset for optical coherence tomography angiography study. Med. Image Anal. 93, 103092 (2024)","journal-title":"Med. Image Anal."},{"doi-asserted-by":"crossref","unstructured":"Cubuk, E.D.,\u00a0Zoph, B.,\u00a0Man\u00e9, D.,\u00a0Vasudevan, V., Le, Q.V.: Autoaugment: learning augmentation policies from data. CoRR arXiv:1805.09501 (2018)","key":"14_CR12","DOI":"10.1109\/CVPR.2019.00020"},{"unstructured":"Hendrycks, D.,\u00a0Mu, N., Cubuk, E.D.,\u00a0Zoph, B.,\u00a0Gilmer, J., Lakshminarayanan, B.: AugMix: a simple data processing method to improve robustness and uncertainty. arXiv:1912.02781 (2020)","key":"14_CR13"},{"doi-asserted-by":"crossref","unstructured":"Lewis, D.D., Gale, W.A.: A sequential algorithm for training text classifiers. CoRR arXiv:cmp-lg\/9407020 (1994)","key":"14_CR14","DOI":"10.1007\/978-1-4471-2099-5_1"},{"key":"14_CR15","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"413","DOI":"10.1007\/11871842_40","volume-title":"Machine Learning: ECML 2006","author":"D Roth","year":"2006","unstructured":"Roth, D., Small, K.: Margin-based active learning for structured output spaces. In: F\u00fcrnkranz, J., Scheffer, T., Spiliopoulou, M. (eds.) ECML 2006. LNCS (LNAI), vol. 4212, pp. 413\u2013424. Springer, Heidelberg (2006). https:\/\/doi.org\/10.1007\/11871842_40"},{"unstructured":"Monarch, R., Manning, C.D.: Human-in-the-Loop Machine Learning : Active Learning and Annotation for Human-centered AI. Shelter Island Manning (2021)","key":"14_CR16"},{"doi-asserted-by":"crossref","unstructured":"Holub, A., Perona, P., Burl, M.C.: Entropy-based active learning for object recognition. In: 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, pp. 1\u20138 (2008)","key":"14_CR17","DOI":"10.1109\/CVPRW.2008.4563068"},{"doi-asserted-by":"crossref","unstructured":"Szegedy, C.,\u00a0Vanhoucke, V.,\u00a0Ioffe, S.,\u00a0Shlens, J.,\u00a0Wojna, Z.: Rethinking the inception architecture for computer vision. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2015)","key":"14_CR18","DOI":"10.1109\/CVPR.2016.308"},{"unstructured":"Guo, C.,\u00a0Pleiss, G.,\u00a0Sun, Y., Weinberger, K.Q.: On calibration of modern neural networks. arXiv:1706.04599 (2017)","key":"14_CR19"},{"doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S., Sun, J.: Deep residual learning for image recognition. CoRR arXiv:1512.03385 (2015)","key":"14_CR20","DOI":"10.1109\/CVPR.2016.90"},{"unstructured":"Simonyan, K., Zisserman, A.: Very deep convolutional networks for large-scale image recognition. arXiv:1409.1556 (2014)","key":"14_CR21"}],"container-title":["Lecture Notes in Computer Science","Data Engineering in Medical Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-73748-0_14","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,24]],"date-time":"2024-10-24T19:05:14Z","timestamp":1729796714000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-73748-0_14"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10,25]]},"ISBN":["9783031737473","9783031737480"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-73748-0_14","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024,10,25]]},"assertion":[{"value":"25 October 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"DEMI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"MICCAI Workshop on Data Engineering in Medical Imaging","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Marrakesh","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Morocco","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 October 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"11 October 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"demi2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/demi-workshop.github.io\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}