دورية أكاديمية
Tensor-based Feature Extraction for Pupil Recognition in Cataract Surgery.
| العنوان: | Tensor-based Feature Extraction for Pupil Recognition in Cataract Surgery. |
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| المؤلفون: | Giap BD, Srinivasan K, Mahmoud O, Mian SI, Tannen BL, Nallasamy N |
| المصدر: | Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference [Annu Int Conf IEEE Eng Med Biol Soc] 2023 Jul; Vol. 2023, pp. 1-4. |
| نوع المنشور: | Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: [IEEE] Country of Publication: United States NLM ID: 101763872 Publication Model: Print Cited Medium: Internet ISSN: 2694-0604 (Electronic) Linking ISSN: 23757477 NLM ISO Abbreviation: Annu Int Conf IEEE Eng Med Biol Soc Subsets: MEDLINE |
| أسماء مطبوعة: | Original Publication: [Piscataway, NJ] : [IEEE], [2007]- |
| مواضيع طبية MeSH: | Cataract Extraction*/methods , Lens, Crystalline* , Cataract*, Humans ; Pupil ; Surgical Instruments |
| مستخلص: | Cataract surgery remains the definitive treatment for cataracts, which are a major cause of preventable blindness worldwide. Adequate and stable dilation of the pupil are necessary for the successful performance of cataract surgery. Pupillary instability is a known risk factor for cataract surgery complications, and the accurate segmentation of the pupil from surgical video streams can enable the analysis of intraoperative pupil changes in cataract surgery. However, pupil segmentation performance can suffer due to variations in surgical illumination, obscuration of the pupil with surgical instruments, and hydration of the lens material intraoperatively. To overcome these challenges, we present a novel method called tensor-based pupil feature extraction (TPFE) to improve the accuracy of pupil recognition systems. We analyzed the efficacy of this approach with experiments performed on a dataset of 4,560 intraoperative annotated images from 190 cataract surgeries in human patients. Our results indicate that TPFE can identify features relevant to pupil segmentation and that pupil segmentation with state-of-the-art deep learning models can be significantly improved with the TPFE method. |
| References: | IEEE Trans Image Process. 2017 May;26(5):2466-2479. (PMID: 28237929) IEEE Trans Pattern Anal Mach Intell. 2021 Oct;43(10):3349-3364. (PMID: 32248092) Ann Transl Med. 2020 Nov;8(22):1540. (PMID: 33313285) |
| معلومات مُعتمدة: | D43 TW012027 United States TW FIC NIH HHS; K12 EY022299 United States EY NEI NIH HHS |
| تواريخ الأحداث: | Date Created: 20231212 Date Completed: 20231216 Latest Revision: 20240702 |
| رمز التحديث: | 20240702 |
| مُعرف محوري في PubMed: | PMC10979349 |
| DOI: | 10.1109/EMBC40787.2023.10340785 |
| PMID: | 38082579 |
| قاعدة البيانات: | MEDLINE |
Full Text Finder | تدمد: | 2694-0604 |
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| DOI: | 10.1109/EMBC40787.2023.10340785 |