The Usefulness of AI-Based Cornea Exposure Rate (CER) Analysis Utilizing the Anigma View System in Evaluating Ptosis Surgery Outcomes

Journal of Clinical Medicine, Год журнала: 2025, Номер 14(5), С. 1691 - 1691

Опубликована: Март 3, 2025

Background/Objectives: Ptosis surgery corrects drooping upper eyelids, improving function and esthetics. Traditional methods like marginal reflex distance (MRD) palpebral fissure height (PFH) offer limited one-dimensional measurements. This study evaluates AI-based corneal exposure ratio (CER) analysis, a two-dimensional approach, compared to manual ImageJ for assessing ptosis outcomes. Methods: In this prospective study, 100 eyes from 50 patients were analyzed using both methods. CER measurements reliability accuracy. Results: comparable ImageJ, with high (ICC 0.992, 0.985). Preoperative was 55.34% (manual) 55.79% (AI), increasing 75.92% 75.84% (AI) postoperatively. The AI tool showed minimal bias repeatability 1.000), offering faster automated Conclusions: analysis matched in accuracy but provided significant efficiency advantages, making it suitable clinical use. Limitations include small homogeneous sample size reliance on 2D imaging, which may not fully capture three-dimensional changes. Further studies are recommended enhance generalizability precision.

Язык: Английский

---

Open-Source Periorbital Segmentation Dataset for Ophthalmic Applications

Ophthalmology Science, Год журнала: 2025, Номер unknown, С. 100757 - 100757

Опубликована: Март 1, 2025

Язык: Английский

---

AI-driven Eyeball Exposure Rate (EER) analysis: A useful tool for assessing ptosis surgery effectiveness

PLoS ONE, Год журнала: 2025, Номер 20(3), С. e0319577 - e0319577

Опубликована: Март 25, 2025

Introduction Ptosis surgery outcomes are measured by one-dimensional metrics like Marginal Reflex Distance (MRD) and Palpebral Fissure Height (PFH) using ImageJ. However, these methods insufficient to capture the full range of changes post-surgery. Eyeball Exposure Rate (EER) offers a more comprehensive two-dimensional perspective as metric. This study compares AI-based EER measurements with conventional ImageJ for assessing outcome ptosis surgery. Methods: Images from 50 patients (total 100 eyes) taken before after were analyzed manual AI-tool “Anigma-View”. Statistical tests assessed accuracy consistency both methods, intraclass correlation coefficients (ICCs) Bland-Altman plots comparison. Results at pre- post-operation 58.85% 75.36%, respectively. Similarly, showed an increase 58.22% 75.27%. The Intraclass Correlation Coefficients between ranged 0.984 0.994, indicating excellent agreement, repeated demonstrating high reproducibility (ICC = 1). agreement two measurements. Additionally, improvement was prominent in moderate severe group 45.94% increase, compared mild 14.39% increase. Discussion findings revealed no significant differences suggesting that is just reliable. automate efficiency objectivity, making it valuable method clinical fields. Conclusion analysis accurate efficient, providing comparable results methods. Its ability simplify surgical assessments makes promising addition practice. Further exploration AI evaluating three-dimensional could enhance future outcomes.

Язык: Английский

---

Multidimensional quantitative characterization of periocular morphology: distinguishing esotropia from epicanthus by deep learning network

Quantitative Imaging in Medicine and Surgery, Год журнала: 2024, Номер 14(9), С. 6273 - 6284

Опубликована: Авг. 12, 2024

Prominent epicanthus could not only diminish the eyes' aesthetics but may be deceptive for its typical appearance of pseudo-esotropia. This study aims to apply a deep learning model characterize periocular morphology preliminary identification.

Язык: Английский

---