Purpose: To study the use of sulcus placement of a 3-piece intraocular lens (IOL) with optic capture in patients with exfoliation with zonular weakness.
Methods: Data on all exfoliation patients who had direct or indirect evidence of zonular weakness and had a 3-piece IOL implanted in the sulcus with optic capture over a 5-year period between January 2017 and January 2022 were included in this retrospective case series.
Results: The study comprised of 35 eyes of 35 patients. The mean age at surgery of the 20 male and 13 female patients was 75.21 years ± 5.74 (standard deviation (SD)). The mean pupillary diameter was 5.77 ± 2.23 mm (range: 10 to 3 mm). A capsular tension ring (CTR) was used in 17 cases and iris hooks as a pupil-expanding device were used in 15 cases. No patients had an increase in inflammation after surgery and there were no late subluxation or dislocation of "in the bag" posterior chamber IOL or major complications. There was a significant improvement in visual acuity.
Conclusion: The sulcus placement of 3-piece IOL with optic capture is the ideal technique in patients with clinical or intraoperative evidence of mild to moderate zonular weakness. It may also be more appropriate in relatively younger patients (in the fifties or sixties) with exfoliation with no overt zonulopathy to prevent late subluxation or dislocation of "in the bag" IOL.
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http://dx.doi.org/10.4103/ijo.IJO_1415_22 | DOI Listing |
Sensors (Basel)
January 2025
School of Computer Science, Northeast Electric Power University, Jilin 132012, China.
Satellites frequently encounter atmospheric haze during imaging, leading to the loss of detailed information in remote sensing images and significantly compromising image quality. This detailed information is crucial for applications such as Earth observation and environmental monitoring. In response to the above issues, this paper proposes an end-to-end multi-scale adaptive feature extraction method for remote sensing image dehazing (MSD-Net).
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December 2024
Intelligent Manufacturing Laboratory, Production Engineering Institute, Faculty of Mechanical Engineering, University of Maribor, Smetanova ulica 17, 2000 Maribor, Slovenia.
Direct verification of the geometric accuracy of machined parts cannot be performed simultaneously with active machining operations, as it usually requires subsequent inspection with measuring devices such as coordinate measuring machines (CMMs) or optical 3D scanners. This sequential approach increases production time and costs. In this study, we propose a novel indirect measurement method that utilizes motor current data from the controller of a Computer Numerical Control (CNC) machine in combination with machine learning algorithms to predict the geometric accuracy of machined parts in real-time.
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December 2024
Key Laboratory of Opto-Electronic Information Processing, Chinese Academy of Sciences, Shenyang 110016, China.
Cross-view geo-localization (CVGL) aims to determine the capture location of street-view images by matching them with corresponding 2D maps, such as satellite imagery. While recent bird's eye view (BEV)-based methods have advanced this task by addressing viewpoint and appearance differences, the existing approaches typically rely solely on either OpenStreetMap (OSM) data or satellite imagery, limiting localization robustness due to single-modality constraints. This paper presents a novel CVGL method that fuses OSM data with satellite imagery, leveraging their complementary strengths to enhance localization robustness.
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December 2024
Department of Advanced Medical and Surgical Sciences, University of Campania Luigi Vanvitelli, 80138 Naples, Italy.
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January 2025
International Health Policy Program (IHPP), Ministry of Public Health, Nonthaburi, Thailand.
Introduction: Screening diabetic retinopathy (DR) for timely management can reduce global blindness. Many existing DR screening programs worldwide are non-digital, standalone, and deployed with grading retinal photographs by trained personnel. To integrate the screening programs, with or without artificial intelligence (AI), into hospital information systems to improve their effectiveness, the non-digital workflow must be transformed into digital.
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