Phase-Specific Augmented Reality Guidance for Microscopic Cataract Surgery Using Long-Short Spatiotemporal Aggregation Transformer

Phacoemulsification cataract surgery (PCS) is a routine procedure conducted using a surgical microscope, heavily reliant on the skill of the ophthalmologist. While existing PCS guidance systems extract valuable information from surgical microscopic videos to enhance intraoperative proficiency, they suffer from non-phasespecific guidance, leading to redundant visual information. In this study, our major contribution is the development of a novel phase-specific augmented reality (AR) guidance system, which offers tailored AR information corresponding to the recognized surgical phase. Leveraging the inherent quasi-standardized nature of PCS procedures, we propose a two-stage surgical microscopic video recognition network. In the first stage, we implement a multi-task learning structure to segment the surgical limbus region and extract limbus region-focused spatial feature for each frame. In the second stage, we propose the long-short spatiotemporal aggregation transformer (LS-SAT) network to model local fine-grained and global temporal relationships, and combine the extracted spatial features to recognize the current surgical phase. Additionally, we collaborate closely with ophthalmologists to design AR visual cues by utilizing techniques such as limbus ellipse fitting and regional restricted normal cross-correlation rotation computation. We evaluated the network on publicly available and in-house datasets, with comparison results demonstrating its superior performance compared to related works. Ablation results further validated the effectiveness of the limbus region-focused spatial feature extractor and the combination of temporal features. Furthermore, the developed system was evaluated in a clinical setup, with results indicating remarkable accuracy and real-time performance. underscoring its potential for clinical applications

Visual Impairment and Blindness

Blindness and vision impairment affect at least 2.2 billion people worldwide with most individuals having a preventable vision impairment. The majority of people with vision impairment are older than 50 years, however, vision loss can affect people of all ages. Reduced eyesight can have major and long-lasting effects on all aspects of life, including daily personal activities, interacting with the community, school and work opportunities, and the ability to access public services. This book provides an overview of the effects of blindness and visual impairment in the context of the most common causes of blindness in older adults as well as children, including retinal disorders, cataracts, glaucoma, and macular or corneal degeneration

Asia Pac J Ophthalmol (Phila)

Purpose:Most published systematic reviews have focused on the use of virtual reality (VR)/augmented reality (AR) technology in ophthalmology as it relates to surgical training. To date, this is the first review that investigates the current state of VR/AR technology applied more broadly to the entire field of ophthalmology.Methods:PubMed, Embase, and CINAHL databases were searched systematically from January 2014 through December 1, 2020. Studies that discussed VR and/or AR as it relates to the field of ophthalmology and provided information on the technology used were considered. Abstracts, non\u2013peer-reviewed literature, review articles, studies that reported only qualitative data, and studies without English translations were excluded.Results:A total of 77 studies were included in this review. Of these, 28 evaluated the use of VR/AR in ophthalmic surgical training/assessment and guidance, 7 in clinical training, 23 in diagnosis/screening, and 19 in treatment/therapy. 15 studies used AR, 61 used VR, and 1 used both. Most studies focused on the validity and usability of novel technologies.Conclusions:Ophthalmology is a field of medicine that is well suited for the use of VR/AR. However, further longitudinal studies examining the practical feasibility, efficacy, and safety of such novel technologies, the cost-effectiveness, and medical/legal considerations are still needed. We believe that time will indeed foster further technological advances and lead to widespread use of VR/AR in routine ophthalmic practice.20212022-06-05T00:00:00ZR21 EY029605/EY/NEI NIH HHSUnited States/U01 DP006436/DP/NCCDPHP CDC HHSUnited States/34383716PMC91676431151

OPTICAL COHERENCE TOMOGRAPHY OPHTHALMIC SURGICAL GUIDANCE

Optical coherence tomography (OCT) performs high-resolution cross-sectional and volumetric tissue imaging in situ through the combination of confocal gating, coherence gating, and polarization gating. Because it is noninvasive, OCT has been used in multiple clinical applications such as tissue pathology assessment and interventional procedure guidance. Moreover, OCT can perform functional measurements such as phase-sensitive measurement of blood flow and polarization-sensitive measurement of tissue birefringence. These features made OCT one of the most widely used imaging systems in ophthalmology. In this thesis, we present several novel OCT methods developed for microsurgery guidance and OCT image analysis. The thesis mainly consists of five parts, which are shown as follows. First, we present a BC-mode OCT image visualization method for microsurgery guidance, where multiple sparsely sampled B-scans are combined to generate a single cross-sectional image with an enhanced instrument and tissue layer visibility and reduced shadowing artifacts. The performance of the proposed method is demonstrated by guiding a 30-gauge needle into an ex-vivo human cornea. Second, we present a microscope-integrated OCT guided robotic subretinal injection method. A workflow is designed for accurate and stable robotic needle navigation. The performance of the proposed method is demonstrated on ex-vivo porcine eye subretinal injection. Third, we present optical flow OCT technique that quantifies accurate velocity fields. The accuracy of the proposed method is verified through phantom flow experiments by using a diluted milk powder solution as the scattering medium, in both cases of advective flow and turbulent flow. Fourth, we present a wrapped Gaussian mixture model to stabilize the phase of swept source OCT systems. A closed-form iteration solution is derived using the expectation-maximization algorithm. The performance of the proposed method is demonstrated through ex-vivo, in-vivo, and flow phantom experiments. The results show its robustness in different application scenarios. Fifth, we present a numerical landmark localization algorithm based on a convolutional neural network and a conditional random field. The robustness of the proposed method is demonstrated through ex-vivo porcine intestine landmark localization experiments