Surgical outcome and safety of peripheral iridectomy plus goniosynechialysis and goniotomy in the treatment of advanced primary angle-closure glaucoma / 中华实验眼科杂志

Objective:To evaluate the preliminary effectiveness and safety of surgical peripheral iridectomy (SPI) combined with goniosynechilysis (GSL) and goniotomy (GT) in the treatment of advanced primary angle-closure glaucoma (PACG).Methods:A multicenter observational case series study was performed.Thirty-five eyes of 27 patients with advanced PACG, who underwent SPI+ GSL+ GT with a follow-up of at least 6 months, were included from August 2021 to January 2022 at Zhongshan Ophthalmic Center, Handan City Eye Hospital, Shijiazhuang People's Hospital, West China Hospital of Sichuan University, and the Third Affiliated Hospital of Chongqing Medical University.The mean follow-up time was 9(7, 10) months.Pre- and post-operative best corrected visual acuity (BCVA) and intraocular pressure (IOP) were measured with an ETDRS chart and a Goldmann applanation tonometer, respectively.The number of anti-glaucoma medications applied before and after surgery was recorded, and the complications after surgery were analyzed.Success rate of surgery was calculated.Complete surgical success was defined as an IOP of 5-18 mmHg (1 mmHg=0.133 kPa) and 20% reduction from baseline without anti-glaucoma medication or reoperation.Qualified success was defined as achieving criterion of complete success under anti-glaucoma medications.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Zhongshan Ophthalmic Center, Sun Yat-sen University (No.2021KYPJ177). Written informed consent was obtained from each subject.Results:The mean preoperative IOP was (30.83±8.87)mmHg, which was significantly decreased to (15.69±3.70)mmHg at 6 months after the surgery ( t=8.588, P<0.001), with a 44.00% (34.78%, 60.00%) decline of 13.00(8.00, 21.00)mmHg.The median number of anti-glaucoma medications was significantly reduced from 2(0, 3) preoperatively to 0 (0, 1) postoperatively ( Z=-3.659, P<0.001). The mean preoperative and postoperative 6-month BCVA were 0.80(0.63, 1.00) and 0.80(0.60, 1.00), respectively, showing no significant difference ( Z=-0.283, P=0.777). Complete surgical success rate was 62.86%(22/35), and the qualified success rate was 91.43%(32/35). Surgical complications mainly included hyphema (6/35), IOP spike (3/35), and shallow anterior chamber (4/35). There was no vision-threatening complication. Conclusions:SPI+ GSL+ GT is preliminarily effective and safe in the treatment of advanced PACG, which provides a new option for PACG.

$\ell _{2,p}$ -Norm Based PCA for Image Recognition.

Recently, many ℓ1-norm-based PCA approaches have been developed to improve the robustness of PCA. However, most existing approaches solve the optimal projection matrix by maximizing ℓ1-norm-based variance and do not best minimize the reconstruction error, which is the true goal of PCA. Moreover, they do not have rotational invariance. To handle these problems, we propose a generalized robust metric learning for PCA, namely, ℓ2,p-PCA, which employs ℓ2,p -norm as the distance metric for reconstruction error. The proposed method not only is robust to outliers but also retains PCA's desirable properties. For example, the solutions are the principal eigenvectors of a robust covariance matrix and the low-dimensional representation have rotational invariance. These properties are not shared by ℓ1-norm-based PCA methods. A new iteration algorithm is presented to solve ℓ2,p-PCA efficiently. Experimental results illustrate that the proposed method is more effective and robust than PCA, PCA-L1 greedy, PCA-L1 nongreedy, and HQ-PCA.

Tensor Rank Preserving Discriminant Analysis for Facial Recognition.

Facial recognition, one of the basic topics in computer vision and pattern recognition, has received substantial attention in recent years. However, for those traditional facial recognition algorithms, the facial images are reshaped to a long vector, thereby losing part of the original spatial constraints of each pixel. In this paper, a new tensor-based feature extraction algorithm termed tensor rank preserving discriminant analysis (TRPDA) for facial image recognition is proposed; the proposed method involves two stages: in the first stage, the low-dimensional tensor subspace of the original input tensor samples was obtained; in the second stage, discriminative locality alignment was utilized to obtain the ultimate vector feature representation for subsequent facial recognition. On the one hand, the proposed TRPDA algorithm fully utilizes the natural structure of the input samples, and it applies an optimization criterion that can directly handle the tensor spectral analysis problem, thereby decreasing the computation cost compared those traditional tensor-based feature selection algorithms. On the other hand, the proposed TRPDA algorithm extracts feature by finding a tensor subspace that preserves most of the rank order information of the intra-class input samples. Experiments on the three facial databases are performed here to determine the effectiveness of the proposed TRPDA algorithm.

Single Image Super-Resolution Using Gaussian Process Regression With Dictionary-Based Sampling and Student- ${t}$ Likelihood.

Gaussian process regression (GPR) is an effective statistical learning method for modeling non-linear mapping from an observed space to an expected latent space. When applying it to example learning-based super-resolution (SR), two outstanding issues remain. One is its high computational complexity restricts SR application when a large data set is available for learning task. The other is that the commonly used Gaussian likelihood in GPR is incompatible with the true observation model for SR reconstruction. To alleviate the above two issues, we propose a GPR-based SR method by using dictionary-based sampling (DbS) and student-t likelihood. Considering that dictionary atoms effectively span the original training sample space, we adopt a DbS strategy by combining all the neighborhood samples of each atom into a compact representative training subset so as to reduce the computational complexity. Based on statistical tests, we statistically validate that student-t likelihood is more suitable to build the observation model for the SR problem. Extensive experimental results show that the proposed method outperforms other competitors and produces more pleasing details in texture regions.

A Non-Greedy Algorithm for L1-Norm LDA.

Recently, L1-norm-based discriminant subspace learning has attracted much more attention in dimensionality reduction and machine learning. However, most existing approaches solve the column vectors of the optimal projection matrix one by one with greedy strategy. Thus, the obtained optimal projection matrix does not necessarily best optimize the corresponding trace ratio objective function, which is the essential criterion function for general supervised dimensionality reduction. In this paper, we propose a non-greedy iterative algorithm to solve the trace ratio form of L1-norm-based linear discriminant analysis. We analyze the convergence of our proposed algorithm in detail. Extensive experiments on five popular image databases illustrate that our proposed algorithm can maximize the objective function value and is superior to most existing L1-LDA algorithms.

Robust Face Sketch Style Synthesis.

Heterogeneous image conversion is a critical issue in many computer vision tasks, among which example-based face sketch style synthesis provides a convenient way to make artistic effects for photos. However, existing face sketch style synthesis methods generate stylistic sketches depending on many photo-sketch pairs. This requirement limits the generalization ability of these methods to produce arbitrarily stylistic sketches. To handle such a drawback, we propose a robust face sketch style synthesis method, which can convert photos to arbitrarily stylistic sketches based on only one corresponding template sketch. In the proposed method, a sparse representation-based greedy search strategy is first applied to estimate an initial sketch. Then, multi-scale features and Euclidean distance are employed to select candidate image patches from the initial estimated sketch and the template sketch. In order to further refine the obtained candidate image patches, a multi-feature-based optimization model is introduced. Finally, by assembling the refined candidate image patches, the completed face sketch is obtained. To further enhance the quality of synthesized sketches, a cascaded regression strategy is adopted. Compared with the state-of-the-art face sketch synthesis methods, experimental results on several commonly used face sketch databases and celebrity photos demonstrate the effectiveness of the proposed method.

Face sketch synthesis via sparse representation-based greedy search.

Face sketch synthesis has wide applications in digital entertainment and law enforcement. Although there is much research on face sketch synthesis, most existing algorithms cannot handle some nonfacial factors, such as hair style, hairpins, and glasses if these factors are excluded in the training set. In addition, previous methods only work on well controlled conditions and fail on images with different backgrounds and sizes as the training set. To this end, this paper presents a novel method that combines both the similarity between different image patches and prior knowledge to synthesize face sketches. Given training photo-sketch pairs, the proposed method learns a photo patch feature dictionary from the training photo patches and replaces the photo patches with their sparse coefficients during the searching process. For a test photo patch, we first obtain its sparse coefficient via the learnt dictionary and then search its nearest neighbors (candidate patches) in the whole training photo patches with sparse coefficients. After purifying the nearest neighbors with prior knowledge, the final sketch corresponding to the test photo can be obtained by Bayesian inference. The contributions of this paper are as follows: 1) we relax the nearest neighbor search area from local region to the whole image without too much time consuming and 2) our method can produce nonfacial factors that are not contained in the training set and is robust against image backgrounds and can even ignore the alignment and image size aspects of test photos. Our experimental results show that the proposed method outperforms several state-of-the-arts in terms of perceptual and objective metrics.

Glaucoma secondary to systemic lupus erythematosus / 中华医学杂志(英文版)

<p><b>BACKGROUND</b>Glaucoma secondary to systemic lupus erythematosus (SLE) is an uncommon but serious complication that threatens vision and therefore cannot be neglected. A few cases of secondary glaucoma resulting from lupus-induced or iatrogenic ocular impairments have been reported in association with SLE. However, a systematic analysis of the diagnosis and treatment of glaucoma secondary to SLE has not been reported in the literature. The aim of this study is to further investigate the relationship between glaucoma and SLE.</p><p><b>METHODS</b>In this study, we reviewed nine eyes of five patients diagnosed with secondary glaucoma associated with SLE, including one case of neovascular glaucoma and four cases of steroid-induced glaucoma.</p><p><b>RESULTS</b>Neovascular glaucoma was successfully treated by Ahmed glaucoma valve implantation surgery with adjunctive ranibizumab intravitreal injection, followed by panretinal photocoagulation (PRP). The steroid-induced glaucoma in eight eyes of four cases were controlled by trabeculectomy along with antiproliferative agents.</p><p><b>CONCLUSION</b>Regular follow-up ocular examinations should be conducted to ensure early diagnosis and treatment of secondary glaucoma in SLE patients to improve the prognosis of vision.</p>

A prospective comparative study on neovascular glaucoma and non-neovascular refractory glaucoma following Ahmed glaucoma valve implantation / 中华医学杂志(英文版)

<p><b>BACKGROUND</b>Neovascular glaucoma is a refractory disease, and difficult to manage. The aim of this study was to evaluate the clinical outcomes of Ahmed glaucoma valve implantation (AGVI) in neovascular glaucoma (NVG) and non-NVG patients.</p><p><b>METHODS</b>This prospective, non-randomized study included 55 eyes of 55 patients with refractory glaucoma; 27 had NVG (NVG group) and 28 had non-NVG (non-NVG group). All of the patients underwent AGVI. The NVG group was adjunctively injected with intravitreal ranibizumab/bevacizumab (IVR/IVB) before AGVI. Intraocular pressure (IOP) was the primary outcome measure in this study. Surgical success rate, number of antiglaucoma medications used, best corrected visual acuity (BCVA), and postoperative complications were analyzed between the groups.</p><p><b>RESULTS</b>All of the patients completed the study (follow-up of 12 months). Kaplan-Meier survival curve analysis indicated that the qualified success rates in the NVG and non-NVG groups at 12 months were 70.5% and 92.9%, respectively; this difference was significant (P = 0.036). The complete success rates in the NVG and non-NVG groups at 12 months were 66.7% and 89.3%, respectively (P = 0.049). Compared with preoperative examinations, the postoperative mean IOP and use of medications were significantly lower at all follow-up time points in both groups (all P < 0.05). There were significant differences in BCVA between the two groups at the 12-month follow-up (χ(2) = 9.86, P = 0.020). Cox proportional hazards regression showed NVG as a risk factor for surgical failure (RR = 15.08, P = 0.033). Postoperative complications were similar between the two groups.</p><p><b>CONCLUSIONS</b>AGVI is a safe and effective procedure in refractory glaucoma, but the success rate of surgery was related to the type of refractory glaucoma. The complete and qualified success rates of NVG patient adjunctive anti-vascular endothelial growth factor treatment are still lower than those of non-NVG patients.</p>

Modified trabeculectomy in primary acute angle-closure with high intraocular pressure and extremely dilated pupil / 中华显微外科杂志

ObjectiveTo determined the outcome of modified trabeculecotomy (with paracentesis,mitomycin C,scleral flap adjustable suture and formation of anterior chamber at the end of the surgery)in the management of primary acute angle-closure (PAAC) with high intraocular pressure (IOP) and extremely dilated pupil. MethodsTwenty-one eyes of 21 successive cases with PAAC with high lOP(IOP ＞ 30mmHg) and large pupil (maximum vertical diameter ＞ 5 mm) were evaluated prospectively. They underwent modified trabeculecotomy between January 2005 and March 2009.The operative success was defined as IOP ≤ 20 mmHg (± medical therapy) without the necessity of further surgery for glaucoma. ResultsSuccess was achieved in all of the eyes(100％)at the postoperative first week.The mean preoperative IOP was (48.25 ± 3.14) mmHg under a mean number of 3.35 antiglaucomotous medications, but it reduced to (10.47 ± 1.15,P ＜ 0.01) mmHg without medication at the first week, (13.86 ± 0.93,P ＜ 0.01) mmHg at postoperative 3rd month respectively.Only 1 eye needed 1 kind of antiglaucomotous eye drop from the 2nd month postoperatively. The mean vertical diameter of pupils was (5.81±0.23) mm preoperatively, (5.92 ±0.21 ) mm at the first week(P ＞ 0.05). No case received section iridectomy. No serious complication was observed.ConclusionsModified trabeculectomy provides reduction of IOP and protection of pupil in cases with PAAC with high IOP and large pupil,and the procedures such as releasing aqueous humor gradually,appliance of scleral flap adjustable sutures and formation of anterior chamber at the end of the surgery can effectively reduce the risk of serious complications.