Objective: To analyze the effectiveness and safety of corneal relaxing incisions (CRI) in correcting keratometric astigmatism during cataract surgery. Methods: A prospective study of two groups: control group and trea...Objective: To analyze the effectiveness and safety of corneal relaxing incisions (CRI) in correcting keratometric astigmatism during cataract surgery. Methods: A prospective study of two groups: control group and treatment group. A treatment group included 25 eyes of 25 patients who had combined clear corneal phacoemulsification, IOL implantation and CRI. A control group included 25 eyes of 25 patients who had clear corneal phacoemulsification and IOL implantation.Postoperative keratometric astigmatism was measured at 1 week, 1 month, 3 months and 6 months. Results: CRI signifi-cantly decreased keratometric astigmatism in patients with preexisting astigmatism compared with astigmatic changes in the control group. In eyes with CRI, the mean keratometric astigmatism was 0.29±0.17 D(range 0 to 0.5 D) at 1 week, 0.41±0.21 D (range 0 to 0.82 D) at 1 month, respectively reduced by 2.42 D and 2.30 D at 1 week and 1 month postoperatively (P=0.000, P=0.000), and postoperative astigmatism was stable until 6 months follow-up. The keratometric astigmatism of all patients decreased to less than 1.00 D postoperatively. Conclusions: CRI is a practical, simple, safe and effective method to reduce preexisting astigmatism during cataract surgery. A modified nomogram is proposed. The long-term effect of CRI should be investigated.展开更多
Jacquard image segmentation is one of the primary steps in image analysis for jacquard pattern identification. The main aim is to recognize homogeneous regions within a jacquard image as distinct, which belongs to dif...Jacquard image segmentation is one of the primary steps in image analysis for jacquard pattern identification. The main aim is to recognize homogeneous regions within a jacquard image as distinct, which belongs to different patterns. Active contour models have become popular for finding the contours of a pattern with a complex shape. However, the performance of active contour models is often inadequate under noisy environment. In this paper, a robust algorithm based on the Mumford-Shah model is proposed for the segmentation of noisy jacquard images. First, the Mumford-Shah model is discretized on piecewise linear finite element spaces to yield greater stability. Then, an iterative relaxation algorithm for numerically solving the discrete version of the model is presented. In this algorithm, an adaptive triangular mesh is refined to generate Delaunay type triangular mesh defined on structured triangulations, and then a quasi-Newton numerical method is applied to find the absolute minimum of the discrete model. Experimental results on noisy jacquard images demonstrated the efficacy of the proposed algorithm.展开更多
Fast and accurate extraction of vascular structures from medical images is fundamental for many clinical procedures.However,most of the vessel segmentation techniques ignore the existence of the isolated and redundant...Fast and accurate extraction of vascular structures from medical images is fundamental for many clinical procedures.However,most of the vessel segmentation techniques ignore the existence of the isolated and redundant points in the segmentation results.In this study,we propose a vascular segmentation method based on a prior shape and local statistics.It could efficiently eliminate outliers and accurately segment thick and thin vessels.First,an improved vesselness filter is defined.This quantifies the likelihood of each voxel belonging to a bright tubular-shaped structure.A matching and connection process is then performed to obtain a blood-vessel mask.Finally,the region-growing method based on local statistics is implemented on the vessel mask to obtain the whole vascular tree without outliers.Experiments and comparisons with Frangi’s and Yang’s models on real magneticresonance-angiography images demonstrate that the proposed method can remove outliers while preserving the connectivity of vessel branches.展开更多
文摘Objective: To analyze the effectiveness and safety of corneal relaxing incisions (CRI) in correcting keratometric astigmatism during cataract surgery. Methods: A prospective study of two groups: control group and treatment group. A treatment group included 25 eyes of 25 patients who had combined clear corneal phacoemulsification, IOL implantation and CRI. A control group included 25 eyes of 25 patients who had clear corneal phacoemulsification and IOL implantation.Postoperative keratometric astigmatism was measured at 1 week, 1 month, 3 months and 6 months. Results: CRI signifi-cantly decreased keratometric astigmatism in patients with preexisting astigmatism compared with astigmatic changes in the control group. In eyes with CRI, the mean keratometric astigmatism was 0.29±0.17 D(range 0 to 0.5 D) at 1 week, 0.41±0.21 D (range 0 to 0.82 D) at 1 month, respectively reduced by 2.42 D and 2.30 D at 1 week and 1 month postoperatively (P=0.000, P=0.000), and postoperative astigmatism was stable until 6 months follow-up. The keratometric astigmatism of all patients decreased to less than 1.00 D postoperatively. Conclusions: CRI is a practical, simple, safe and effective method to reduce preexisting astigmatism during cataract surgery. A modified nomogram is proposed. The long-term effect of CRI should be investigated.
基金Project (No. 2003AA411021) supported by the Hi-Tech Research andDevelopment Program (863) of China
文摘Jacquard image segmentation is one of the primary steps in image analysis for jacquard pattern identification. The main aim is to recognize homogeneous regions within a jacquard image as distinct, which belongs to different patterns. Active contour models have become popular for finding the contours of a pattern with a complex shape. However, the performance of active contour models is often inadequate under noisy environment. In this paper, a robust algorithm based on the Mumford-Shah model is proposed for the segmentation of noisy jacquard images. First, the Mumford-Shah model is discretized on piecewise linear finite element spaces to yield greater stability. Then, an iterative relaxation algorithm for numerically solving the discrete version of the model is presented. In this algorithm, an adaptive triangular mesh is refined to generate Delaunay type triangular mesh defined on structured triangulations, and then a quasi-Newton numerical method is applied to find the absolute minimum of the discrete model. Experimental results on noisy jacquard images demonstrated the efficacy of the proposed algorithm.
基金Project supported by the National Natural Science Foundation of China(Nos.61472042 and 61802020)the Beijing Natural Science Foundation,China(No.4174094)the Fundamental Research Funds for the Central Universities,China(No.2015KJJCB25)
文摘Fast and accurate extraction of vascular structures from medical images is fundamental for many clinical procedures.However,most of the vessel segmentation techniques ignore the existence of the isolated and redundant points in the segmentation results.In this study,we propose a vascular segmentation method based on a prior shape and local statistics.It could efficiently eliminate outliers and accurately segment thick and thin vessels.First,an improved vesselness filter is defined.This quantifies the likelihood of each voxel belonging to a bright tubular-shaped structure.A matching and connection process is then performed to obtain a blood-vessel mask.Finally,the region-growing method based on local statistics is implemented on the vessel mask to obtain the whole vascular tree without outliers.Experiments and comparisons with Frangi’s and Yang’s models on real magneticresonance-angiography images demonstrate that the proposed method can remove outliers while preserving the connectivity of vessel branches.
