AIM:To explore the impact of insulin-like growth factor-1 receptorα(IGF-1Rα)on the differentiation fate of optic-cupderived retinal stem cells(OC-RSCs)into retinal ganglion cells(RGCs)in vitro.METHODS:OC-RSCs were i...AIM:To explore the impact of insulin-like growth factor-1 receptorα(IGF-1Rα)on the differentiation fate of optic-cupderived retinal stem cells(OC-RSCs)into retinal ganglion cells(RGCs)in vitro.METHODS:OC-RSCs were isolated from optic cups of rats on embryonic day 12.5,and high-purity OC-RSCs were obtained by conditioned culture and passage.Differentiation of OC-RSCs into RGCs under different serum concentrations was examined using flow cytometry,and the serum concentration with high interference with differentiation ratio was selected.Furthermore,the effect of blocking IGF-1Rαon the differentiation of OC-RSCs into RGCs was analyzed through immunocytochemistry and Western blotting.RESULTS:Immunohistochemical analysis revealed IGF-1Rαwas highly expressed in rat embryos at day 12.5.OC-RSCs were isolated and purified,and high-purity OCRSCs were obtained.When 2.5%serum was administered,the ratio of differentiated RGCs(Thy-1.1 positive)decreased significantly,and the results of immunoblotting also confirmed the blockade of IGF-1Rαreduced Thy-1.1 protein expression.CONCLUSION:IGF-1Rαblocking can reduce the differentiation of OC-RSCs into RGCs.展开更多
In this work,we aim to introduce some modifications to the Anam-Net deep neural network(DNN)model for segmenting optic cup(OC)and optic disc(OD)in retinal fundus images to estimate the cup-to-disc ratio(CDR).The CDR i...In this work,we aim to introduce some modifications to the Anam-Net deep neural network(DNN)model for segmenting optic cup(OC)and optic disc(OD)in retinal fundus images to estimate the cup-to-disc ratio(CDR).The CDR is a reliable measure for the early diagnosis of Glaucoma.In this study,we developed a lightweight DNN model for OC and OD segmentation in retinal fundus images.Our DNN model is based on modifications to Anam-Net,incorporating an anamorphic depth embedding block.To reduce computational complexity,we employ a fixed filter size for all convolution layers in the encoder and decoder stages as the network deepens.This modification significantly reduces the number of trainable parameters,making the model lightweight and suitable for resource-constrained applications.We evaluate the performance of the developed model using two publicly available retinal image databases,namely RIM-ONE and Drishti-GS.The results demonstrate promising OC segmentation performance across most standard evaluation metrics while achieving analogous results for OD segmentation.We used two retinal fundus image databases named RIM-ONE and Drishti-GS that contained 159 images and 101 retinal images,respectively.For OD segmentation using the RIM-ONE we obtain an f1-score(F1),Jaccard coefficient(JC),and overlapping error(OE)of 0.950,0.9219,and 0.0781,respectively.Similarly,for OC segmentation using the same databases,we achieve scores of 0.8481(F1),0.7428(JC),and 0.2572(OE).Based on these experimental results and the significantly lower number of trainable parameters,we conclude that the developed model is highly suitable for the early diagnosis of glaucoma by accurately estimating the CDR.展开更多
Purpose: To investigate the difference of stereometric parameters of optic nerve head between the normal subjects and patients with big-cupped disk and primary open angle glaucoma (POAG).Methods: Twenty-two cases (44 ...Purpose: To investigate the difference of stereometric parameters of optic nerve head between the normal subjects and patients with big-cupped disk and primary open angle glaucoma (POAG).Methods: Twenty-two cases (44 eyes) of normal subjects, 17 cases (34 eyes) of patients with big-cupped disk and 19 cases (37 eyes) of patients with POAG underwent Heidelberg Retina Tomograph (HRT) examination to get topography images and stereometric parameters of optic nerve head.Results: The stereometric parameters of optic nerve head of the normal, patients with big-cupped disk and POAG were 1) disk area (mm2): 1. 995± 0. 501, 2. 407±0. 661 and 2. 248±0.498; 2) cup area (mm2): 0.573±0.264, 1. 095±0. 673 and 1. 340±0. 516; 3) cup/disk ratio: 0. 25±0. 095, 0. 428±0. 176 and 0. 589±0.195; 4) rim area (mm2): 1.461±0.328, 1.312±0.418 and 0. 905± 0.409; 5)cup volume (mm3): 0. 108±0. 073, 0. 347±0. 346 and 0. 550 ±0. 394; 6) rim volume (mm3): 0. 421±0. 111, 0. 378±0. 225 and 0. 224±0. 189; 7) mean cup展开更多
视杯、视盘的区域信息对青光眼的诊断具有重要意义。为提高视网膜图像中杯盘分割的准确性,提出DMSwin-Unet模型。它以Swin-Unet为主干,融合MMAS(Multi-scale Mixed Aggregation and Selection)机制提高瓶颈层的感受野,增强边界与细节特...视杯、视盘的区域信息对青光眼的诊断具有重要意义。为提高视网膜图像中杯盘分割的准确性,提出DMSwin-Unet模型。它以Swin-Unet为主干,融合MMAS(Multi-scale Mixed Aggregation and Selection)机制提高瓶颈层的感受野,增强边界与细节特征的捕获能力;同时通过DCA(Dual Cross-Attention)模块加强跳跃连接中的语义信息交互,提升上下文建模能力。此外,结合杯盘边界模糊、区域不平滑的特点设计了混合损失函数,进一步优化分割边界。在REFUGE、ORIGA、Drishti-GS数据集上,DMSwin-Unet分别取得了视杯Dice分数:89.06%、91.28%、93.35%;视盘Dice分数:96.46%、98.06%、97.85%。实验结果表明,该模型在视杯与视盘分割任务中均优于现有方法,具备良好的临床应用潜力。展开更多
目的探讨生理性大视杯随时间推移,有无形态学变化。方法对200只生理性大视杯眼进行随访,每间隔3个月随访1次,每眼至少随访12个月以上。随访项目包括,各视乳头参数、眼压、视野、眼轴长度以及屈光度等。结果符合上述随访要求的有148只生...目的探讨生理性大视杯随时间推移,有无形态学变化。方法对200只生理性大视杯眼进行随访,每间隔3个月随访1次,每眼至少随访12个月以上。随访项目包括,各视乳头参数、眼压、视野、眼轴长度以及屈光度等。结果符合上述随访要求的有148只生理性大视杯眼,平均随访16个月。发现视杯面积(P<0.05),杯盘面积比、视杯容积、盘沿容积、平均视杯深度、最大视杯深度、轮廓线高度变化、平均视网膜神经纤维层厚度、视网膜神经纤维层横截面积均变大(P<0.01);盘沿面积变小(P<0.05);视盘面积、杯形测量无显著性变化。眼压值变小(P<0.01),视野 MS 变大、MD 变小(P<0.01),眼轴变长(P<0.01),近视加深(P<0.01)。结论经随访,生理性大视杯形态结构参数有一定变化,但无青光眼性神经损害。(中国眼耳鼻喉科杂志,2006,6:164～166)展开更多
文摘AIM:To explore the impact of insulin-like growth factor-1 receptorα(IGF-1Rα)on the differentiation fate of optic-cupderived retinal stem cells(OC-RSCs)into retinal ganglion cells(RGCs)in vitro.METHODS:OC-RSCs were isolated from optic cups of rats on embryonic day 12.5,and high-purity OC-RSCs were obtained by conditioned culture and passage.Differentiation of OC-RSCs into RGCs under different serum concentrations was examined using flow cytometry,and the serum concentration with high interference with differentiation ratio was selected.Furthermore,the effect of blocking IGF-1Rαon the differentiation of OC-RSCs into RGCs was analyzed through immunocytochemistry and Western blotting.RESULTS:Immunohistochemical analysis revealed IGF-1Rαwas highly expressed in rat embryos at day 12.5.OC-RSCs were isolated and purified,and high-purity OCRSCs were obtained.When 2.5%serum was administered,the ratio of differentiated RGCs(Thy-1.1 positive)decreased significantly,and the results of immunoblotting also confirmed the blockade of IGF-1Rαreduced Thy-1.1 protein expression.CONCLUSION:IGF-1Rαblocking can reduce the differentiation of OC-RSCs into RGCs.
基金funded byResearchers Supporting Project Number(RSPD2024R 553),King Saud University,Riyadh,Saudi Arabia.
文摘In this work,we aim to introduce some modifications to the Anam-Net deep neural network(DNN)model for segmenting optic cup(OC)and optic disc(OD)in retinal fundus images to estimate the cup-to-disc ratio(CDR).The CDR is a reliable measure for the early diagnosis of Glaucoma.In this study,we developed a lightweight DNN model for OC and OD segmentation in retinal fundus images.Our DNN model is based on modifications to Anam-Net,incorporating an anamorphic depth embedding block.To reduce computational complexity,we employ a fixed filter size for all convolution layers in the encoder and decoder stages as the network deepens.This modification significantly reduces the number of trainable parameters,making the model lightweight and suitable for resource-constrained applications.We evaluate the performance of the developed model using two publicly available retinal image databases,namely RIM-ONE and Drishti-GS.The results demonstrate promising OC segmentation performance across most standard evaluation metrics while achieving analogous results for OD segmentation.We used two retinal fundus image databases named RIM-ONE and Drishti-GS that contained 159 images and 101 retinal images,respectively.For OD segmentation using the RIM-ONE we obtain an f1-score(F1),Jaccard coefficient(JC),and overlapping error(OE)of 0.950,0.9219,and 0.0781,respectively.Similarly,for OC segmentation using the same databases,we achieve scores of 0.8481(F1),0.7428(JC),and 0.2572(OE).Based on these experimental results and the significantly lower number of trainable parameters,we conclude that the developed model is highly suitable for the early diagnosis of glaucoma by accurately estimating the CDR.
文摘Purpose: To investigate the difference of stereometric parameters of optic nerve head between the normal subjects and patients with big-cupped disk and primary open angle glaucoma (POAG).Methods: Twenty-two cases (44 eyes) of normal subjects, 17 cases (34 eyes) of patients with big-cupped disk and 19 cases (37 eyes) of patients with POAG underwent Heidelberg Retina Tomograph (HRT) examination to get topography images and stereometric parameters of optic nerve head.Results: The stereometric parameters of optic nerve head of the normal, patients with big-cupped disk and POAG were 1) disk area (mm2): 1. 995± 0. 501, 2. 407±0. 661 and 2. 248±0.498; 2) cup area (mm2): 0.573±0.264, 1. 095±0. 673 and 1. 340±0. 516; 3) cup/disk ratio: 0. 25±0. 095, 0. 428±0. 176 and 0. 589±0.195; 4) rim area (mm2): 1.461±0.328, 1.312±0.418 and 0. 905± 0.409; 5)cup volume (mm3): 0. 108±0. 073, 0. 347±0. 346 and 0. 550 ±0. 394; 6) rim volume (mm3): 0. 421±0. 111, 0. 378±0. 225 and 0. 224±0. 189; 7) mean cup
文摘目的探讨生理性大视杯随时间推移,有无形态学变化。方法对200只生理性大视杯眼进行随访,每间隔3个月随访1次,每眼至少随访12个月以上。随访项目包括,各视乳头参数、眼压、视野、眼轴长度以及屈光度等。结果符合上述随访要求的有148只生理性大视杯眼,平均随访16个月。发现视杯面积(P<0.05),杯盘面积比、视杯容积、盘沿容积、平均视杯深度、最大视杯深度、轮廓线高度变化、平均视网膜神经纤维层厚度、视网膜神经纤维层横截面积均变大(P<0.01);盘沿面积变小(P<0.05);视盘面积、杯形测量无显著性变化。眼压值变小(P<0.01),视野 MS 变大、MD 变小(P<0.01),眼轴变长(P<0.01),近视加深(P<0.01)。结论经随访,生理性大视杯形态结构参数有一定变化,但无青光眼性神经损害。(中国眼耳鼻喉科杂志,2006,6:164～166)
