Artificial intelligence(AI),encompassing machine learning and deep learning,is being extensively used in medical sciences.It is slated to positively impact the diagnosis and prognostication of various diseases.Deep le...Artificial intelligence(AI),encompassing machine learning and deep learning,is being extensively used in medical sciences.It is slated to positively impact the diagnosis and prognostication of various diseases.Deep learning,a subset of AI,has been instrumental in diagnosing diabetic retinopathy(DR),diabetic macular edema,glaucoma,age-related macular degeneration,and numerous other ocular diseases.AI performs equally well in the early prediction of glaucoma and agerelated macular degeneration.Integrating AI with telemedicine promises to improve healthcare delivery,although challenges persist in implementing AI algorithms,especially in deve-loping countries.This review provides a compre hensive summary of AI,its applications in ophthalmology,particularly DR,the diverse algorithms utilized for different ocular conditions,and prospects for the future integration of AI in eye care.展开更多
Purpose:This study aimed to propose a novel deep learning-based approach to assess the extent of abduction in patients with abducens nerve palsy before and after strabismus surgery.Methods:This study included 13 patie...Purpose:This study aimed to propose a novel deep learning-based approach to assess the extent of abduction in patients with abducens nerve palsy before and after strabismus surgery.Methods:This study included 13 patients who were diagnosed with abducens nerve palsy and underwent strabismus surgery in a tertiary hospital.Photographs of primary,dextroversion and levoversion position were collected before and after strabismus surgery.The eye location and eye segmentation network were trained via recurrent residual convolutional neural networks with attention gate connection based on U-Net(R2AU-Net).Facial images of abducens nerve palsy patients were used as the test set and parameters were measured automatically based on the masked images.Absolute abduction also was measured manually,and relative abduction was calculated.Agreements between manual and automatic measurements,as well as repeated automatic measurements were analyzed.Preoperative and postoperative results were compared.Results:The intraclass correlation coefficients(ICCs)between manual and automatic measurements of absolute abduction ranged from 0.985 to 0.992(P<0.001),and the bias ranged from-0.25 mm to-0.05 mm.The ICCs between two repeated automatic measurements ranged from 0.994 to 0.997(P<0.001),and the bias ranged from-0.11 mm to 0.05 mm.After strabismus surgery,absolute abduction of affected eye increased from 2.18±1.40 mm to 3.36±1.93 mm(P<0.05).The relative abduction was improved in 76.9%patients(10/13)after surgery(P<0.01).Conclusions:This image analysis technique demonstrated excellent accuracy and repeatability for automatic measurements of ocular abduction,which has promising application prospects in objectively assessing surgical outcomes in patients with abducens nerve palsy.展开更多
An on-line full scan inspection system is developed for particle size analysis. A particle image is first obtained through optical line scan technology and is then analyzed using digital image processing. The system i...An on-line full scan inspection system is developed for particle size analysis. A particle image is first obtained through optical line scan technology and is then analyzed using digital image processing. The system is composed of a particle separation module, an image acquisition module, an image processing module, and an electric control module. Experiments are carried out using non-uniform 0.1 mm particles. The main advantage of this system consists of a full analysis of particles without any overlap or miss, thus improving the Area Scan Charge Coupled Device （CCD） acquisition problems. Particle size distribution, roundness, and sphericity can be obtained using the system with a deviation of repeated precision of around ±1%. The developed system is shown to be also convenient and versatile for any particle size and shape for academic and industrial users.展开更多
文摘Artificial intelligence(AI),encompassing machine learning and deep learning,is being extensively used in medical sciences.It is slated to positively impact the diagnosis and prognostication of various diseases.Deep learning,a subset of AI,has been instrumental in diagnosing diabetic retinopathy(DR),diabetic macular edema,glaucoma,age-related macular degeneration,and numerous other ocular diseases.AI performs equally well in the early prediction of glaucoma and agerelated macular degeneration.Integrating AI with telemedicine promises to improve healthcare delivery,although challenges persist in implementing AI algorithms,especially in deve-loping countries.This review provides a compre hensive summary of AI,its applications in ophthalmology,particularly DR,the diverse algorithms utilized for different ocular conditions,and prospects for the future integration of AI in eye care.
基金supported by General Planning Project of Education Science Planning of Zhejiang Province(2024SCG251)Key Program of the National Natural Science Foundation of China(82330032)+1 种基金National Natural Science Foundation Regional Innovation and Development Joint Fund(U20A20386)Key Research and Development Program of Zhejiang Province(2024C03204).
文摘Purpose:This study aimed to propose a novel deep learning-based approach to assess the extent of abduction in patients with abducens nerve palsy before and after strabismus surgery.Methods:This study included 13 patients who were diagnosed with abducens nerve palsy and underwent strabismus surgery in a tertiary hospital.Photographs of primary,dextroversion and levoversion position were collected before and after strabismus surgery.The eye location and eye segmentation network were trained via recurrent residual convolutional neural networks with attention gate connection based on U-Net(R2AU-Net).Facial images of abducens nerve palsy patients were used as the test set and parameters were measured automatically based on the masked images.Absolute abduction also was measured manually,and relative abduction was calculated.Agreements between manual and automatic measurements,as well as repeated automatic measurements were analyzed.Preoperative and postoperative results were compared.Results:The intraclass correlation coefficients(ICCs)between manual and automatic measurements of absolute abduction ranged from 0.985 to 0.992(P<0.001),and the bias ranged from-0.25 mm to-0.05 mm.The ICCs between two repeated automatic measurements ranged from 0.994 to 0.997(P<0.001),and the bias ranged from-0.11 mm to 0.05 mm.After strabismus surgery,absolute abduction of affected eye increased from 2.18±1.40 mm to 3.36±1.93 mm(P<0.05).The relative abduction was improved in 76.9%patients(10/13)after surgery(P<0.01).Conclusions:This image analysis technique demonstrated excellent accuracy and repeatability for automatic measurements of ocular abduction,which has promising application prospects in objectively assessing surgical outcomes in patients with abducens nerve palsy.
文摘An on-line full scan inspection system is developed for particle size analysis. A particle image is first obtained through optical line scan technology and is then analyzed using digital image processing. The system is composed of a particle separation module, an image acquisition module, an image processing module, and an electric control module. Experiments are carried out using non-uniform 0.1 mm particles. The main advantage of this system consists of a full analysis of particles without any overlap or miss, thus improving the Area Scan Charge Coupled Device （CCD） acquisition problems. Particle size distribution, roundness, and sphericity can be obtained using the system with a deviation of repeated precision of around ±1%. The developed system is shown to be also convenient and versatile for any particle size and shape for academic and industrial users.
