Dear Editor,We report a relatively safe and effective triple procedure for traumatic aphakia,glaucoma,and mydriasis.Blunt eye trauma can lead to various anterior-and posterior-segment conditions[1],that often occur si...Dear Editor,We report a relatively safe and effective triple procedure for traumatic aphakia,glaucoma,and mydriasis.Blunt eye trauma can lead to various anterior-and posterior-segment conditions[1],that often occur simultaneously.Closed-globe injuries can damage one or more ocular structures.展开更多
Transorbital craniocerebral injury is a relatively rare type of penetrating head injury that poses a significant threat to the ocular and cerebral structures.^([1])The clinical prognosis of transorbital craniocerebral...Transorbital craniocerebral injury is a relatively rare type of penetrating head injury that poses a significant threat to the ocular and cerebral structures.^([1])The clinical prognosis of transorbital craniocerebral injury is closely related to the size,shape,speed,nature,and trajectory of the foreign object,as well as the incidence of central nervous system damage and secondary complications.The foreign objects reported to have caused these injuries are categorized into wooden items,metallic items,^([2-8])and other materials,which penetrate the intracranial region via fi ve major pathways,including the orbital roof (OR),superior orbital fissure (SOF),inferior orbital fissure(IOF),optic canal (OC),and sphenoid wing.Herein,we present eight cases of transorbital craniocerebral injury caused by an unusual metallic foreign body.展开更多
Myasthenia Gravis(MG)is an autoimmune neuromuscular disease.Given that extraocular muscle manifestations are the initial and primary symptoms in most patients,ocular muscle assessment is regarded necessary early scree...Myasthenia Gravis(MG)is an autoimmune neuromuscular disease.Given that extraocular muscle manifestations are the initial and primary symptoms in most patients,ocular muscle assessment is regarded necessary early screening tool.To overcome the limitations of the manual clinical method,an intuitive idea is to collect data via imaging devices,followed by analysis or processing using Deep Learning(DL)techniques(particularly image segmentation approaches)to enable automatic MG evaluation.Unfortunately,their clinical applications in this field have not been thoroughly explored.To bridge this gap,our study prospectively establishes a new DL-based system to promote the diagnosis of MG disease,with a complete workflow including facial data acquisition,eye region localization,and ocular structure segmentation.Experimental results demonstrate that the proposed system achieves superior segmentation performance of ocular structure.Moreover,it markedly improves the diagnostic accuracy of doctors.In the future,this endeavor can offer highly promising MG monitoring tools for healthcare professionals,patients,and regions with limited medical resources.展开更多
文摘Dear Editor,We report a relatively safe and effective triple procedure for traumatic aphakia,glaucoma,and mydriasis.Blunt eye trauma can lead to various anterior-and posterior-segment conditions[1],that often occur simultaneously.Closed-globe injuries can damage one or more ocular structures.
文摘Transorbital craniocerebral injury is a relatively rare type of penetrating head injury that poses a significant threat to the ocular and cerebral structures.^([1])The clinical prognosis of transorbital craniocerebral injury is closely related to the size,shape,speed,nature,and trajectory of the foreign object,as well as the incidence of central nervous system damage and secondary complications.The foreign objects reported to have caused these injuries are categorized into wooden items,metallic items,^([2-8])and other materials,which penetrate the intracranial region via fi ve major pathways,including the orbital roof (OR),superior orbital fissure (SOF),inferior orbital fissure(IOF),optic canal (OC),and sphenoid wing.Herein,we present eight cases of transorbital craniocerebral injury caused by an unusual metallic foreign body.
基金funded by the National High Level Hospital Clinical Research Funding(No.BJ-2023-111).
文摘Myasthenia Gravis(MG)is an autoimmune neuromuscular disease.Given that extraocular muscle manifestations are the initial and primary symptoms in most patients,ocular muscle assessment is regarded necessary early screening tool.To overcome the limitations of the manual clinical method,an intuitive idea is to collect data via imaging devices,followed by analysis or processing using Deep Learning(DL)techniques(particularly image segmentation approaches)to enable automatic MG evaluation.Unfortunately,their clinical applications in this field have not been thoroughly explored.To bridge this gap,our study prospectively establishes a new DL-based system to promote the diagnosis of MG disease,with a complete workflow including facial data acquisition,eye region localization,and ocular structure segmentation.Experimental results demonstrate that the proposed system achieves superior segmentation performance of ocular structure.Moreover,it markedly improves the diagnostic accuracy of doctors.In the future,this endeavor can offer highly promising MG monitoring tools for healthcare professionals,patients,and regions with limited medical resources.
