Support tool for presumptive diagnosis of Glaucoma using fundus image processing and artificial intelligence implementation


Abstract:

Blindness is a global health problem and glaucoma is one of the diseases that are considered of vital importance to treat since it is a neurodegenerative disease that causes irreversible blindness that still has no cure, however, it can be treated if detected early; Most people begin to feel symptoms when this disease is already in an advanced stage, therefore in this work we have developed a tool to support the medical diagnosis through digital image processing for it has been consulted in several databases for the study and classification of retinal images among these images we have healthy eyes, suspected glaucoma and diagnosed with glaucoma. The region of interest, we worked with was the optic disc since this is where the blood vessels are interconnected and it is an important area for analysis. We have made a tool to support the presumptive diagnosis of glaucoma applied several neural systems with different structures obtaining very good results of accuracy and sensitivity, this tool was developed free software so that it has free access to both treating physicians and students in the health area, in addition, it has been made in a very intuitive way for its easy use, in first instance allows the entry of images in JPG, JPEG and PNG color format, additionally the patient's data and the treating physician, the results are displayed in a PDF format document with all the information entered and the respective diagnosis, which makes it easier to keep a proper medical history.

Año de publicación:

2022

Keywords:

  • Convolutional Networks
  • Visual Impairment
  • Presumptive diagnosis
  • optic disc
  • glaucoma
  • Neural networks
  • pbkp_rediction and detection of glaucoma
  • Blindness

Fuente:

scopusscopus

Tipo de documento:

Conference Object

Estado:

Acceso restringido

Áreas de conocimiento:

  • Inteligencia artificial
  • Ciencias de la computación

Áreas temáticas:

  • Enfermedades
  • Métodos informáticos especiales
  • Física aplicada