No abstract

Glaucoma is one of the leading severe retinal disease which damages the optic nerve head on the retinal part of the eye irreversibly. Once the person is diagnosed with glaucoma, it cannot be treated entirely, but it can be controlled. If glaucoma is not diagnosed in time, it will lead to vision loss by damaging the Optic Nerve Head. The glaucoma detection is performed based on the optic disc and optic cup parameters on the retinal part of the eye. In the existing system, many image processing and machine learning techniques used for the segmentation and classification of optic disc and optic cup. To improve the precision of diagnosis, the existing techniques used need an improvement. This article helps readers with more information about the existing methods applied for the diagnosis of glaucoma, it also lists the research gaps and technical challenges to improve the accuracy of segmentation and classification methods.

No abstract

No abstract

The main aim is to secure the medical records by ensuring safe communication between the sender and the receiver by adding multiple layers of security. This project is a combined approach of both encryption and steganography to give security the utmost importance. In the sender, only the authorized person can send the secret image to the receiver. In the first stage, an image steganography system is processed using confidential medical X-ray images which are hidden under the cover images. The encryption method used is based on Random Number Generator and the pixel indicator, in other words, by moving the position of the pixel in the image to encrypt the image on the transmitting side. Whereas on the receiver side, this project proposes a method to authenticate the receiver by incorporating Email Authentication and OTP Verification to decrypt the encrypted image.