💡[Feature]: Pseudo Papilledema Detection using Deep Learning

[sreevidya-16]

Is there an existing issue for this?

• [X] I have searched the existing issues

Feature Description

• Deep learning techniques are leveraged in pseudo-papilledema detection by training convolutional neural networks (CNNs) on large datasets of retinal images to differentiate between true papilledema and pseudo-papilledema.
• These models can automatically extract relevant features from the images, leading to high accuracy in identifying subtle differences that might be challenging for human observers.
• This approach improves diagnostic accuracy, reduces the need for invasive procedures, and supports ophthalmologists in making timely and precise decisions.

@TAHIR0110, @Avdhesh-Varshney, could you please assign me this issue under GSSOC'24

Use Case

Supports ophthalmologists in making timely and precise decisions.

Benefits

No response

Add ScreenShots

No response

Priority

High

Record

• [X] I have read the Contributing Guidelines
• [X] I'm a GSSOC'24 contributor
• [X] I want to work on this issue

[sreevidya-16]

@Avdhesh-Varshney, could you please assign me this issue

[sreevidya-16]

@Avdhesh-Varshney, could you please assign me this issue