X-Ray Examination Using Deep Learning

X-Ray Examination Using Deep Learning
Author(s):
Noor Fathima, Lakshmi M R, S.Tharunram, Owais Khan Hannan, Vibha S
Keywords:
Deep Learning, YoloV7, Machine Learning.
Abstract
In a human body bone is one of the most important part. Bones support your body and allow you to move. They protect your brain, heart, and other organs from injury. Bone is a living, growing tissue[11]. Many times due to accidents the bone can be broken. The X-Ray Examination helps detecting whether the bone was broken or not. The X-Ray Examiner helps detecting the fracture more accurately. The modelling of this software is done by using deep learning and trained datasets available at GRAZPEDWRI-DX. The GRAZPEDWRI-DX is an open [3] dataset containing 20327 annotated pediatric trauma wrist radiograph images of 6091 patients. The aim is to differentiate between a broken bone and a healthy bone. We will be using trained datasets and YoloV7 model, In order to expand the amount of the data set, data augmentation techniques that have been deployed.
Article Details
Unique Paper ID: 157920 Publication Volume & Issue: Volume 9, Issue 8 Page(s): 265 - 270
Article Preview & Download

Share This Article

NCSEM 2024

National Conference on Sustainable Engineering and Management - 2024

Last Date: 15th March 2024

IJIRT.org enables door in research by providing high quality research articles in open access market.

Send us any query related to your research on editor@ijirt.org