Covid Vision : Advanced Covid-19 detection from lung X-rays with machine learning or deep learnings
Project Title: Covid Vision : Advanced Covid-19 detection from lung X-rays with machine learning or deep learnings
Team Id: NM2023TMID22628
Team Size: 5
Team Leader: GURU PRAKASH G
Team Member: MANOJ S
Team Member: ALAGU VELAN G
Team Member: JENISH DEVA RAJ J
Team Member: NADEEM MALIK R
Description : COVID-19 (coronavirus disease 2019) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is a strain of coronavirus. The disease was officially announced as a pandemic by the World Health Organization(WHO) on 11 March 2020. Given spikes in new COVID-19 cases and the re-opening of daily activities around the world, the demand for curbing the pandemic is to be more emphasized. Medical images and artificial intelligence (AI) have been found useful for rapid assessment to provide treatment of COVID-19 infected patients. The PCR test may take several hours to become available, information revealed from the chest X-ray plays an important role for a rapid clinical assessment. This means if the clinical condition and the chest X-ray are normal, the patient is sent home while awaiting the results of the etiological test. But if the X-ray shows pathological findings, the suspected patient will be admitted to the hospital for close monitoring. Chest X-ray data have been found to be very promising for assessing COVID-19 patients, especially for resolving emergency-department and urgent-care-center overcapacity. Deep-learning (DL) methods in artificial intelligence (AI) play a dominant role as high-performance classifiers in the detection of the disease using chest X-rays. One of the biggest challenges following the Covid-19 pandemic is the detection of the disease in patients. To address this challenge we have been using the Deep Learning Algorithm to build an image recognition model that can detect the presence of Covid-19 from an X-Ray or CT-Scan image of a patient's lungs.
Transfer learning has become one of the most common techniques that has achieved better performance in many areas, especially in medical image analysis and classification. We used Transfer Learning techniques like Inception V3,Resnet50, Xception V3 that are more widely used as a transfer learning method in medical image analysis and they are highly effective.
Dataset Link: https://www.kaggle.com/code/rollanmaratov/...
Reference Source Code:
https://github.com/100ravp/Deep-Learning-w...