• Avaneesh Khandekar
• Rutuja Shitole
• Siddharth Yawatkar
• Shreeya Tambolkar

This study proposes the use of computer-assisted analysis for better interpreting of images in the medical imaging field. On the image understanding front, recent advances in machine learning, especially deep learning, have made a big leap to help identify, classify, quantify patterns in medical images. Deep learning is rapidly proving to be the state-of-the-art foundation, achieving enhanced performances in various medical applications. We introduce the fundamentals of deep learning methods; review their successes to image registration and computer-aided disease diagnosis. In this Study, we surveyed the use of Computed Tomography (CT) scan and X-ray images as raw data input to a Convolutional Neural Network(CNN) and predict the presence of Chronic Obstructive Pulmonary Disease(COPD).

CNN, COPD, Neural Networks

"Detection of Chronic Obstructive Pulmonary Disease using Convolutional Neural Networks: A Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.182-185, April-2019, Available :http://www.jetir.org/papers/JETIR1904H36.pdf

"Detection of Chronic Obstructive Pulmonary Disease using Convolutional Neural Networks: A Survey", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp182-185, April-2019, Available at : http://www.jetir.org/papers/JETIR1904H36.pdf