Using Computer Vision Techniques to Automatically Detect Abnormalities in Chest X-rays.

ABSTRACT: Our research focused on creating an advanced machine-learning algorithm that accurately detects anomalies in chest X-ray images to provide healthcare professionals with a reliable tool for diagnosing various lung conditions. To achieve this, we analysed a vast collection of X-ray images and utilised sophisticated visual analysis techniques; such as deep learning (DL) algorithms, object recognition, and categorisation models. To create our model, we used a large training dataset of chest X-rays, which provided valuable information for visualising and categorising abnormalities. We also utilised various data augmentation methods; such as scaling, rotation, and imitation; to increase the diversity of images used for training. We adopted the widely used You Only Look Once (YOLO) v8 algorithm,

SUBMITTER: Mustafa Z 

PROVIDER: S-EPMC10530162 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature