Medical Imaging Analysis using Computer-Assisted Technologies
Qamber Abbas, Muhammad Qasim Yasin, Muhammad Asif, Saddam Hussain · 2022 Global Conference on Robotics, Artificial Intelligence and Information Technology (GCRAIT) · 2022
Analysis of medical images using computer-assisted technologies has been on the rise in the recent past. Machine and deep learning have proven to be reliable in the biomedical field, providing solutions to the analysis of many health issues. Machine learning platforms are a great tool in obtaining and analyzing medical images especially when a considerable implementation effort is made. Following this, efforts have been put into research pertaining to the application of this technology to give reliable results as far as diagnosis and images are concerned. This paper looks at developing a model that will be used in medical imaging technology using machine learning. The main aim is to come up with a model that can be adopted and simplify medical imaging. This work provides a machine learning pipeline to be applied in medical imaging such as regression, segmentation, generation of images, and learning applications. The components of this model include data loading, augmentation of data, networks build-ups, loss functions, and evaluating matrices that take advantage of medical image analysis. This model will allow researchers and medical practitioners to adopt a fast and efficient method to be applied in medical imaging.