Processing of Idiopathic Pulmonary Fibrosis images based on spatial interpolation using DFT, FFT, DCT and LPF
Year: 2024
Type: article
Abstract: The work focuses on the study of existing issues with some medical images obtained from patients with Idiopathic Pulmonary Fibrosis (IPF) who have survived this COVID-19 pandemic. This study analyzes potential causes of incorrect medical diagnoses with this disease. In this regard, we employ numerical algorithms such as DFT (Discrete Fourier Transform), FFT (Fast Fourier Transform), DCT (Discrete Cosine Transform), and LPF (Low-pass filter). The main objective of this work is to demonstrate that with these numerical algorithms based on Continuous and Discrete Fourier Theory, it is possible to filter existing noise in IPF radiography images. Furthermore, it is possible to compress, enhance, and improve their resolution so that better decisions can be made in a medical protocol. In this way, it contributes to the understanding of the true images that would be used for an optimal medical diagnosis.
Authors: Irla Mantilla, Mihael Arce
Institution: National University of Engineering
Language: English
Topic: Image Enhancement Techniques
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: bronze
OpenAlex ID: W4404043675