Open AccessPleural Line Detection Enhancement in Lung Ultrasonography (LUS) Based on Morphological and Adaptive Structural 2D Filter
Author(s) -
Suprijanto,
Hesty Susanti
Publication year - 2021
Publication title -
international journal of integrated engineering/international journal of integrated engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.215
H-Index - 10
eISSN - 2600-7916
pISSN - 2229-838X
DOI - 10.30880/ijie.2021.13.05.011
Subject(s) - lung , filter (signal processing) , computer vision , artificial intelligence , radiology , line (geometry) , computer science , medicine , image processing , image (mathematics) , mathematics , geometry
Lung ultrasonography (LUS) imaging has been used intensively to investigate and assess the lung’s various pathological conditions. A diagnostic system of lung abnormalities is developed to detect and localize the pleural line that can be viewed as the artifacts in LUS image. The continuous pleural line indicates one crucial pattern of a healthy lung. The regular repeated horizontal A-line marks this pattern with a fixed distance between the lines and ideally, produces a higher contrast in the lung image. This work proposes an image processing framework for enhancing pleural line detection in healthy subjects and patients as an early stage of further lung image interpretations in pneumonia patients. The proposed image processing framework is based on a top-hat morphological grayscale 2D filter with a texture structure element and an adaptive structural 2D low pass filter. This framework is evaluated for open dataset video ultrasonography (USG) of Point-of-care ultrasound (POCUS) to enhance the pleural line detection for typical video LUS acquired using a linear and a convex transducer.