Signal Processing and Image Analysis Techniques for Lung Ultrasound Imaging
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Applied Biosciences and Bioengineering".
Deadline for manuscript submissions: closed (15 December 2019) | Viewed by 33114
Special Issue Editors
Interests: signal processing; image analysis; ultrasound imaging; beam-forming
Interests: pulmonary medicine; intensive care; interventional ultrasound; thoracic ultrasound; non-invasive hemodynamics
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The use of ultrasound imaging for the monitoring and diagnosis of lung diseases is finally receiving the attention it deserves. Of particular interest are specific imaging artifacts, e.g., A- and B-lines. In particular, while A-lines are generally believed to be an indication of a healthy lung, B-lines have been found to correlate with several pathological conditions. In essence, these patterns carry information.
Spotting and recognising these artifacts is by itself already useful in clinical practice, and technical solutions aimed at automatically detecting and localising these patterns are of clear support for the clinician. However, deepening our knowledge on the ultrasound signals behind these artifacts, on their genesis, and on their link with the alterations of the lung structure, is crucial in order to develop quantitative signal processing and image analysis solutions able to distinguish different grades and types of diseases. The lung is in fact a very peculiar acoustic medium, and calls for a dedicated imaging approach.
This special issue focuses on the challenges we have to face if we are to make use of the full potentials of ultrasound technologies when applied to the lung. Contributions are welcome on the design, development and testing of automated artifact detection algorithms, dedicated signal processing and image analysis approaches, as well as on the fabrication of lung-mimicking phantoms, and on the clinical and safety aspects of LUS.
Assistant Professor, Dr. Libertario Demi
M.D. Gino Soldati
Guest Editors
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Keywords
- lung ultrasound
- signal processing
- image analysis
- pattern recognition
- deep learning
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