Automatic Detection of B-lines in In-Vivo Lung Ultrasound

Research output: Contribution to journalJournal article – Annual report year: 2019Researchpeer-review

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Automatic Detection of B-lines in In-Vivo Lung Ultrasound. / Moshavegh, Ramin; Hansen, Kristoffer Lindskov; Moller-Sorensen, Hasse; Nielsen, Michael Bachmann; Jensen, Jørgen Arendt.

In: IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control, Vol. 66, No. 2, 2019, p. 309-317 .

Research output: Contribution to journalJournal article – Annual report year: 2019Researchpeer-review

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Moshavegh, Ramin ; Hansen, Kristoffer Lindskov ; Moller-Sorensen, Hasse ; Nielsen, Michael Bachmann ; Jensen, Jørgen Arendt. / Automatic Detection of B-lines in In-Vivo Lung Ultrasound. In: IEEE Transactions on Ultrasonics, Ferroelectrics, and Frequency Control. 2019 ; Vol. 66, No. 2. pp. 309-317 .

Bibtex

@article{3859c8bda3a144f79d4845029bce7be0,
title = "Automatic Detection of B-lines in In-Vivo Lung Ultrasound",
abstract = "This paper proposes an automatic method for accurate detection and visualization of B-lines in ultrasound lung scans, which provides a quantitative measure for the number of Blines present. All the scans used in this study were acquired using a BK3000 ultrasound scanner (BK Ultrasound, Denmark) driving a 5.5 MHz linear transducer (BK Ultrasound). Four healthy subjects and four patients after major surgery with pulmonary edema, were scanned at four locations on each lung for B-line examination. Eight sequences of 50 frames were acquired for each subject yielding 64 sequences in total. The proposed algorithm was applied to all 3200 in-vivo lung ultrasound images. The results showed that the average number of B-lines was 0.28±0.06 (Mean±Std) in scans belonging to the patients compared to 0.03±0.06 (Mean±Std) in the healthy subjects. Also, the Mann- Whitney test showed a significant difference between the two groups with p-value of 0.015, and indicating that the proposed algorithm was able to differentiate between the healthy volunteers and the patients. In conclusion, the method can be used to automatically and to quantitatively characterize the distribution of B-lines for diagnosing pulmonary edema.",
keywords = "B-lines, Segmentation, Pulmonary edema, Ultrasound imaging",
author = "Ramin Moshavegh and Hansen, {Kristoffer Lindskov} and Hasse Moller-Sorensen and Nielsen, {Michael Bachmann} and Jensen, {J{\o}rgen Arendt}",
year = "2019",
doi = "10.1109/TUFFC.2018.2885955",
language = "English",
volume = "66",
pages = "309--317",
journal = "I E E E Transactions on Ultrasonics, Ferroelectrics and Frequency Control",
issn = "0885-3010",
publisher = "Institute of Electrical and Electronics Engineers",
number = "2",

}

RIS

TY - JOUR

T1 - Automatic Detection of B-lines in In-Vivo Lung Ultrasound

AU - Moshavegh, Ramin

AU - Hansen, Kristoffer Lindskov

AU - Moller-Sorensen, Hasse

AU - Nielsen, Michael Bachmann

AU - Jensen, Jørgen Arendt

PY - 2019

Y1 - 2019

N2 - This paper proposes an automatic method for accurate detection and visualization of B-lines in ultrasound lung scans, which provides a quantitative measure for the number of Blines present. All the scans used in this study were acquired using a BK3000 ultrasound scanner (BK Ultrasound, Denmark) driving a 5.5 MHz linear transducer (BK Ultrasound). Four healthy subjects and four patients after major surgery with pulmonary edema, were scanned at four locations on each lung for B-line examination. Eight sequences of 50 frames were acquired for each subject yielding 64 sequences in total. The proposed algorithm was applied to all 3200 in-vivo lung ultrasound images. The results showed that the average number of B-lines was 0.28±0.06 (Mean±Std) in scans belonging to the patients compared to 0.03±0.06 (Mean±Std) in the healthy subjects. Also, the Mann- Whitney test showed a significant difference between the two groups with p-value of 0.015, and indicating that the proposed algorithm was able to differentiate between the healthy volunteers and the patients. In conclusion, the method can be used to automatically and to quantitatively characterize the distribution of B-lines for diagnosing pulmonary edema.

AB - This paper proposes an automatic method for accurate detection and visualization of B-lines in ultrasound lung scans, which provides a quantitative measure for the number of Blines present. All the scans used in this study were acquired using a BK3000 ultrasound scanner (BK Ultrasound, Denmark) driving a 5.5 MHz linear transducer (BK Ultrasound). Four healthy subjects and four patients after major surgery with pulmonary edema, were scanned at four locations on each lung for B-line examination. Eight sequences of 50 frames were acquired for each subject yielding 64 sequences in total. The proposed algorithm was applied to all 3200 in-vivo lung ultrasound images. The results showed that the average number of B-lines was 0.28±0.06 (Mean±Std) in scans belonging to the patients compared to 0.03±0.06 (Mean±Std) in the healthy subjects. Also, the Mann- Whitney test showed a significant difference between the two groups with p-value of 0.015, and indicating that the proposed algorithm was able to differentiate between the healthy volunteers and the patients. In conclusion, the method can be used to automatically and to quantitatively characterize the distribution of B-lines for diagnosing pulmonary edema.

KW - B-lines

KW - Segmentation

KW - Pulmonary edema

KW - Ultrasound imaging

U2 - 10.1109/TUFFC.2018.2885955

DO - 10.1109/TUFFC.2018.2885955

M3 - Journal article

VL - 66

SP - 309

EP - 317

JO - I E E E Transactions on Ultrasonics, Ferroelectrics and Frequency Control

JF - I E E E Transactions on Ultrasonics, Ferroelectrics and Frequency Control

SN - 0885-3010

IS - 2

ER -