Decision fusion for temporal prediction of respiratory liver motion

C. Tanner; K. Eppenhof; J. Gelderblom; G. Székely

doi:10.1109/ISBI.2014.6867966

Decision fusion for temporal prediction of respiratory liver motion

C. Tanner
, K. Eppenhof
, J. Gelderblom
, G. Székely

Biomedical Engineering

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

9 Citaten (Scopus)

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Temporal prediction of respiratory motion is required due to the latencies in image-guided therapy systems. In this study we propose to combine the outcome of four temporal prediction methods, which have different strength and weaknesses, by taking their median. Based on 25 motion traces from ultrasound liver tracking, this decision fusion provided statistically significantly better results than the individual outcomes for latencies from 150 to 1000ms. On average, RMS errors reduced by at least 50% in comparison to assuming no motion for all latencies. Furthermore it was shown that time-intensive optimization of the methods parameters to individual cases was not required, as performance from using the median parameters from the population was not significantly worse when using decision fusion.

Originele taal-2	Engels
Titel	2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, April 29-May 2, 2014, Beijing, China
Plaats van productie	Piscataway
Uitgeverij	Institute of Electrical and Electronics Engineers
Pagina's	698-701
Aantal pagina's	4
ISBN van geprinte versie	978-1-4673-1959-1
DOI's	https://doi.org/10.1109/ISBI.2014.6867966
Status	Gepubliceerd - 29 jul. 2014
Evenement	11th IEEE International Symposium on Biomedical Imaging (ISBI 2014) - Renaissance Beijing Capital Hotel, Beijing, China Duur: 29 apr. 2014 → 2 mei 2014 Congresnummer: 11 http://biomedicalimaging.org/2014/

Congres

Congres	11th IEEE International Symposium on Biomedical Imaging (ISBI 2014)
Verkorte titel	ISBI 2014
Land/Regio	China
Stad	Beijing
Periode	29/04/14 → 2/05/14
Ander	IEEE International Symposium on Biomedical Imaging
Internet adres	http://biomedicalimaging.org/2014/

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Tanner, C., Eppenhof, K., Gelderblom, J., & Székely, G. (2014). Decision fusion for temporal prediction of respiratory liver motion. In 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, April 29-May 2, 2014, Beijing, China (blz. 698-701). Artikel 6867966 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ISBI.2014.6867966

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title = "Decision fusion for temporal prediction of respiratory liver motion",

abstract = "Temporal prediction of respiratory motion is required due to the latencies in image-guided therapy systems. In this study we propose to combine the outcome of four temporal prediction methods, which have different strength and weaknesses, by taking their median. Based on 25 motion traces from ultrasound liver tracking, this decision fusion provided statistically significantly better results than the individual outcomes for latencies from 150 to 1000ms. On average, RMS errors reduced by at least 50\% in comparison to assuming no motion for all latencies. Furthermore it was shown that time-intensive optimization of the methods parameters to individual cases was not required, as performance from using the median parameters from the population was not significantly worse when using decision fusion.",

keywords = "Decision fusion, Image-guided therapy, Liver, Respiratory motion, Temporal prediction",

author = "C. Tanner and K. Eppenhof and J. Gelderblom and G. Sz{\'e}kely",

year = "2014",

month = jul,

day = "29",

doi = "10.1109/ISBI.2014.6867966",

language = "English",

isbn = "978-1-4673-1959-1",

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booktitle = "2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, April 29-May 2, 2014, Beijing, China",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "11th IEEE International Symposium on Biomedical Imaging (ISBI 2014), ISBI 2014 ; Conference date: 29-04-2014 Through 02-05-2014",

url = "http://biomedicalimaging.org/2014/",

}

Tanner, C, Eppenhof, K, Gelderblom, J & Székely, G 2014, Decision fusion for temporal prediction of respiratory liver motion. in 2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, April 29-May 2, 2014, Beijing, China., 6867966, Institute of Electrical and Electronics Engineers, Piscataway, blz. 698-701, 11th IEEE International Symposium on Biomedical Imaging (ISBI 2014), Beijing, China, 29/04/14. https://doi.org/10.1109/ISBI.2014.6867966

Decision fusion for temporal prediction of respiratory liver motion. / Tanner, C.; Eppenhof, K.; Gelderblom, J. et al.
2014 IEEE 11th International Symposium on Biomedical Imaging, ISBI 2014, April 29-May 2, 2014, Beijing, China. Piscataway: Institute of Electrical and Electronics Engineers, 2014. blz. 698-701 6867966.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

TY - GEN

T1 - Decision fusion for temporal prediction of respiratory liver motion

AU - Tanner, C.

AU - Eppenhof, K.

AU - Gelderblom, J.

AU - Székely, G.

N1 - Conference code: 11

PY - 2014/7/29

Y1 - 2014/7/29

N2 - Temporal prediction of respiratory motion is required due to the latencies in image-guided therapy systems. In this study we propose to combine the outcome of four temporal prediction methods, which have different strength and weaknesses, by taking their median. Based on 25 motion traces from ultrasound liver tracking, this decision fusion provided statistically significantly better results than the individual outcomes for latencies from 150 to 1000ms. On average, RMS errors reduced by at least 50% in comparison to assuming no motion for all latencies. Furthermore it was shown that time-intensive optimization of the methods parameters to individual cases was not required, as performance from using the median parameters from the population was not significantly worse when using decision fusion.

AB - Temporal prediction of respiratory motion is required due to the latencies in image-guided therapy systems. In this study we propose to combine the outcome of four temporal prediction methods, which have different strength and weaknesses, by taking their median. Based on 25 motion traces from ultrasound liver tracking, this decision fusion provided statistically significantly better results than the individual outcomes for latencies from 150 to 1000ms. On average, RMS errors reduced by at least 50% in comparison to assuming no motion for all latencies. Furthermore it was shown that time-intensive optimization of the methods parameters to individual cases was not required, as performance from using the median parameters from the population was not significantly worse when using decision fusion.

KW - Decision fusion

KW - Image-guided therapy

KW - Liver

KW - Respiratory motion

KW - Temporal prediction

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ER -

Decision fusion for temporal prediction of respiratory liver motion

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