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Semi-automatic motion compensation of contrast-enhanced ultrasound images from abdominal organs for perfusion analysis

S. Schäfer, K. Nylund, F. Sævik, T. Engjom, M. Mézl, R. Jiřík, G. Dimcevski, OH. Gilja, K. Tönnies,

. 2015 ; 63 (-) : 229-37. [pub] 20141017

Jazyk angličtina Země Spojené státy americké

Typ dokumentu časopisecké články, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/bmc16021029

This paper presents a system for correcting motion influences in time-dependent 2D contrast-enhanced ultrasound (CEUS) images to assess tissue perfusion characteristics. The system consists of a semi-automatic frame selection method to find images with out-of-plane motion as well as a method for automatic motion compensation. Translational and non-rigid motion compensation is applied by introducing a temporal continuity assumption. A study consisting of 40 clinical datasets was conducted to compare the perfusion with simulated perfusion using pharmacokinetic modeling. Overall, the proposed approach decreased the mean average difference between the measured perfusion and the pharmacokinetic model estimation. It was non-inferior for three out of four patient cohorts to a manual approach and reduced the analysis time by 41% compared to manual processing.

Citace poskytuje Crossref.org

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$a This paper presents a system for correcting motion influences in time-dependent 2D contrast-enhanced ultrasound (CEUS) images to assess tissue perfusion characteristics. The system consists of a semi-automatic frame selection method to find images with out-of-plane motion as well as a method for automatic motion compensation. Translational and non-rigid motion compensation is applied by introducing a temporal continuity assumption. A study consisting of 40 clinical datasets was conducted to compare the perfusion with simulated perfusion using pharmacokinetic modeling. Overall, the proposed approach decreased the mean average difference between the measured perfusion and the pharmacokinetic model estimation. It was non-inferior for three out of four patient cohorts to a manual approach and reduced the analysis time by 41% compared to manual processing.
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$a Nylund, Kim $u National Centre for Ultrasound in Gastroenterology, Haukeland University Hospital, Bergen, Norway.
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$a Sævik, Fredrik $u Department of Clinical Medicine, University of Bergen, Norway; National Centre for Ultrasound in Gastroenterology, Haukeland University Hospital, Bergen, Norway.
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$a Engjom, Trond $u Section of Gastroenterology, Department of Medicine, Haukeland University Hospital, Bergen, Norway; National Centre for Ultrasound in Gastroenterology, Haukeland University Hospital, Bergen, Norway.
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$a Jiřík, Radovan $u Institute of Scientific Instruments of the Academy of Sciences of the Czech Republic, Brno, Czech Republic; International Clinical Research Center - Center of Biomedical Engineering, St. Anne׳s University Hospital Brno, Czech Republic.
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$a Dimcevski, Georg $u Section of Gastroenterology, Department of Medicine, Haukeland University Hospital, Bergen, Norway; National Centre for Ultrasound in Gastroenterology, Haukeland University Hospital, Bergen, Norway.
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