6533b833fe1ef96bd129c1a7

RESEARCH PRODUCT

Comparison of different segmentation approaches without using gold standard. Application to the estimation of the left ventricle ejection fraction from cardiac cine MRI sequences.

Patrick ClarysseJessica LebenbergChristopher CastaAlain LalandeFrédérique FrouinAlexandre CochetStéphanie Jehan-bessonAlain De CesareLaurent NajmanConstantin ConstantinidesJean CoustyChristophe TilmantMuriel LefortIrène BuvatElodie RoullotMireille GarreauLaurent Sarry

subject

MESH : Ventricular Function Left[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing02 engineering and technologyMESH: Regression AnalysisVentricular Function LeftArticleMESH: Ventricular Function Left030218 nuclear medicine & medical imagingMESH: Magnetic Resonance Imaging03 medical and health sciencesMESH : Heart0302 clinical medicine[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingMESH : Magnetic Resonance ImagingMESH : Regression Analysis0202 electrical engineering electronic engineering information engineeringHumansMedicineSegmentation[ SDV.IB ] Life Sciences [q-bio]/BioengineeringReliability (statistics)[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processing[SDV.IB] Life Sciences [q-bio]/BioengineeringEjection fractionMESH: Humansbusiness.industryMESH : HumansHeartRegression analysisPattern recognitionImage segmentationGold standard (test)Magnetic Resonance ImagingMESH: Heartmedicine.anatomical_structureVentricleRegression AnalysisA priori and a posteriori020201 artificial intelligence & image processing[SDV.IB]Life Sciences [q-bio]/BioengineeringArtificial intelligencebusinessNuclear medicine[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing

description

International audience; A statistical method is proposed to compare several estimates of a relevant clinical parameter when no gold standard is available. The method is illustrated by considering the left ventricle ejection fraction derived from cardiac magnetic resonance images and computed using seven approaches with different degrees of automation. The proposed method did not use any a priori regarding with the reliability of each method and its degree of automation. The results showed that the most accurate estimates of the ejection fraction were obtained using manual segmentations, followed by the semiautomatic methods, while the methods with the least user input yielded the least accurate ejection fraction estimates. These results were consistent with the expected performance of the estimation methods, suggesting that the proposed statistical approach might be helpful to assess the performance of estimation methods on clinical data for which no gold standard is available.

10.1109/iembs.2011.6090732https://www.hal.inserm.fr/inserm-00773261