6533b832fe1ef96bd129aa88

RESEARCH PRODUCT

Definition of a mutual reference shape based on information theory and active contours

Stéphanie Jehan-bessonChristophe TilmantAlain De CesareAlain LalandeAlexandre CochetJean CoustyJessica LebenbergMuriel LefortPatrick ClarysseRégis ClouardLaurent NajmanLaurent SarryFrédérique FrouinMireille Garreau

subject

[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image Processingsegmentation evaluation[ INFO.INFO-IM ] Computer Science [cs]/Medical Imaging[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processingaverage shape[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging[INFO.INFO-IM] Computer Science [cs]/Medical ImagingComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingactive contours[SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV]shape gradientsImage processingcardiac MRI.[INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][ INFO.INFO-TI ] Computer Science [cs]/Image Processingshape optimizationcardiac MRI[INFO.INFO-IM]Computer Science [cs]/Medical Imaging[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/Imaging[SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processinginformation theory

description

In this paper, we propose to consider the estimation of a reference shape from a set of different segmentation results using both active contours and information theory. The reference shape is then defined as the minimum of a criterion that benefits from both the mutual information and the joint entropy of the input segmentations. This energy criterion is here justified using similarities between information theory quantities and area measures, and presented in a continuous variational framework. This framework brings out some interesting evaluation measures such as the specificity and sensitivity. In order to solve this shape optimization problem, shape derivatives are computed for each term of the criterion and interpreted as an evolution equation of an active contour. A mutual shape is then estimated together with the sensitivity and specificity. Some synthetical examples allow us to cast the light on the difference between our mutual shape and an average shape. The applicability and robustness of our framework has also been tested for the evaluation of different segmentation methods of the left ventricular cavity from cardiac MRI.

https://hal.archives-ouvertes.fr/hal-00844144/document