We propose a novel Markovian segmentation model which takes into account edge information. By construction, the model uses only pairwise interactions and its energy is submodular. Thus the exact energy minima is obtained via a max-flow/min-cut algorithm. The method has been quantitatively evaluated on synthetic images as well as on fluorescence microscopic images of live cells. © 2010 IEEE.

1 aLesko, Milan1 aKato, Zoltan1 aNagy, Antal1 aGombos, Imre1 aTörök, Zsolt1 aVígh, László1 aVígh, László1 aErcil, Aytul uhttps://www.inf.u-szeged.hu/publication/live-cell-segmentation-in-fluorescence-microscopy-via-graph-cut-001745nas a2200181 4500008004100000020002300041245007900064210006900143260003700212300001400249520109300263100002001356700001401376700001601390700001701406700002101423856011901444 2007 eng d a978-953-184-116-0 00aReconstructing some hv-convex binary images from three or four projections0 aReconstructing some hvconvex binary images from three or four pr aIstanbul, TurkeybIEEEcSep 2007 a136 - 1403 aThe reconstruction of binary images from their projections is animportant problem in discrete tomography. The main challenge in this task is that in certain cases the projections do not uniquely determine the binary image. This can yield an extremely large number of (sometimes very different) solutions. Moreover, under certain circumstances the reconstruction becomes NP-hard. A commonly used technique to reduce ambiguity and to avoid intractability is to suppose that the image to be reconstructed arises from a certain class of images having some geometrical properties. This paper studies the reconstruction problem in the class of hv-convex images having their components in so-called decomposable configurations. First, we give a negative result showing that there can be exponentially many images of the above class having the same three projections. Then, we present a heuristic that uses four projections to reconstruct an hv-convex image with decomposable configuration. We also analyze the performance of our heuristic from the viewpoints of accuracy and running time.

1 aBalázs, Péter1 aPetrou, M1 aSaramaki, T1 aErcil, Aytul1 aLončarić, Sven uhttps://www.inf.u-szeged.hu/publication/reconstructing-some-hv-convex-binary-images-from-three-or-four-projections