"2"^^ . . "Fabi\u00E1n, Tom\u00E1\u0161" . . "Sofia" . "194069" . . "11th International Multidisciplinary Scientific GeoConference SGEM 2011 (1.-3. d\u00EDl)" . "DEVELOPMENT OF METHODS FOR THE PROCESSING OF MEDICAL IMAGES USING GENETIC ALGORITHMS"@en . "2"^^ . "STEF92 Technology Ltd." . . . . "Albena, Varna" . . . "1314-2704" . "2011-06-20+02:00"^^ . "RIV/61989100:27240/11:86079622" . . "27240" . "DEVELOPMENT OF METHODS FOR THE PROCESSING OF MEDICAL IMAGES USING GENETIC ALGORITHMS" . . . "medical imaging, image segmentation, active contour, GVF snake, SOMA"@en . "In this paper we deal with analysis and evaluation of objects of interest which are present in ultrasound images as well as assessment of the progress or regressions that occurred in these objects. These objects are highly significant from a medicinal perspective and include atherosclerostic plaque in carotid arteries, the intima-media thickness in the distal part of the common carotid artery, cerebral cortex size and brain stem findings in cases of Parkinson disease. Here, we describe procedures employing combination of common methods and evolutionary algorithms for recognizing points of interest in the images that may serve in determining various parameters and properties of analyzed objects. We use the evolutionary algorithms to optimize the energy function of deformable models used to approximate the locations and shapes of object boundaries in images. We suppose that evolutionary algorithms can be used to find the desired global solution."@en . "DEVELOPMENT OF METHODS FOR THE PROCESSING OF MEDICAL IMAGES USING GENETIC ALGORITHMS" . "[ADF848EF7406]" . . . . . "Z(MSM6198910027)" . "8"^^ . . "Li\u010Dev, La\u010Dezar" . "000307366300065" . . "RIV/61989100:27240/11:86079622!RIV14-MSM-27240___" . . . "DEVELOPMENT OF METHODS FOR THE PROCESSING OF MEDICAL IMAGES USING GENETIC ALGORITHMS"@en . . "In this paper we deal with analysis and evaluation of objects of interest which are present in ultrasound images as well as assessment of the progress or regressions that occurred in these objects. These objects are highly significant from a medicinal perspective and include atherosclerostic plaque in carotid arteries, the intima-media thickness in the distal part of the common carotid artery, cerebral cortex size and brain stem findings in cases of Parkinson disease. Here, we describe procedures employing combination of common methods and evolutionary algorithms for recognizing points of interest in the images that may serve in determining various parameters and properties of analyzed objects. We use the evolutionary algorithms to optimize the energy function of deformable models used to approximate the locations and shapes of object boundaries in images. We suppose that evolutionary algorithms can be used to find the desired global solution." .