Márta Fidrich

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This paper presents a comparison study between 10 automatic and six interactive methods for liver segmentation from contrast-enhanced CT images. It is based on results from the "MICCAI 2007 Grand Challenge" workshop, where 16 teams evaluated their algorithms on a common database. A collection of 20 clinical images with reference segmentations was provided(More)
Segmentation of contrast-enhanced abdominal CT images is required by many clinical applications of computer aided diagnosis and therapy planning. The research on automated methods involves different organs among which the liver is the most emphasized. In the current clinical practice more images (at different phases) are acquired from the region of interest(More)
The need for fast and precise segmentation has increased recently due to the spread of systems for computer aided diagnosis and therapy planning. The manual segmentation of the liver is very time consuming, so it is desired to develop a method that can precisely segment the liver without any human interaction. In this paper we propose a fully automatic(More)
1 Abstract A method is presented to extract space curves, deened by diierential invariants, at increasing scales. The curves are considered as the intersection of two iso-surfaces in 3D, so their moving paths or orbits can be explicitly obtained in scale space as the intersection of two iso-surfaces in 4D. This method is based on a novel algorithm to search(More)
ÐAccurate and robust correspondence calculations are very important in many medical and biological applications. Often, the correspondence calculation forms part of a rigid registration algorithm, but accurate correspondences are especially important for elastic registration algorithms and for quantifying changes over time. In this paper, a new(More)
We present two approaches for automatically segmenting the spinal cord/canal from native CT images of the thorax region containing the spine. Different strategies are included to handle images where only part of the spinal column is visible. The algorithms require one seed point given on a slice located in the middle region of the spine, and the rest is(More)
Two facial models corresponding to two deceased subjects have been manually created and the two corresponding skulls have been dissected and skeletonized. These pairs of skull/ facial data have been scanned with a CT scanner, and the computed geometric three-dimensional models of both skulls and facial tissue have been built. One set of skull/facial data(More)
The ability to accurately register images of patients taken at different times is very important in many medical applications. In most cases, the main reason for registration is to measure changes, and therefore any automatic registration algorithm employed for this task must be able to cope when there are significant differences in the images. In this(More)
To provide a good basis for the registration of medical images we search for reliable feature points using a scale-space approach. Our main concern is with 2D images: we analyze corner points, de ned by di erential invariants, at increasing scales. The number and position of corner points change in the scale-extended space, which de ne moving paths or(More)