Atlas-based segmentation of pathological brain MR images

We propose a method for brain atlas deformation inpresence of large space-occupying tumors, based on an apriori model of lesion growth that assumes radialexpansion of the lesion from its starting point. First,an affine registration brings the atlas and the patientinto global correspondence. Then, the seeding of asynthetic tumor into the brain atlas provides a templatefor the lesion. Finally, the seeded atlas is deformed,combining a method derived from optical flow principlesand a model of lesion growth (MLG). Results show that themethod can be applied to the automatic segmentation ofstructures and substructures in brains with grossdeformation, with important medical applications inneurosurgery, radiosurgery and radiotherapy.

Professori Jaakko Uotila 18/12 1975

Kirje 18.12.1975

Atlas-manuel des maladies du larynx (2e éd.) / par le Dr L. Grünwald ; édition française par A. Castex,... P. Collinet,...

Collection : Atlas-manuels de médecine

Atlas sedimentológico de la plataforma continental peruana

Presenta un atlas sedimentológico compuesto por un texto explicativo y 19 cartas elaboradas en base a la información obtenida de 726 muestras de sedimento superficial de la plataforma continental peruana y del talud continental, extraídas entre 1976 y 1983 mediante una draga Van Veen de 0,10m2. Incluye la batimetría de la zona estudiada,la ubicación de los puntos de muestreo, la textura y granulometría del sedimento, así como el contenido tanto de carbonatos como de carbono orgánico. Las cartas son más detalladas para la plataforma que para el talud y muestran la predominancia de sedimentos arenosos en la mayor parte de la plataforma continental y del talud superior entre los 6°15' y 10°30' S, y la presencia de arcilla limosa cubriendo todo el talud continental y gran parte de la plataforma al sur de los 10°30' S. En cuanto al carbono orgánico y carbonatos se observa valores muy bajos ( <2% de carbono orgánico y <10% de carbonatos en sedimento) al norte de los 10"30'S y valores altos (>5%- 20% de carbono orgánico y hasta de 30%-50% de carbonatos) al sur de los 10°30'S.

[Trois feuilles d'un atlas géologique ou destinées à un ouvrage de géologie] / Lith. P. Bineteau

Échelle(s) : Échelle indéterminable

Atlas del Instituto del Mar del Perú

Atlas de información general sobre el Instituto del Mar del Perú sobre determinadas condiciones biológicas, físicas y químicas

Atlas-based segmentation of pathological MR brain images using a model of lesion growth.

We propose a method for brain atlas deformation in the presence of large space-occupying tumors, based on an a priori model of lesion growth that assumes radial expansion of the lesion from its starting point. Our approach involves three steps. First, an affine registration brings the atlas and the patient into global correspondence. Then, the seeding of a synthetic tumor into the brain atlas provides a template for the lesion. The last step is the deformation of the seeded atlas, combining a method derived from optical flow principles and a model of lesion growth. Results show that a good registration is performed and that the method can be applied to automatic segmentation of structures and substructures in brains with gross deformation, with important medical applications in neurosurgery, radiosurgery, and radiotherapy.

Dense deformation field estimation for atlas-based segmentation of pathological MR brain images.

Atlas registration is a recognized paradigm for the automatic segmentation of normal MR brain images. Unfortunately, atlas-based segmentation has been of limited use in presence of large space-occupying lesions. In fact, brain deformations induced by such lesions are added to normal anatomical variability and they may dramatically shift and deform anatomically or functionally important brain structures. In this work, we chose to focus on the problem of inter-subject registration of MR images with large tumors, inducing a significant shift of surrounding anatomical structures. First, a brief survey of the existing methods that have been proposed to deal with this problem is presented. This introduces the discussion about the requirements and desirable properties that we consider necessary to be fulfilled by a registration method in this context: To have a dense and smooth deformation field and a model of lesion growth, to model different deformability for some structures, to introduce more prior knowledge, and to use voxel-based features with a similarity measure robust to intensity differences. In a second part of this work, we propose a new approach that overcomes some of the main limitations of the existing techniques while complying with most of the desired requirements above. Our algorithm combines the mathematical framework for computing a variational flow proposed by Hermosillo et al. [G. Hermosillo, C. Chefd'Hotel, O. Faugeras, A variational approach to multi-modal image matching, Tech. Rep., INRIA (February 2001).] with the radial lesion growth pattern presented by Bach et al. [M. Bach Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure, J.-Ph. Thiran, Atlas-based segmentation of pathological MR brain images using a model of lesion growth, IEEE Trans. Med. Imag. 23 (10) (2004) 1301-1314.]. Results on patients with a meningioma are visually assessed and compared to those obtained with the most similar method from the state-of-the-art.