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368


Clinical correlates of structural brain abnormalities in male schizophrenic patients [Meeting Abstract]

Chakos, MH; Schobel, SA; Gerig, G; Charles, C; Gu, H; Bradford, D; Lieberman, JA
ISI:000168411700513
ISSN: 0920-9964
CID: 1782112

Neonatal cerebral ventricle volume: A comparison of 3D ultrasound and MRI [Meeting Abstract]

Gilmore, JH; Gerig, G; Specter, B; Charles, C; Wilbur, JS; Hertzberg, BS; Kliewer, MA
ISI:000168411700522
ISSN: 0920-9964
CID: 1782122

Structural neuroimaging of psychiatry disease: Reliable and efficient automatic brain tissue segmentation for increased sensitivity [Meeting Abstract]

Park, J; Gerig, G; Chakos, MH; Vandermeulen, D; Lieberman, JA
ISI:000168411700552
ISSN: 0920-9964
CID: 1782132

Duration and severity of illness and hippocampal volume in schizophrenia patients as assessed by 3-D manual segmentation [Meeting Abstract]

Schobel, SA; Chakos, MH; Gerig, G; Bridges, HE; Gu, H; Charles, C; Lieberman, JA
ISI:000168411700558
ISSN: 0920-9964
CID: 1782142

Shape analysis of ventricular structures in mono- and dizygotic twin study [Meeting Abstract]

Styner, M; Jomier, M; Jones, DW; Weinberger, DR; Lieberman, JA; Gerig, G
ISI:000168411700565
ISSN: 0920-9964
CID: 1782152

Segmentation of hippocampal shape: Improved reliability by 2D and 3D visualization of segmented objects and of intra-/inter-rater variability [Meeting Abstract]

Gerig, G; Jomier, M; Chakos, MH; Lieberman, JA
ISI:000168411700521
ISSN: 0920-9964
CID: 1782202

Three-dimensional medial shape representation incorporating object variability [Meeting Abstract]

Styner, M; Gerig, G; Jacobs, A; Baldwin, T
This paper presents a novel processing scheme for the automatic computation of a medial shape model which is representative for an object population with shape variability. The sensitivity of medial descriptions to object variations and small boundary perturbations are fundamental problems of any skeletonization technique. These problems are approached with the computation of a model with common medial branching topology and grid sampling. This model is then used for a medial shape description of individual objects via a constrained model fit. The process starts from parametric 3D boundary representations with existing point-to-point homology between objects. The Voronoi diagram of each sampled object boundary is grouped into medial sheets and simplified by a pruning algorithm using a volumetric contribution criterion. Medial sheets are combined to form a common medial branching topology. Finally, the medial sheets are sampled and represented as meshes of medial primitives. We present new results on populations of up to 184 biological objects. For these objects the common medial branching topology is described by a small number of sheets. Despite the coarse medial sampling, a close approximation of individual objects is achieved.
ISI:000184694400094
ISSN: 1063-6919
CID: 1782382

Hybrid boundary-medial shape description for biologically variable shapes

Chapter by: Styner, Martin; Gerig, Guido
in: Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis by
[S.l.] : IEEELos Alamitos, CA, United States, 2000
pp. 235-242
ISBN:
CID: 4942052

Model-based segmentation of radiological images

Szekely, Gabor; Gerig, Guido
ORIGINAL:0009889
ISSN: 0933-1875
CID: 1783842

Hybrid boundary-medial shape description for biologically variable shapes

Styner, M.; Gerig, G.
INSPEC:6657285
ISSN: n/a
CID: 1783682