Tumor-induced structural and radiometric asymmetry in brain images

This paper presents a general framework for analyzing structural and radiometric asymmetry in brain images. In a healthy brain, the left and right hemispheres are largely symmetric across the mid-sagittal plane. Brain tumors may belong to one or both of the following categories: mass-effect, in which the diseased tissue displaces healthy tissue; and infiltrating, in which healthy tissue has become diseased. Mass-effect brain tumors cause structural asymmetry by displacing healthy tissue, and may cause radiometric asymmetry in adjacent normal structures due to edema. Infiltrating tumors have a different radiometric response from healthy tissue. Thus, structural and radiometric asymmetries across the mid-sagittal plane in brain images provide important cues that tumors may be present. We have developed a framework that registers images with their reflections across the mid-sagittal plane. The registration process accounts for tissue displacement through large deformation image warping. Radiometric differences are taken into account through an additive intensity field. We present an efficient multi-scale algorithm for the joint estimation of structural and radiometric asymmetry.

[1]  R. Rabbitt,et al.  3D brain mapping using a deformable neuroanatomy. , 1994, Physics in medicine and biology.

[2]  M. Styner,et al.  Hybrid boundary-medial shape description for biologically variable shapes , 2000, Proceedings IEEE Workshop on Mathematical Methods in Biomedical Image Analysis. MMBIA-2000 (Cat. No.PR00737).

[3]  Christos Davatzikos,et al.  Spatial Transformation and Registration of Brain Images Using Elastically Deformable Models , 1997, Comput. Vis. Image Underst..

[4]  Sébastien Ourselin,et al.  Computation of the Mid-Sagittal Plane in 3D Medical Images of the Brain , 2000, ECCV.

[5]  J. Moossy,et al.  Bilateral symmetry of morphologic lesions in Alzheimer's disease. , 1988, Archives of neurology.

[6]  Michael I. Miller,et al.  Deformable templates using large deformation kinematics , 1996, IEEE Trans. Image Process..

[7]  Stephen M. Smith,et al.  Accurate Robust Symmetry Estimation , 1999, MICCAI.

[8]  Iwao Kanno,et al.  Automatic detection of the mid-sagittal plane in 3-D brain images , 1997, IEEE Transactions on Medical Imaging.

[9]  R. Bajcsy,et al.  Elastic Matching: Continuum Mechanical and Probabilistic Analysis , 1999 .

[10]  U. Grenander,et al.  Hippocampal morphometry in schizophrenia by high dimensional brain mapping. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[11]  Michael I. Miller,et al.  Volumetric transformation of brain anatomy , 1997, IEEE Transactions on Medical Imaging.

[12]  G. Christensen,et al.  Large Deformation Fluid Diffeomorphisms for Landmark and Image Matching , 1999 .

[13]  Yanxi Liu,et al.  Robust Midsagittal Plane Extraction from Coarse, Pathological 3D Images , 2000, MICCAI.

[14]  M. Miller,et al.  Statistical Analysis of Hippocampal Asymmetry in Schizophrenia , 2001, NeuroImage.

[15]  Michael I. Miller,et al.  Hierarchical brain mapping via a generalized Dirichlet solution for mapping brain manifolds , 1995, Optics & Photonics.

[16]  A. Toga,et al.  Cortical variability and asymmetry in normal aging and Alzheimer's disease. , 1998, Cerebral cortex.

[17]  Changming Sun,et al.  3D Symmetry Detection Using The Extended Gaussian Image , 1997, IEEE Trans. Pattern Anal. Mach. Intell..

[18]  S. Joshi,et al.  Early DAT is distinguished from aging by high-dimensional mapping of the hippocampus , 2000, Neurology.

[19]  Yanxi Liu,et al.  Robust midsagittal plane extraction from normal and pathological 3-D neuroradiology images , 2001, IEEE Transactions on Medical Imaging.

[20]  Martin Styner,et al.  Medial Models Incorporating Object Variability for 3D Shape Analysis , 2001, IPMI.

[21]  Paul M. Thompson,et al.  Detecting Disease-Specific Patterns of Brain Structure Using Cortical Pattern Matching and a Population-Based Probabilistic Brain Atlas , 2001, IPMI.

[22]  Neil Roberts,et al.  Automatic Analysis of Normal Brain Dissymmetry of Males and Females in MR Images , 1998, MICCAI.

[23]  S. Joshi,et al.  Mesial temporal sclerosis and temporal lobe epilepsy: MR imaging deformation-based segmentation of the hippocampus in five patients. , 2000, Radiology.

[24]  Gérard Subsol,et al.  Statistical Analysis of Dissymmetry in Volumetric Medical Images , 1997 .

[25]  D. Luenberger Optimization by Vector Space Methods , 1968 .