Biomedical subjects

Paul Yushkevich

Publications and source records attributed to Paul Yushkevich.

3 recordsLinked to original sources

PubMed2005

Regional structural characterization of the brain of schizophrenia patients.

RATIONALE AND OBJECTIVES: We study morphologic characteristics and age-related changes in patients with schizophrenia to investigate whether abnormal neurodevelopment and brain structure have a role in the pathophysiological course of this disease. MATERIALS AND METHODS: Our data consist of a set of cranial magnetic resonance images of 46 patients with schizophrenia and age- and sex-matched healthy controls. We deformed a template brain image to our set of subject images. Jacobian fields of these deformations were reduced to sets of 52 normalized region volumes for each subject by using a neuroanatomic atlas. Normalized regional volumes of the control and patient groups were compared by using Student t-test, and age correlation of each region volume was calculated for the two groups. All results were corrected for multiple comparisons by using permutation testing. We used a classifier based on support vector machines and a feature selection method to determine our ability to discriminate brains of controls from those of patients. RESULTS: Analysis of normalized region volumes shows enlargement of the third ventricle in patients. The age-correlation study showed a significant positive correlation in the third ventricle and right thalamus of controls, but not patients. Using an average of 6.5 features, our classifier was able to correctly identify 72% of patients and 70% of controls. CONCLUSION: In addition to enlargement of the third ventricle, brains of patients with schizophrenia show a different pattern of age-related changes.

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PubMed2003

Feature selection for shape-based classification of biological objects.

This paper introduces a method for selecting subsets of relevant statistical features in biological shape-based classification problems. The method builds upon existing feature selection methodology by introducing a heuristic that favors the geometric locality of the selected features. This heuristic effectively reduces the combinatorial search space of the feature selection problem. The new method is tested on synthetic data and on clinical data from a study of hippocampal shape in schizophrenia. Results on clinical data indicate that features describing the head of the right hippocampus are most relevant for discrimination.

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PubMed2002

Multiscale deformable model segmentation and statistical shape analysis using medial descriptions.

This paper presents a multiscale framework based on a medial representation for the segmentation and shape characterization of anatomical objects in medical imagery. The segmentation procedure is based on a Bayesian deformable templates methodology in which the prior information about the geometry and shape of anatomical objects is incorporated via the construction of exemplary templates. The anatomical variability is accommodated in the Bayesian framework by defining probabilistic transformations on these templates. The transformations, thus, defined are parameterized directly in terms of natural shape operations, such as growth and bending, and their locations. A preliminary validation study of the segmentation procedure is presented. We also present a novel statistical shape analysis approach based on the medial descriptions that examines shape via separate intuitive categories, such as global variability at the coarse scale and localized variability at the fine scale. We show that the method can be used to statistically describe shape variability in intuitive terms such as growing and bending.

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