Dataset Information

Amygdalar shape analysis method using surface contour aligning, spherical mapping, and probabilistic subregional segmentation.

ABSTRACT: The objective of this study was to develop a reliable method for the shape analysis of the amygdala, a structure that is important in gaining a better understanding of the limbic system in the human brain. The goal of this study was threefold; to develop (1) a robust method for aligning the contour of the amygdala; (2) a reproducible method for extracting surface parameters of the amygdala using a spherical mapping technique; and (3) a standardized approach for statistical assessment and visualization of shape alterations by applying the probabilistic maps of amygdalar subregions. This technique was validated by conducting an artificial phantom study and by assessing sex-related amygdalar shape differences using T1-weighted images from healthy volunteers. In the phantom study, the region with atrophy was detected successfully through the shape analysis process. In the human study, the average radii of the centromedial (CM) subregion in the left amygdala and laterobasal (LB), superficial (SF) and CM subregions in the right amygdala were different between sexes (t-tests, p=0.02, 0.04, 0.04, and 0.002, respectively). In addition, focal regions with larger radii in amygdalae of men than those of women were found predominantly on the surfaces of bilateral SF and bilateral CM subregions, after the volumes of the amygdala had been scaled to the unit volume (1000mm(3)) (Mann-Whitney U-test, false discovery rate corrected p<0.05, clustered vertex points>25). Regions with smaller radii in amygdalae of men were found predominantly on the anterior surfaces of the right LB and SF subregions (Mann-Whitney U-test, false discovery rate corrected p<0.05, clustered vertex points>25). This is generally in agreement with previous findings from animal studies. The current method may be used for measuring subtle local shape changes of the amygdala in various psychiatric or neurologic disorders.

SUBMITTER: Kim N

PROVIDER: S-EPMC5510472 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature

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Amygdalar shape analysis method using surface contour aligning, spherical mapping, and probabilistic subregional segmentation.

Kim Namkug N Kim Hengjun J HJ Hwang Jaeuk J Yoon Sujung J SJ Cho Han Byul HB Renshaw Perry F PF Lyoo In Kyoon IK Kim Jieun E JE

Neuroscience letters 20101105 1

The objective of this study was to develop a reliable method for the shape analysis of the amygdala, a structure that is important in gaining a better understanding of the limbic system in the human brain. The goal of this study was threefold; to develop (1) a robust method for aligning the contour of the amygdala; (2) a reproducible method for extracting surface parameters of the amygdala using a spherical mapping technique; and (3) a standardized approach for statistical assessment and visuali ...[more]

PMID: 21056631

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Project description:Performing lobe-based quantitative analysis of the lung in computed tomography (CT) scans can assist in efforts to better characterize complex diseases such as chronic obstructive pulmonary disease (COPD). While airways and vessels can help to indicate the location of lobe boundaries, segmentations of these structures are not always available, so methods to define the lobes in the absence of these structures are desirable.The authors present a fully automatic lung lobe segmentation algorithm that is effective in volumetric inspiratory and expiratory computed tomography (CT) datasets. The authors rely on ridge surface image features indicating fissure locations and a novel approach to modeling shape variation in the surfaces defining the lobe boundaries. The authors employ a particle system that efficiently samples ridge surfaces in the image domain and provides a set of candidate fissure locations based on the Hessian matrix. Following this, lobe boundary shape models generated from principal component analysis (PCA) are fit to the particles data to discriminate between fissure and nonfissure candidates. The resulting set of particle points are used to fit thin plate spline (TPS) interpolating surfaces to form the final boundaries between the lung lobes.The authors tested algorithm performance on 50 inspiratory and 50 expiratory CT scans taken from the COPDGene study. Results indicate that the authors' algorithm performs comparably to pulmonologist-generated lung lobe segmentations and can produce good results in cases with accessory fissures, incomplete fissures, advanced emphysema, and low dose acquisition protocols. Dice scores indicate that only 29 out of 500 (5.85%) lobes showed Dice scores lower than 0.9. Two different approaches for evaluating lobe boundary surface discrepancies were applied and indicate that algorithm boundary identification is most accurate in the vicinity of fissures detectable on CT.The proposed algorithm is effective for lung lobe segmentation in absence of auxiliary structures such as vessels and airways. The most challenging cases are those with mostly incomplete, absent, or near-absent fissures and in cases with poorly revealed fissures due to high image noise. However, the authors observe good performance even in the majority of these cases.

Dataset Information

Amygdalar shape analysis method using surface contour aligning, spherical mapping, and probabilistic subregional segmentation.

Publications

Amygdalar shape analysis method using surface contour aligning, spherical mapping, and probabilistic subregional segmentation.

Similar Datasets

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