Substance use during pregnancy and the postpartum period may have significant implications for bo... more Substance use during pregnancy and the postpartum period may have significant implications for both mother and the developing child. However, the neurobiological basis of the impact of substance use on parenting is less well understood. Here, we examined the impact of maternal substance use on cortical gray matter (GM) and white matter (WM) volumes and whether this was associated with individual differences in motivational systems of behavioral activation and inhibition. Mothers were included in the substance-using group if any addictive substance was used during pregnancy and/or in the immediate postpartum period (within 3 months of delivery). GM volume was reduced in substance-using mothers compared to non-substance-using mothers, particularly in frontal brain regions. In substance-using mothers, we also found that frontal GM was negatively correlated with levels of behavioral activation (i.e., the motivation to approach rewarding stimuli). This effect was absent in non-substance-...
Many statistical shape analysis methods produce various types of data about the analyzed surfaces... more Many statistical shape analysis methods produce various types of data about the analyzed surfaces, such as p-value maps, distance maps, 3D difference vectors and local covariance matrices. This data is often too large and thus difficult to be properly evaluated on a qualitative basis. A visual representation of this data strongly simplifies qualitative evaluation by humans and thus greatly enhances the value of the statistical results. In this paper we present a new tool for visualizing various datasets on surfaces represented as triangle meshes. Our tool, KWMeshVisu, is implemented using the Insight Toolkit ITK, www.itk.org, the Visualization Toolkit VTK, www.vtk.org, and the KWWidgets user interface toolkit, www.kwwidgets.org. The source code for KWMeshVisu, as well as input data used to generate the images in this paper, is provided with this document.
Shape analysis has become of increasing interest to the neuroimaging community due to its potenti... more Shape analysis has become of increasing interest to the neuroimaging community due to its potential to precisely locate morphological changes between healthy and pathological structures. This manuscript presents a comprehensive set of tools for the computation of 3D structural statistical shape analysis. It has been applied in several studies on brain morphometry, but can potentially be employed in other 3D shape problems. Its main limitations is the necessity of spherical topology.The input of the proposed shape analysis is a set of binary segmentation of a single brain structure, such as the hippocampus or caudate. These segmentations are converted into a corresponding spherical harmonic description (SPHARM), which is then sampled into a triangulated surfaces (SPHARM-PDM). After alignment, differences between groups of surfaces are computed using the Hotelling T^2 T2 two sample metric. Statistical p-values, both raw and corrected for multiple comparisons, result in significance ma...
The general problem addressed in this thesis is the automatic model-based segmentation of two-and... more The general problem addressed in this thesis is the automatic model-based segmentation of two-and three-dimensional objects from medical images and volumetric image data. The development of the 2-D segmentation procedure closely follows the seminal work of [Cootes et al. 1994a]. The work done being necessary to allow the extension of this technique to 3-D, presenting solutions to the difficulties arising in application to true volume data as opposed to slice-by-slice 2-D processing. The segmentation system includes both the building of statistical models and the automatic segmentation of unseen image data sets via a constrained elastic deformation of models. Geometric models are derived from a sample set of image data which has been segmented by experts; a training set. The surfaces of these binary objects are converted into a parametric surface net which is normalized to yield an invariant object-centered coordinate system. Surface descriptions are expanded into series of spherical...
This paper reviews the mathematical formalism of the least squares template matching (LSM) and pr... more This paper reviews the mathematical formalism of the least squares template matching (LSM) and presents a framework for automatic quality control of the resulting match. LSM is an iterative and area-based fitting method which replaces the conventional multi-step procedure of feature extraction followed by discrete parameter search. The technique is especially suitable for attaining very high precision or for processing low-contrast, noisy and blurred imagery as it takes into account the full information of the image signal. The automatic quality control—a component often missing in commonly used image matching methods—is achieved by self-diagnostic measures supervising the iterative procedure. The development is driven by applying image analysis in order to control patient position in radiotherapy treatment. The exact positioning of patients during radiotherapy is essential for high precision treatment. Accurate information about patient position is gained by the automated matching ...
Combining image segmentation based on statistical classification with a geometric prior has been ... more Combining image segmentation based on statistical classification with a geometric prior has been shown to significantly increase robustness and reproducibility. Using a probabilistic geometric model of sought structures and image registration serves both initialization of probability density functions and definition of spatial constraints. A strong spatial prior, however, prevents segmentation of structures that are not part of the model. In practical applications, we encounter either the presentation of new objects that cannot be modeled with a spatial prior or regional intensity changes of existing structures not explained by the model. Our driving application is the segmentation of brain tissue and tumors from three-dimensional magnetic resonance imaging (MRI). Our goal is a high-quality segmentation of healthy tissue and a precise delineation of tumor boundaries. We present an extension to an existing expectation maximization (EM) segmentation algorithm that modifies a probabili...
Proceedings of SPIE--the International Society for Optical Engineering, Jan 2, 2018
The quantification of cerebrospinal fluid (CSF) in the human brain has shown to play an important... more The quantification of cerebrospinal fluid (CSF) in the human brain has shown to play an important role in early postnatal brain developmental. Extr a-axial fluid (EA-CSF), which is characterized by the CSF in the subarachnoid space, is promising in the early detection of children at risk for neurodevelopmental disorders. Currently, though, there is no tool to extract local EA-CSF measurements in a way that is suitable for localized analysis. In this paper, we propose a novel framework for the localized, cortical surface based analysis of EA-CSF. In our proposed processing, we combine probabilistic brain tissue segmentation, cortical surface reconstruction as well as streamline based local EA-CSF quantification. For streamline computation, we employ the vector field generated by solving a Laplacian partial differential equation (PDE) between the cortical surface and the outer CSF hull. To achieve sub-voxel accuracy while minimizing numerical errors, fourth-order Runge-Kutta (RK4) int...
Proceedings. IEEE International Symposium on Biomedical Imaging, 2018
Longitudinal shape analysis has shown great potential to model anatomical processes from baseline... more Longitudinal shape analysis has shown great potential to model anatomical processes from baseline to follow-up observations. Shape regression estimates a continuous trajectory of time-discrete anatomical shapes to quantify temporal changes. The need for shape alignment and point-to-point correspondences represent limitations of current shape analysis methodologies, and present significant challenges in shape evaluation. We propose a method that estimates a continuous trajectory of continuous medial representations (CM-Rep) from a set of time-discrete observed shapes. To avoid the traditional step of aligning individual objects, shape changes are modeled via diffeomorphic ambient space deformations. Using a medial shape representation, we separately capture object pose changes and intrinsic geometry changes. Tests and validation with synthetic and real anatomical shapes demonstrate that the new method captures extrinsic shape changes as well as intrinsic shape changes encoded with CM...
Proceedings. IEEE International Symposium on Biomedical Imaging, 2018
Statistical shape analysis captures the geometric properties of a given set of shapes, obtained f... more Statistical shape analysis captures the geometric properties of a given set of shapes, obtained from medical images, by means of statistical methods. Orthognathic surgery is a type of craniofacial surgery that is aimed at correcting severe skeletal deformities in the mandible and maxilla. Methods assuming spherical topology cannot represent the class of anatomical structures exhibiting complex geometries and topologies, including the mandible. In this paper we propose methodology based on non-rigid deformations of 3D geometries to be applied to objects with thin, complex structures. We are able to accurately and quantitatively characterize bone healing at the osteotomy site as well as condylar remodeling for three orthognathic surgery cases, demonstrating the effectiveness of the proposed methodology.
Substance use during pregnancy and the postpartum period may have significant implications for bo... more Substance use during pregnancy and the postpartum period may have significant implications for both mother and the developing child. However, the neurobiological basis of the impact of substance use on parenting is less well understood. Here, we examined the impact of maternal substance use on cortical gray matter (GM) and white matter (WM) volumes and whether this was associated with individual differences in motivational systems of behavioral activation and inhibition. Mothers were included in the substance-using group if any addictive substance was used during pregnancy and/or in the immediate postpartum period (within 3 months of delivery). GM volume was reduced in substance-using mothers compared to non-substance-using mothers, particularly in frontal brain regions. In substance-using mothers, we also found that frontal GM was negatively correlated with levels of behavioral activation (i.e., the motivation to approach rewarding stimuli). This effect was absent in non-substance-...
Many statistical shape analysis methods produce various types of data about the analyzed surfaces... more Many statistical shape analysis methods produce various types of data about the analyzed surfaces, such as p-value maps, distance maps, 3D difference vectors and local covariance matrices. This data is often too large and thus difficult to be properly evaluated on a qualitative basis. A visual representation of this data strongly simplifies qualitative evaluation by humans and thus greatly enhances the value of the statistical results. In this paper we present a new tool for visualizing various datasets on surfaces represented as triangle meshes. Our tool, KWMeshVisu, is implemented using the Insight Toolkit ITK, www.itk.org, the Visualization Toolkit VTK, www.vtk.org, and the KWWidgets user interface toolkit, www.kwwidgets.org. The source code for KWMeshVisu, as well as input data used to generate the images in this paper, is provided with this document.
Shape analysis has become of increasing interest to the neuroimaging community due to its potenti... more Shape analysis has become of increasing interest to the neuroimaging community due to its potential to precisely locate morphological changes between healthy and pathological structures. This manuscript presents a comprehensive set of tools for the computation of 3D structural statistical shape analysis. It has been applied in several studies on brain morphometry, but can potentially be employed in other 3D shape problems. Its main limitations is the necessity of spherical topology.The input of the proposed shape analysis is a set of binary segmentation of a single brain structure, such as the hippocampus or caudate. These segmentations are converted into a corresponding spherical harmonic description (SPHARM), which is then sampled into a triangulated surfaces (SPHARM-PDM). After alignment, differences between groups of surfaces are computed using the Hotelling T^2 T2 two sample metric. Statistical p-values, both raw and corrected for multiple comparisons, result in significance ma...
The general problem addressed in this thesis is the automatic model-based segmentation of two-and... more The general problem addressed in this thesis is the automatic model-based segmentation of two-and three-dimensional objects from medical images and volumetric image data. The development of the 2-D segmentation procedure closely follows the seminal work of [Cootes et al. 1994a]. The work done being necessary to allow the extension of this technique to 3-D, presenting solutions to the difficulties arising in application to true volume data as opposed to slice-by-slice 2-D processing. The segmentation system includes both the building of statistical models and the automatic segmentation of unseen image data sets via a constrained elastic deformation of models. Geometric models are derived from a sample set of image data which has been segmented by experts; a training set. The surfaces of these binary objects are converted into a parametric surface net which is normalized to yield an invariant object-centered coordinate system. Surface descriptions are expanded into series of spherical...
This paper reviews the mathematical formalism of the least squares template matching (LSM) and pr... more This paper reviews the mathematical formalism of the least squares template matching (LSM) and presents a framework for automatic quality control of the resulting match. LSM is an iterative and area-based fitting method which replaces the conventional multi-step procedure of feature extraction followed by discrete parameter search. The technique is especially suitable for attaining very high precision or for processing low-contrast, noisy and blurred imagery as it takes into account the full information of the image signal. The automatic quality control—a component often missing in commonly used image matching methods—is achieved by self-diagnostic measures supervising the iterative procedure. The development is driven by applying image analysis in order to control patient position in radiotherapy treatment. The exact positioning of patients during radiotherapy is essential for high precision treatment. Accurate information about patient position is gained by the automated matching ...
Combining image segmentation based on statistical classification with a geometric prior has been ... more Combining image segmentation based on statistical classification with a geometric prior has been shown to significantly increase robustness and reproducibility. Using a probabilistic geometric model of sought structures and image registration serves both initialization of probability density functions and definition of spatial constraints. A strong spatial prior, however, prevents segmentation of structures that are not part of the model. In practical applications, we encounter either the presentation of new objects that cannot be modeled with a spatial prior or regional intensity changes of existing structures not explained by the model. Our driving application is the segmentation of brain tissue and tumors from three-dimensional magnetic resonance imaging (MRI). Our goal is a high-quality segmentation of healthy tissue and a precise delineation of tumor boundaries. We present an extension to an existing expectation maximization (EM) segmentation algorithm that modifies a probabili...
Proceedings of SPIE--the International Society for Optical Engineering, Jan 2, 2018
The quantification of cerebrospinal fluid (CSF) in the human brain has shown to play an important... more The quantification of cerebrospinal fluid (CSF) in the human brain has shown to play an important role in early postnatal brain developmental. Extr a-axial fluid (EA-CSF), which is characterized by the CSF in the subarachnoid space, is promising in the early detection of children at risk for neurodevelopmental disorders. Currently, though, there is no tool to extract local EA-CSF measurements in a way that is suitable for localized analysis. In this paper, we propose a novel framework for the localized, cortical surface based analysis of EA-CSF. In our proposed processing, we combine probabilistic brain tissue segmentation, cortical surface reconstruction as well as streamline based local EA-CSF quantification. For streamline computation, we employ the vector field generated by solving a Laplacian partial differential equation (PDE) between the cortical surface and the outer CSF hull. To achieve sub-voxel accuracy while minimizing numerical errors, fourth-order Runge-Kutta (RK4) int...
Proceedings. IEEE International Symposium on Biomedical Imaging, 2018
Longitudinal shape analysis has shown great potential to model anatomical processes from baseline... more Longitudinal shape analysis has shown great potential to model anatomical processes from baseline to follow-up observations. Shape regression estimates a continuous trajectory of time-discrete anatomical shapes to quantify temporal changes. The need for shape alignment and point-to-point correspondences represent limitations of current shape analysis methodologies, and present significant challenges in shape evaluation. We propose a method that estimates a continuous trajectory of continuous medial representations (CM-Rep) from a set of time-discrete observed shapes. To avoid the traditional step of aligning individual objects, shape changes are modeled via diffeomorphic ambient space deformations. Using a medial shape representation, we separately capture object pose changes and intrinsic geometry changes. Tests and validation with synthetic and real anatomical shapes demonstrate that the new method captures extrinsic shape changes as well as intrinsic shape changes encoded with CM...
Proceedings. IEEE International Symposium on Biomedical Imaging, 2018
Statistical shape analysis captures the geometric properties of a given set of shapes, obtained f... more Statistical shape analysis captures the geometric properties of a given set of shapes, obtained from medical images, by means of statistical methods. Orthognathic surgery is a type of craniofacial surgery that is aimed at correcting severe skeletal deformities in the mandible and maxilla. Methods assuming spherical topology cannot represent the class of anatomical structures exhibiting complex geometries and topologies, including the mandible. In this paper we propose methodology based on non-rigid deformations of 3D geometries to be applied to objects with thin, complex structures. We are able to accurately and quantitatively characterize bone healing at the osteotomy site as well as condylar remodeling for three orthognathic surgery cases, demonstrating the effectiveness of the proposed methodology.
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