18 Result(s)
within
Computer Science
Image Processing and Computer Vision
Imaging / Radiology
Kilian M. Pohl
Chapter
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Chapter and Conference Paper
3D Motion Modeling and Reconstruction of Left Ventricle Wall in Cardiac MRI
The analysis of left ventricle (LV) wall motion is a critical step for understanding cardiac functioning mechanisms and clinical diagnosis of ventricular diseases. We present a novel approach for 3D motion mod...
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Chapter and Conference Paper
Joint Data Harmonization and Group Cardinality Constrained Classification
To boost the power of classifiers, studies often increase the size of existing samples through the addition of independently collected data sets. Doing so requires harmonizing the data for demographic and acqu...
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Chapter and Conference Paper
Solving Logistic Regression with Group Cardinality Constraints for Time Series Analysis
We propose an algorithm to distinguish 3D+t images of healthy from diseased subjects by solving logistic regression based on cardinality constrained, group sparsity. This method reduces the risk of overfitting...
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Chapter and Conference Paper
FLOOR: Fusing Locally Optimal Registrations
Most registration algorithms, such as Demons [1], align two scans by iteratively finding the deformation minimizing the image dissimilarity at each location and smoothing this minimum across the image domain. ...
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Chapter and Conference Paper
Collaborative Multi Organ Segmentation by Integrating Deformable and Graphical Models
Organ segmentation is a challenging problem on which significant progress has been made. Deformable models (DM) and graphical models (GM) are two important categories of optimization based image segmentation m...
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Chapter and Conference Paper
Extracting Evolving Pathologies via Spectral Clustering
A bottleneck in the analysis of longitudinal MR scans with white matter brain lesions is the temporally consistent segmentation of the pathology. We identify pathologies in 3D+t(ime) within a spectral graph cl...
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Chapter and Conference Paper
Multinomial Probabilistic Fiber Representation for Connectivity Driven Clustering
The clustering of fibers into bundles is an important task in studying the structure and function of white matter. Existing technology mostly relies on geometrical features, such as the shape of fibers, and th...
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Chapter and Conference Paper
Validation of DRAMMS among 12 Popular Methods in Cross-Subject Cardiac MRI Registration
Cross-subject image registration is the building block for many cardiac studies. In the literature, it is often handled by voxel-wise registration methods. However, studies are lacking to show which methods ar...
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Chapter and Conference Paper
Regional Manifold Learning for Deformable Registration of Brain MR Images
We propose a method for deformable registration based on learning the manifolds of individual brain regions. Recent publications on registration of medical images advocate the use of manifold learning in order...
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Chapter and Conference Paper
Temporal Shape Analysis via the Spectral Signature
In this paper, we adapt spectral signatures for capturing morphological changes over time. Advanced techniques for capturing temporal shape changes frequently rely on first registering the sequence of shapes a...
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Chapter and Conference Paper
Joint Segmentation and Deformable Registration of Brain Scans Guided by a Tumor Growth Model
This paper presents an approach for joint segmentation and deformable registration of brain scans of glioma patients to a normal atlas. The proposed method is based on the Expectation Maximization (EM) algorit...
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Chapter and Conference Paper
Morphological Classification: Application to Cardiac MRI of Tetralogy of Fallot
This paper presents an image-based classification method, and applies it to classification of cardiac MRI scans of individuals with Tetralogy of Fallot (TOF). Clinicians frequently diagnose cardiac disease by ...
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Chapter and Conference Paper
A Unified Framework for MR Based Disease Classification
In this paper, we employ an anatomical parameterization of spatial warps to reveal structural differences between medical images of healthy control subjects and disease patients. The warps are represented as s...
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Chapter and Conference Paper
Active Mean Fields: Solving the Mean Field Approximation in the Level Set Framework
We describe a new approach for estimating the posterior probability of tissue labels. Conventional likelihood models are combined with a curve length prior on boundaries, and an approximate posterior distribut...
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Chapter and Conference Paper
Logarithm Odds Maps for Shape Representation
The concept of the Logarithm of the Odds (LogOdds) is frequently used in areas such as artificial neural networks, economics, and biology. Here, we utilize LogOdds for a shape representation that demonstrates ...
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Chapter and Conference Paper
Shape Based Segmentation of Anatomical Structures in Magnetic Resonance Images
Standard image based segmentation approaches perform poorly when there is little or no contrast along boundaries of different regions. In such cases, segmentation is largely performed manually using prior know...
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Chapter and Conference Paper
A Unifying Approach to Registration, Segmentation, and Intensity Correction
We present a statistical framework that combines the registration of an atlas with the segmentation of magnetic resonance images. We use an Expectation Maximization-based algorithm to find a solution within th...
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Chapter and Conference Paper
Incorporating Non-rigid Registration into Expectation Maximization Algorithm to Segment MR Images
The paper introduces an algorithm which allows the automatic segmentation of multi channel magnetic resonance images. We extended the Expectation Maximization-Mean Field Approximation Segmenter, to include Loc...
