Chung, Moo K Vilalta-Gil, Victoria Lee, Hyekyoung Rathouz, Paul J Lahey, Benjamin B Zald, David H
Published in
Information processing in medical imaging : proceedings of the ... conference
We present a novel framework for characterizing paired brain networks using techniques in hyper-networks, sparse learning and persistent homology. The framework is general enough for dealing with any type of paired images such as twins, multimodal and longitudinal images. The exact nonparametric statistical inference procedure is derived on testing...
Rekik, Islem Li, Gang Lin, Weili Shen, Dinggang
Published in
Information processing in medical imaging : proceedings of the ... conference
Many methods have been developed to spatially normalize a population of brain images for estimating a mean image as a population-average atlas. However, methods for deriving a network atlas from a set of brain networks sitting on a complex manifold are still absent. Learning how to average brain networks across subjects constitutes a key step in cr...
Schabdach, Jenna Wells, William M 3rd Cho, Michael Batmanghelich, Kayhan N
Published in
Information processing in medical imaging : proceedings of the ... conference
We propose a non-parametric approach for characterizing heterogeneous diseases in large-scale studies. We target diseases where multiple types of pathology present simultaneously in each subject and a more severe disease manifests as a higher level of tissue destruction. For each subject, we model the collection of local image descriptors as sample...
Nenning, Karl-Heinz Kollndorfer, Kathrin Schöpf, Veronika Prayer, Daniela Langs, Georg
Published in
Information processing in medical imaging : proceedings of the ... conference
Functional magnetic resonance imaging group studies rely on the ability to establish correspondence across individuals. This enables location specific comparison of functional brain characteristics. Registration is often based on morphology and does not take variability of functional localization into account. This can lead to a loss of specificity...
Wong, Ken C L Summers, Ronald M Kebebew, Electron Yao, Jianhua
Published in
Information processing in medical imaging : proceedings of the ... conference
Pancreatic neuroendocrine tumors are abnormal growths of hormone-producing cells in the pancreas. Different from the brain in the skull, the pancreas in the abdomen can be largely deformed by the body posture and the surrounding organs. In consequence, both tumor growth and pancreatic motion attribute to the tumor shape difference observable from i...
Schmidt-Richberg, Alexander Guerrero, Ricardo Ledig, Christian Molina-Abril, Helena Frangi, Alejandro F Rueckert, Daniel
Published in
Information processing in medical imaging : proceedings of the ... conference
The estimation of disease progression in Alzheimer's disease (AD) based on a vector of quantitative biomarkers is of high interest to clinicians, patients, and biomedical researchers alike. In this work, quantile regression is employed to learn statistical models describing the evolution of such biomarkers. Two separate models are constructed using...
Piuze, Emmanuel Sporring, Jon Siddiqi, Kaleem
Published in
Information processing in medical imaging : proceedings of the ... conference
The method of moving frames provides powerful geometrical tools for the analysis of smoothly varying frame fields. However, in the face of missing measurements, a reconstruction problem arises, one that is largely unexplored for 3D frame fields. Here we consider the particular example of reconstructing impaired cardiac diffusion magnetic resonance ...
Wachinger, Christian Golland, Polina
Published in
Information processing in medical imaging : proceedings of the ... conference
High computational costs of manifold learning prohibit its application for large datasets. A common strategy to overcome this problem is to perform dimensionality reduction on selected landmarks and to successively embed the entire dataset with the Nyström method. The two main challenges that arise are: (i) the landmarks selected in non-Euclidean g...
Fleishman, Greg M Gutman, Boris A Fletcher, P Thomas Thompson, Paul M
Published in
Information processing in medical imaging : proceedings of the ... conference
Here we present an algorithm for the simultaneous registration of N longitudinal image pairs such that information acquired by each pair is used to constrain the registration of each other pair. More specifically, in the geodesic shooting setting for Large Deformation Diffeomorphic Metric Mappings (LDDMM) an average of the initial momenta character...
Young, Alexandra L Oxtoby, Neil P Huang, Jonathan Marinescu, Razvan V Daga, Pankaj Cash, David M Fox, Nick C Ourselin, Sebastien Schott, Jonathan M Alexander, Daniel C
...
Published in
Information processing in medical imaging : proceedings of the ... conference
The event-based model constructs a discrete picture of disease progression from cross-sectional data sets, with each event corresponding to a new biomarker becoming abnormal. However, it relies on the assumption that all subjects follow a single event sequence. This is a major simplification for sporadic disease data sets, which are highly heteroge...
