Information processing in medical imaging : proceedings of the ... conference
Jan 1, 2015
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 N...
Information processing in medical imaging : proceedings of the ... conference
Jan 1, 2015
This paper presents a dictionary learning-based method to segment the brain surface in post-surgical CT images of epilepsy patients following surgical implantation of electrodes. Using the electrodes identified in the post-implantation CT, surgeons r...
Information processing in medical imaging : proceedings of the ... conference
Jan 1, 2015
We investigate the problem of diagnostic lung nodule classification using thoracic Computed Tomography (CT) screening. Unlike traditional studies primarily relying on nodule segmentation for regional analysis, we tackle a more challenging problem on ...
Information processing in medical imaging : proceedings of the ... conference
Jan 1, 2015
Understanding the early dynamics of the highly folded human cerebral cortex is still an actively evolving research field teeming with unanswered questions. Longitudinal neuroimaging analysis and modeling have become the new trend to advance research ...
Information processing in medical imaging : proceedings of the ... conference
Jan 1, 2015
Sequential learning techniques, such as auto-context, that applies the output of an intermediate classifier as contextual features for its subsequent classifier has shown impressive performance for semantic segmentation. We show that these methods ca...
Information processing in medical imaging : proceedings of the ... conference
Jan 1, 2015
Automatic medical image analysis systems often start from identifying the human body part contained in the image; Specifically, given a transversal slice, it is important to know which body part it comes from, namely "slice-based bodypart recognition...
Information processing in medical imaging : proceedings of the ... conference
Jan 1, 2015
Learning representative computational models from medical imaging data requires large training data sets. Often, voxel-level annotation is unfeasible for sufficient amounts of data. An alternative to manual annotation, is to use the enormous amount o...
Information processing in medical imaging : proceedings of the ... conference
Jan 1, 2015
Brain morphometry study plays a fundamental role in medical imaging analysis and diagnosis. This work proposes a novel framework for brain cortical surface classification using Wasserstein distance, based on uniformization theory and Riemannian optim...
Studies in health technology and informatics
Jan 1, 2015
We consider the task of automatic classification of clinical incident reports using machine learning methods. Our data consists of 5448 clinical incident reports collected from the Incident Information Management System used by 7 hospitals in the sta...
Studies in health technology and informatics
Jan 1, 2015
Home monitoring of chronically ill or elderly patient can reduce frequent hospitalisations and hence provide improved quality of care at a reduced cost to the community, therefore reducing the burden on the healthcare system. Activity recognition of ...
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