12,105 research outputs found
Multi-Atlas Segmentation using Partially Annotated Data: Methods and Annotation Strategies
Multi-atlas segmentation is a widely used tool in medical image analysis,
providing robust and accurate results by learning from annotated atlas
datasets. However, the availability of fully annotated atlas images for
training is limited due to the time required for the labelling task.
Segmentation methods requiring only a proportion of each atlas image to be
labelled could therefore reduce the workload on expert raters tasked with
annotating atlas images. To address this issue, we first re-examine the
labelling problem common in many existing approaches and formulate its solution
in terms of a Markov Random Field energy minimisation problem on a graph
connecting atlases and the target image. This provides a unifying framework for
multi-atlas segmentation. We then show how modifications in the graph
configuration of the proposed framework enable the use of partially annotated
atlas images and investigate different partial annotation strategies. The
proposed method was evaluated on two Magnetic Resonance Imaging (MRI) datasets
for hippocampal and cardiac segmentation. Experiments were performed aimed at
(1) recreating existing segmentation techniques with the proposed framework and
(2) demonstrating the potential of employing sparsely annotated atlas data for
multi-atlas segmentation
From Data Fusion to Knowledge Fusion
The task of {\em data fusion} is to identify the true values of data items
(eg, the true date of birth for {\em Tom Cruise}) among multiple observed
values drawn from different sources (eg, Web sites) of varying (and unknown)
reliability. A recent survey\cite{LDL+12} has provided a detailed comparison of
various fusion methods on Deep Web data. In this paper, we study the
applicability and limitations of different fusion techniques on a more
challenging problem: {\em knowledge fusion}. Knowledge fusion identifies true
subject-predicate-object triples extracted by multiple information extractors
from multiple information sources. These extractors perform the tasks of entity
linkage and schema alignment, thus introducing an additional source of noise
that is quite different from that traditionally considered in the data fusion
literature, which only focuses on factual errors in the original sources. We
adapt state-of-the-art data fusion techniques and apply them to a knowledge
base with 1.6B unique knowledge triples extracted by 12 extractors from over 1B
Web pages, which is three orders of magnitude larger than the data sets used in
previous data fusion papers. We show great promise of the data fusion
approaches in solving the knowledge fusion problem, and suggest interesting
research directions through a detailed error analysis of the methods.Comment: VLDB'201
Online Forum Thread Retrieval using Pseudo Cluster Selection and Voting Techniques
Online forums facilitate knowledge seeking and sharing on the Web. However,
the shared knowledge is not fully utilized due to information overload. Thread
retrieval is one method to overcome information overload. In this paper, we
propose a model that combines two existing approaches: the Pseudo Cluster
Selection and the Voting Techniques. In both, a retrieval system first scores a
list of messages and then ranks threads by aggregating their scored messages.
They differ on what and how to aggregate. The pseudo cluster selection focuses
on input, while voting techniques focus on the aggregation method. Our combined
models focus on the input and the aggregation methods. The result shows that
some combined models are statistically superior to baseline methods.Comment: The original publication is available at
http://www.springerlink.com/. arXiv admin note: substantial text overlap with
arXiv:1212.533
The narcissism of national solipsism:civic nationalism and sub-state formation processes in Scotland
This paper accounts for the lengthy emergence of sub-state nationalism in Scotland by locating it within British state formation processes. A spiral process of compromise and challenge characterises Scotland’s constantly evolving position within the United Kingdom. Despite the legalistic dilemmas that each challenge poses, the fissiparous process of sub-state remaking is rarely about ‘the constitution’ so much as shifts in the We–I balance expressed by deeply contested political and moral differences between formally equal but distinct partners of the ‘union state’. Relieved of direct responsibility for the organised violence of great power politics, and notwithstanding the formative role of Scots in managing the British empire, a charismatic Scottish we-ideal claims for itself the peaceful, humanist and egalitarian virtues of civic nationalism in contrast to the perfidious Machiavellianism at the heart of UK state power
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