78 research outputs found
PVR: Patch-to-Volume Reconstruction for Large Area Motion Correction of Fetal MRI
In this paper we present a novel method for the correction of motion
artifacts that are present in fetal Magnetic Resonance Imaging (MRI) scans of
the whole uterus. Contrary to current slice-to-volume registration (SVR)
methods, requiring an inflexible anatomical enclosure of a single investigated
organ, the proposed patch-to-volume reconstruction (PVR) approach is able to
reconstruct a large field of view of non-rigidly deforming structures. It
relaxes rigid motion assumptions by introducing a specific amount of redundant
information that is exploited with parallelized patch-wise optimization,
super-resolution, and automatic outlier rejection. We further describe and
provide an efficient parallel implementation of PVR allowing its execution
within reasonable time on commercially available graphics processing units
(GPU), enabling its use in the clinical practice. We evaluate PVR's
computational overhead compared to standard methods and observe improved
reconstruction accuracy in presence of affine motion artifacts of approximately
30% compared to conventional SVR in synthetic experiments. Furthermore, we have
evaluated our method qualitatively and quantitatively on real fetal MRI data
subject to maternal breathing and sudden fetal movements. We evaluate
peak-signal-to-noise ratio (PSNR), structural similarity index (SSIM), and
cross correlation (CC) with respect to the originally acquired data and provide
a method for visual inspection of reconstruction uncertainty. With these
experiments we demonstrate successful application of PVR motion compensation to
the whole uterus, the human fetus, and the human placenta.Comment: 10 pages, 13 figures, submitted to IEEE Transactions on Medical
Imaging. v2: wadded funders acknowledgements to preprin
DeepCut: Object Segmentation from Bounding Box Annotations using Convolutional Neural Networks
In this paper, we propose DeepCut, a method to obtain pixelwise object
segmentations given an image dataset labelled with bounding box annotations. It
extends the approach of the well-known GrabCut method to include machine
learning by training a neural network classifier from bounding box annotations.
We formulate the problem as an energy minimisation problem over a
densely-connected conditional random field and iteratively update the training
targets to obtain pixelwise object segmentations. Additionally, we propose
variants of the DeepCut method and compare those to a naive approach to CNN
training under weak supervision. We test its applicability to solve brain and
lung segmentation problems on a challenging fetal magnetic resonance dataset
and obtain encouraging results in terms of accuracy
Short pulse generation and high power emission of Quantum Cascade lasers
The final publication is available via https://doi.org/10.1109/IRMMW-THz.2017.8067124.A unique feature of Quantum Cascade lasers is the possibility to stack active regions. Using a three stack heterogeneous Quantum Cascade laser ultra broadband amplification and short pulse generation is demonstrated. High power output is achieved by two stacked symmetric active regions
Chronic non-specific low back pain - sub-groups or a single mechanism?
Copyright 2008 Wand and O'Connell; licensee BioMed Central Ltd.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0),
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Low back pain is a substantial health problem and has subsequently attracted a
considerable amount of research. Clinical trials evaluating the efficacy of a variety of interventions
for chronic non-specific low back pain indicate limited effectiveness for most commonly applied
interventions and approaches.
Discussion: Many clinicians challenge the results of clinical trials as they feel that this lack of
effectiveness is at odds with their clinical experience of managing patients with back pain. A
common explanation for this discrepancy is the perceived heterogeneity of patients with chronic
non-specific low back pain. It is felt that the effects of treatment may be diluted by the application
of a single intervention to a complex, heterogeneous group with diverse treatment needs. This
argument presupposes that current treatment is effective when applied to the correct patient.
An alternative perspective is that the clinical trials are correct and current treatments have limited
efficacy. Preoccupation with sub-grouping may stifle engagement with this view and it is important
that the sub-grouping paradigm is closely examined. This paper argues that there are numerous
problems with the sub-grouping approach and that it may not be an important reason for the
disappointing results of clinical trials. We propose instead that current treatment may be ineffective
because it has been misdirected. Recent evidence that demonstrates changes within the brain in
chronic low back pain sufferers raises the possibility that persistent back pain may be a problem of
cortical reorganisation and degeneration. This perspective offers interesting insights into the
chronic low back pain experience and suggests alternative models of intervention.
Summary: The disappointing results of clinical research are commonly explained by the failure of
researchers to adequately attend to sub-grouping of the chronic non-specific low back pain
population. Alternatively, current approaches may be ineffective and clinicians and researchers may
need to radically rethink the nature of the problem and how it should best be managed
Spintronics: Fundamentals and applications
Spintronics, or spin electronics, involves the study of active control and
manipulation of spin degrees of freedom in solid-state systems. This article
reviews the current status of this subject, including both recent advances and
well-established results. The primary focus is on the basic physical principles
underlying the generation of carrier spin polarization, spin dynamics, and
spin-polarized transport in semiconductors and metals. Spin transport differs
from charge transport in that spin is a nonconserved quantity in solids due to
spin-orbit and hyperfine coupling. The authors discuss in detail spin
decoherence mechanisms in metals and semiconductors. Various theories of spin
injection and spin-polarized transport are applied to hybrid structures
relevant to spin-based devices and fundamental studies of materials properties.
Experimental work is reviewed with the emphasis on projected applications, in
which external electric and magnetic fields and illumination by light will be
used to control spin and charge dynamics to create new functionalities not
feasible or ineffective with conventional electronics.Comment: invited review, 36 figures, 900+ references; minor stylistic changes
from the published versio
Automated cardiovascular magnetic resonance image analysis with fully convolutional networks
Background: Cardiovascular magnetic resonance (CMR) imaging is a standard imaging modality for assessing cardiovascular diseases (CVDs), the leading cause of death globally. CMR enables accurate quantification of the cardiac chamber volume, ejection fraction and myocardial mass, providing information for diagnosis and monitoring of CVDs. However, for years, clinicians have been relying on manual approaches for CMR image analysis, which is time consuming and prone to subjective errors. It is a major clinical challenge to automatically derive quantitative and clinically relevant information from CMR images.
Methods: Deep neural networks have shown a great potential in image pattern recognition and segmentation for a variety of tasks. Here we demonstrate an automated analysis method for CMR images, which is based on a fully convolutional network (FCN). The network is trained and evaluated on a large-scale dataset from the UK Biobank, consisting of 4,875 subjects with 93,500 pixelwise annotated images. The performance of the method has been evaluated using a number of technical metrics, including the Dice metric, mean contour distance and Hausdorff distance, as well as clinically relevant measures, including left ventricle (LV) end-diastolic volume (LVEDV) and end-systolic volume (LVESV), LV mass (LVM); right ventricle (RV) end-diastolic volume (RVEDV) and end-systolic volume (RVESV).
Results: By combining FCN with a large-scale annotated dataset, the proposed automated method achieves a high performance in segmenting the LV and RV on short-axis CMR images and the left atrium (LA) and right atrium (RA) on long-axis CMR images. On a short-axis image test set of 600 subjects, it achieves an average Dice metric of 0.94 for the LV cavity, 0.88 for the LV myocardium and 0.90 for the RV cavity. The mean absolute difference between automated measurement and manual measurement was 6.1 mL for LVEDV, 5.3 mL for LVESV, 6.9 gram for LVM, 8.5 mL for RVEDV and 7.2 mL for RVESV. On long-axis image test sets, the average Dice metric was 0.93 for the LA cavity (2-chamber view), 0.95 for the LA cavity (4-chamber view) and 0.96 for the RA cavity (4-chamber view). The performance is comparable to human inter-observer variability.
Conclusions: We show that an automated method achieves a performance on par with human experts in analysing CMR images and deriving clinically relevant measures
Guidelines and Recommendations on Yeast Cell Death Nomenclature
Elucidating the biology of yeast in its full complexity has major implications for science, medicine and industry. One of the most critical processes determining yeast life and physiology is cellular demise. However, the investigation of yeast cell death is a relatively young field, and a widely accepted set of concepts and terms is still missing. Here, we propose unified criteria for the definition of accidental, regulated, and programmed forms of cell death in yeast based on a series of morphological and biochemical criteria. Specifically, we provide consensus guidelines on the differential definition of terms including apoptosis, regulated necrosis, and autophagic cell death, as we refer to additional cell death routines that are relevant for the biology of (at least some species of) yeast. As this area of investigation advances rapidly, changes and extensions to this set of recommendations will be implemented in the years to come. Nonetheless, we strongly encourage the authors, reviewers and editors of scientific articles to adopt these collective standards in order to establish an accurate framework for yeast cell death research and, ultimately, to accelerate the progress of this vibrant field of research
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