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Riegler G.,Graz University of Technology | Urschler M.,Ludwig Boltzmann Institute for Clinical Forensic Imaging | Ruther M.,Graz University of Technology | Bischof H.,Graz University of Technology | Stern D.,Graz University of Technology
Proceedings of the IEEE International Conference on Computer Vision | Year: 2016

An important initial step in many medical image analysis applications is the accurate detection of anatomical landmarks. Most successful methods for this task rely on data-driven machine learning algorithms. However, modern machine learning techniques, e.g. convolutional neural networks, need a large corpus of training data, which is often an unrealistic setting for medical datasets. In this work, we investigate how to adapt synthetic image datasets from other computer vision tasks to overcome the under-representation of the anatomical pose and shape variations in medical image datasets. We transform both data domains to a common one in such a way that a convolutional neural network can be trained on the larger synthetic image dataset and fine-tuned on the smaller medical image dataset. Our evaluations on data of MR hand and whole body CT images demonstrate that this approach improves the detection results compared to training a convolutional neural network only on the medical data. The proposed approach may also be usable in other medical applications, where training data is scarce. © 2015 IEEE. Source

von Wurmb-Schwark N.,University of Kiel | von Wurmb-Schwark N.,ForScix GmbH | Podruks E.,University of Kiel | Schwark T.,Ludwig Boltzmann Institute for Clinical Forensic Imaging | And 4 more authors.
International Journal of Legal Medicine | Year: 2015

The determination of potential sibship is a common task in routine kinship analysis, but often the putative parents are not available for analysis anymore. Then, a sibling analysis has to be conducted investigating only the potential siblings, thus reducing the power of the conclusion. In an attempt to determine meaningfulness of biostatistical calculations, 346 dizygotic twin pairs, 30 confirmed half siblings, and 112 unrelated people (to generate 6216 pair comparisons) were studied, all genetically typed using at least the Powerplex® 16 STRs. From every pair, the probabilities for a full sibship (identical parents) and half sibship (different fathers) were calculated using a commercially available computer program. Additionally, we simulated marker data for one million pairs of full sibs, half sibs, and unrelated persons each. Ninety-five percent of full sibling pairs demonstrated a likelihood ratio (LR) > 9 (W-value > 90 %) and less than 4 % of these showed a LR < 3 (W-value < 75 %) for full sibship after analysis of 15 STRs. The results for half siblings are less unambiguous. Here, only 57 % achieved a LR > 9 and 23 % a LR < 3. Regarding the unrelated pairs, more than 90 % had a LR < 1/9 and only 2 % reached a LR > 9. All in all, our results show that 15 to 20 STRs have sufficient power for analyses in kinship. Moreover, our data provide a statistical basis for the determination of the information content of a LR/W-value in a sibship case. Investigating an identical number of full siblings and unrelated pairs, it could be shown that 92 % of pairs with a LR > 9 for full sibship probability really are full siblings. So, setting a cutoff level for full sibship at LR > 9, less than 10 % of pairs will be wrongly assumed as full siblings even though they are unrelated. © 2015, Springer-Verlag Berlin Heidelberg. Source

Ith M.,University of Bern | Scheurer E.,University of Bern | Scheurer E.,Ludwig Boltzmann Institute for Clinical Forensic Imaging | Kreis R.,University of Bern | And 3 more authors.
NMR in Biomedicine | Year: 2011

Standard methods for the estimation of the postmortem interval (PMI, time since death), based on the cooling of the corpse, are limited to about 48h after death. As an alternative, noninvasive postmortem observation of alterations of brain metabolites by means of 1H MRS has been suggested for an estimation of the PMI at room temperature, so far without including the effect of other ambient temperatures. In order to study the temperature effect, localized 1H MRS was used to follow brain decomposition in a sheep brain model at four different temperatures between 4 and 26°C with repeated measurements up to 2100h postmortem. The simultaneous determination of 25 different biochemical compounds at each measurement allowed the time courses of concentration changes to be followed. A sudden and almost simultaneous change of the concentrations of seven compounds was observed after a time span that decreased exponentially from 700h at 4°C to 30h at 26°C ambient temperature. As this represents, most probably, the onset of highly variable bacterial decomposition, and thus defines the upper limit for a reliable PMI estimation, data were analyzed only up to this start of bacterial decomposition. As 13 compounds showed unequivocal, reproducible concentration changes during this period while eight showed a linear increase with a slope that was unambiguously related to ambient temperature. Therefore, a single analytical function with PMI and temperature as variables can describe the time courses of metabolite concentrations. Using the inverse of this function, metabolite concentrations determined from a single MR spectrum can be used, together with known ambient temperatures, to calculate the PMI of a corpse. It is concluded that the effect of ambient temperature can be reliably included in the PMI determination by 1H MRS. © 2011 John Wiley & Sons, Ltd. Source

Helmberger M.,Ludwig Boltzmann Research Institute | Helmberger M.,University of Graz | Pienn M.,Ludwig Boltzmann Research Institute | Urschler M.,University of Graz | And 10 more authors.
PLoS ONE | Year: 2014

Pulmonary hypertension (PH) can result in vascular pruning and increased tortuosity of the blood vessels. In this study we examined whether automatic extraction of lung vessels from contrast-enhanced thoracic computed tomography (CT) scans and calculation of tortuosity as well as 3D fractal dimension of the segmented lung vessels results in measures associated with PH. In this pilot study, 24 patients (18 with and 6 without PH) were examined with thorax CT following their diagnostic or follow-up right-sided heart catheterisation (RHC). Images of the whole thorax were acquired with a 128-slice dual-energy CT scanner. After lung identification, a vessel enhancement filter was used to estimate the lung vessel centerlines. From these, the vascular trees were generated. For each vessel segment the tortuosity was calculated using distance metric. Fractal dimension was computed using 3D box counting. Hemodynamic data from RHC was used for correlation analysis. Distance metric, the readout of vessel tortuosity, correlated with mean pulmonary arterial pressure (Spearman correlation coefficient: ρ = 0.60) and other relevant parameters, like pulmonary vascular resistance (ρ = 0.59), arterio-venous difference in oxygen (ρ = 0.54), arterial (ρ = -0.54) and venous oxygen saturation (ρ = -0.68). Moreover, distance metric increased with increase of WHO functional class. In contrast, 3D fractal dimension was only significantly correlated with arterial oxygen saturation (ρ = 0.47). Automatic detection of the lung vascular tree can provide clinically relevant measures of blood vessel morphology. Non-invasive quantification of pulmonary vessel tortuosity may provide a tool to evaluate the severity of pulmonary hypertension. © 2014 Helmberger et al. Source

Petrovic A.,Ludwig Boltzmann Institute for Clinical Forensic Imaging | Petrovic A.,University of Graz | Scheurer E.,Ludwig Boltzmann Institute for Clinical Forensic Imaging | Scheurer E.,Medical University of Graz | Stollberger R.,University of Graz
Magnetic Resonance in Medicine | Year: 2015

Purpose: T2 quantification with multiecho sequences is typically impaired by the contribution of stimulated echoes to the echo decay due to B1+ inhomogeneity and slice profile effects. In this work, a compact signal model based on the generating functions approach, which accounts for both sources of error, is presented. Methods: The generating functions (GF) approach is used to obtain a closed solution to the evolution of the transverse magnetization in an echo train, however, not in the time domain, but in the transformed z-domain. The approach is generalized by the incorporation of flip angle distribution across the refocusing slice profiles. The approach is tested by fitting the model to simulated data as well as to phantom and in vivo measurements, followed by a comparison with the common monoexponential fitting approach. Results: The fitting simulations indicate that T2 errors of up to 30% can be commonplace in a clinical setting using the monoexponential method. Conversely, the GF approach produced accurate results. Phantom and in vivo experiments showed a good agreement of the GF values with spectroscopic measurements and single-echo spin-echo sequences. Conclusion: A correction for stimulated echoes is necessary to compute comparable T2 values. The presented approach provides a solution to this issue. © 2014 Wiley Periodicals, Inc. Source

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