Cornelis H. Slump

MRI modalitiy transformation in demon registration

Nonrigid local image registration plays an important role in medical imaging. In this paper we focus on demon registration which is introduced by Thirion [1], and is comparable to fluid registration. Because demon registration cannot deal with multiple MRI modalities, we introduce a MRI modality transformation which changes the representation of a T1 scan into a T2 scan using the peaks in a joint histogram. We compare the performance between demon registration with modality transformation, demon registration with gradient images and Rueckerts [2] B-spline based free form deformation method in combination with mutual information. For this test we use perfectly aligned T1 and T2 slices from the BrainWeb database [3], which we local spherically distort. In conclusion demon registration with modality transformation gives the smallest registration errors, in case of local large spherical distortions and small bias fields.

Cognitive Small Cell Networks: Energy Efficiency and Trade-Offs

Heterogeneous networks using a mix of macrocells and small cells are foreseen as one of the solutions to meet the ever increasing mobile traffic demand. Nevertheless, a massive deployment of small cell access points (SAPs) leads also to a considerable increase in energy consumption. Spurred by growing environmental awareness and the high price of energy, it is crucial to design energy efficient wireless systems for both macrocells and small cells. In this work, we evaluate a distributed sleep-mode strategy for cognitive SAPs and we analyze the trade-off between traffic offloading from the macrocell and the energy consumption of the small cells. Using tools from stochastic geometry, we define the user discovery performance of the SAP and derive the uplink capacity of the small cells located in the Voronoi cell of a macrocell base station, accounting for the uncertainties associated with random position, density, user activity, propagation channel, network interference generated by uncoordinated activity, and the sensing scheme. In addition, we define a fundamental limit on the interference density that allows robust detection and we elucidate the relation between energy efficiency and sensing time using large deviations theory. Through the formulation of several optimization problems, we propose a framework that yields design guidelines for energy efficient small cell networks.

Speed-of-sound compensated photoacoustic tomography for accurate imaging

PURPOSE In most photoacoustic (PA) tomographic reconstructions, variations in speed-of-sound (SOS) of the subject are neglected under the assumption of acoustic homogeneity. Biological tissue with spatially heterogeneous SOS cannot be accurately reconstructed under this assumption. The authors present experimental and image reconstruction methods with which 2D SOS distributions can be accurately acquired and reconstructed, and with which the SOS map can be used subsequently to reconstruct highly accurate PA tomograms. METHODS The authors begin with a 2D iterative reconstruction approach in an ultrasound transmission tomography setting, which uses ray refracted paths instead of straight ray paths to recover accurate SOS images of the subject. Subsequently, they use the SOS distribution in a new 2D iterative PA reconstruction approach, where refraction of rays originating from PA sources is accounted for in accurately retrieving the distribution of these sources. Both the SOS reconstruction and SOS-compensated PA reconstruction methods utilize the Eikonal equation to model acoustic wavefront propagation. The equation is solved using a high accuracy fast marching method. RESULTS The authors validated the new reconstruction algorithms using numerical phantoms. For experiments they utilized the recently introduced PER-PACT method which can be used to simultaneously acquire SOS and PA data from subjects. CONCLUSIONS It is first confirmed that it is important to take SOS inhomogeneities into account in high resolution PA tomography. The iterative reconstruction algorithms, that model acoustic refractive effects, in reconstructing SOS distributions, and subsequently using these distributions to correct PA tomograms, yield artifact-free highly accurate images. The approach of using the hybrid measurement method and the new reconstruction algorithms is successful in substantially improving the quality of PA images with a minimization of blurring and artifacts.

Concomitant speed-of-sound tomography in photoacoustic imaging

We present a method to generate quantitative cross-sectional maps of acoustic propagation speed in tissue using the photoacoustic principle. The method is based on the interaction of laser-induced ultrasound from an extraneous absorber with the object under photoacoustic investigation. The propagation times of the ultrasound transients through the object at angles around 360° are measured using a multielement ultrasound detector. The geometry lends itself to fan-beam reconstruction allowing speed-of-sound tomograms to be generated. Simultaneously, conventional photoacoustic computed tomography can be performed as well. We demonstrate the concept showing results on phantoms carrying speed-of-sound distributions.

Collateral Status on Baseline Computed Tomographic Angiography and Intra-Arterial Treatment Effect in Patients with Proximal Anterior Circulation Stroke

Background and Purpose— Recent randomized trials have proven the benefit of intra-arterial treatment (IAT) with retrievable stents in acute ischemic stroke. Patients with poor or absent collaterals (preexistent anastomoses to maintain blood flow in case of a primary vessel occlusion) may gain less clinical benefit from IAT. In this post hoc analysis, we aimed to assess whether the effect of IAT was modified by collateral status on baseline computed tomographic angiography in the Multicenter Randomized Clinical Trial of Endovascular Treatment of Acute Ischemic Stroke in the Netherlands (MR CLEAN). Methods— MR CLEAN was a multicenter, randomized trial of IAT versus no IAT. Primary outcome was the modified Rankin Scale at 90 days. The primary effect parameter was the adjusted common odds ratio for a shift in direction of a better outcome on the modified Rankin Scale. Collaterals were graded from 0 (absent) to 3 (good). We used multivariable ordinal logistic regression analysis with interaction terms to estimate treatment effect modification by collateral status. Results— We found a significant modification of treatment effect by collaterals (P=0.038). The strongest benefit (adjusted common odds ratio 3.2 [95% confidence intervals 1.7–6.2]) was found in patients with good collaterals (grade 3). The adjusted common odds ratio was 1.6 [95% confidence intervals 1.0–2.7] for moderate collaterals (grade 2), 1.2 [95% confidence intervals 0.7–2.3] for poor collaterals (grade 1), and 1.0 [95% confidence intervals 0.1–8.7] for patients with absent collaterals (grade 0). Conclusions— In MR CLEAN, baseline computed tomographic angiography collateral status modified the treatment effect. The benefit of IAT was greatest in patients with good collaterals on baseline computed tomographic angiography. Treatment benefit appeared less and may be absent in patients with absent or poor collaterals. Clinical Trial Registration— URL: http://www.trialregister.nl and http://www.controlled-trials.com. Unique identifier: (NTR)1804 and ISRCTN10888758, respectively.

Successive Interference Cancellation in Heterogeneous Networks

At present, operators address the explosive growth of mobile data demand by densification of the cellular network so as to reduce the transmitter-receiver distance and to achieve higher spectral efficiency. Due to such network densification and the intense proliferation of wireless devices, modern wireless networks are interference-limited, which motivates the use of interference mitigation and coordination techniques. In this work, we develop a statistical framework to evaluate the performance of multi-tier heterogeneous networks with successive interference cancellation (SIC) capabilities, accounting for the computational complexity of the cancellation scheme and relevant network related parameters such as random location of the access points (APs) and mobile users, and the characteristics of the wireless propagation channel. We explicitly model the consecutive events of canceling interferers and we derive the success probability to cancel the n-th strongest signal and to decode the signal of interest after n cancellations. When users are connected to the AP which provides the maximum average received signal power, the analysis indicates that the performance gains of SIC diminish quickly with n and the benefits are modest for realistic values of the signal-to-interference ration (SIR). We extend the statistical model to include several association policies where distinct gains of SIC are expected: (i) maximum instantaneous SIR association, (ii) minimum load association, and (iii) range expansion. Numerical results show the effectiveness of SIC for the considered association policies. This work deepens the understanding of SIC by defining the achievable gains for different association policies in multi-tier heterogeneous networks.

Optimized anisotropic rotational invariant diffusion scheme on cone-beam CT

Cone-beam computed tomography (CBCT) is an important image modality for dental surgery planning, with high resolution images at a relative low radiation dose. In these scans the mandibular canal is hardly visible, this is a problem for implant surgery planning. We use anisotropic diffusion filtering to remove noise and enhance the mandibular canal in CBCT scans. For the diffusion tensor we use hybrid diffusion with a continuous switch (HDCS), suitable for filtering both tubular as planar image structures. We focus in this paper on the diffusion discretization schemes. The standard scheme shows good isotropic filtering behavior but is not rotational invariant, the diffusion scheme of Weickert is rotational invariant but suffers from checkerboard artifacts. We introduce a new scheme, in which we numerically optimize the image derivatives. This scheme is rotational invariant and shows good isotropic filtering properties on both synthetic as real CBCT data.

Automatic segmentation of cerebral white matter hyperintensities using only 3D FLAIR images.

Magnetic Resonance (MR) white matter hyperintensities have been shown to predict an increased risk of developing cognitive decline. However, their actual role in the conversion to dementia is still not fully understood. Automatic segmentation methods can help in the screening and monitoring of Mild Cognitive Impairment patients who take part in large population-based studies. Most existing segmentation approaches use multimodal MR images. However, multiple acquisitions represent a limitation in terms of both patient comfort and computational complexity of the algorithms. In this work, we propose an automatic lesion segmentation method that uses only three-dimensional fluid-attenuation inversion recovery (FLAIR) images. We use a modified context-sensitive Gaussian mixture model to determine voxel class probabilities, followed by correction of FLAIR artifacts. We evaluate the method against the manual segmentation performed by an experienced neuroradiologist and compare the results with other unimodal segmentation approaches. Finally, we apply our method to the segmentation of multiple sclerosis lesions by using a publicly available benchmark dataset. Results show a similar performance to other state-of-the-art multimodal methods, as well as to the human rater.

On the Calculation of the Exact Number of Zeroes of a Set of Equations

The number of simple zeroes common to a set of nonlinear equations is calculated exactly and analytically in terms of an integral taken over the boundary of the domain of interest. The integrand consists only of simple algebraic quantities containing the functions involved as well as their derivatives up to second order. The numerical feasibility is shown by some computed examples.ZusammenfassungDie genaue Anzahl der einfachen Nullstellen eines Systems nichtlinearer Gleichungen wird analytisch durch ein Integral über die Berandung des interessierenden Bereichs dargestellt. Der Integrand besteht aus einfachen algebraischen Größen, die die Funktionen samt ihren Ableitungen bis zur zweiten Ordnung enthalten. Die numerische Anwendbarkeit wird mit durchgerechneten Beispielen belegt.

An opportunistic error correction layer for OFDM systems

We propose a novel cross layer scheme to reduce the power consumption of ADCs in OFDM systems. The ADCs in a receiver can consume up to 50% of the total baseband energy. Our scheme is based on resolution-adaptive ADCs and Fountain codes. In a wireless frequency-selective channel some subcarriers have good channel conditions and others are attenuated. The key part of the proposed system is that the dynamic range of ADCs can be reduced by discarding subcarriers that are attenuated by the channel. Correspondingly, the power consumption in ADCs can be decreased. In our approach, each subcarrier carries a Fountain-encoded packet. To protect Fountain-encoded packets against bit errors, an LDPC code has been used. The receiver only decodes subcarriers (i.e., Fountain-encoded packets) with the highest SNR. Others are discarded. For that reason a LDPC code with a relatively high code rate can be used. The new error correction layer does not require perfect channel knowledge, so it can be used in a realistic system where the channel is estimated. With our approach, more than 70% of the energy consumption in the ADCs can be saved compared with the conventional IEEE 802.11a WLAN system under the same channel conditions and throughput. In addition, it requires 7.5 dB less SNR than the 802.11a system. To reduce the overhead of Fountain codes, we apply message passing and Gaussian elimination in the decoder. In this way, the overhead is 3% for a small block size (i.e., 500 packets). Using both methods results in an efficient system with low delay.