| 1. |
- Milani, Lili, et al.
(author)
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DNA methylation for subtype classification and prediction of treatment outcome in patients with childhood acute lymphoblastic leukemia.
- 2010
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In: Blood. - : American Society of Hematology. - 0006-4971 .- 1528-0020. ; 115:6, s. 1214-25
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Journal article (peer-reviewed)abstract
- Despite improvements in the prognosis of childhood acute lymphoblastic leukemia (ALL), subgroups of patients would benefit from alternative treatment approaches. Our aim was to identify genes with DNA methylation profiles that could identify such groups. We determined the methylation levels of 1320 CpG sites in regulatory regions of 416 genes in cells from 401 children diagnosed with ALL. Hierarchical clustering of 300 CpG sites distinguished between T-lineage ALL and B-cell precursor (BCP) ALL and between the main cytogenetic subtypes of BCP ALL. It also stratified patients with high hyperdiploidy and t(12;21) ALL into 2 subgroups with different probability of relapse. By using supervised learning, we constructed multivariate classifiers by external cross-validation procedures. We identified 40 genes that consistently contributed to accurate discrimination between the main subtypes of BCP ALL and gene sets that discriminated between subtypes of ALL and between ALL and controls in pairwise classification analyses. We also identified 20 individual genes with DNA methylation levels that predicted relapse of leukemia. Thus, methylation analysis should be explored as a method to improve stratification of ALL patients. The genes highlighted in our study are not enriched to specific pathways, but the gene expression levels are inversely correlated to the methylation levels.
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| 2. |
- Gustafsson, Mats, et al.
(author)
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Cramer-Rao Lower Bounds for Inverse Scattering Problems of Multilayer Structures
- 2006
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In: Inverse Problems. - : IOP Publishing. ; 22:4, s. 1359-1380, s. 1-1
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Journal article (peer-reviewed)abstract
- In this paper, the inverse scattering problem of amultilayer structure is analysed with the Fisher information matrix and the Cramer–Rao lower bound (CRLB). The CRLB quantifies the ill-posedness of the inverse scattering problem in terms of resolution versus estimation accuracy based on the observation of noisy data. The limit for feasible inversion is identified by an asymptotic eigenvalue analysis of the Toeplitz Fisher information matrix and an application of the sampling theorem. It is shown that the resolution is inversely proportional to the bandwidth of the reflection data and that the CRLB increases linearly with the number of slabs. The transmission data give a rank-1 Fisher information matrix which can approximately reduce the CRLB by a factor of 4. Moreover, the effect of dispersive material parameters and simultaneous estimation of two material parameters are analysed. The results are illustrated with numerical examples.
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| 3. |
- Dahl, Andreas, et al.
(author)
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Traffic-generated emissions of ultrafine particles from pavement-tire interface
- 2006
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In: Atmospheric Environment. - : Elsevier. - 1352-2310 .- 1873-2844. ; 40:7, s. 1314-1323
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Journal article (peer-reviewed)abstract
- In a road simulator study, a significant source of sub-micrometer fine particles produced by the road-tire interface was observed. Since the particle size distribution and source strength is dependent on the type of tire used, it is likely that these particles largely originate from the tires, and not the road pavement. The particles consisted most likely of mineral oils from the softening filler and fragments of the carbon-reinforcing filler material (soot agglomerates). This identification was based on transmission electron microscopy studies of collected ultrafine wear particles and on-line thermal treatment using a thermodesorber. The mean particle number diameters were between 15-50 nm, similar to those found in light duty vehicle (LDV) tail-pipe exhaust. A simple box model approach was used to estimate emission factors in the size interval 15-700 nm. The emission factors increased with increasing vehicle speed, and varied between 3.7 x 10(11) and 3.2 x 10(12) particles vehicle(-1) km(-1) at speeds of 50 and 70 km h(-1). This corresponds to between 0.1-1% of tail-pipe emissions in real-world emission studies at similar speeds from a fleet of LDV with 95% gasoline and 5% diesel-fueled cars. The emission factors for particles originating from the road-tire interface were, however, similar in magnitude to particle number emission factors from liquefied petroleum gas-powered vehicles derived in test bench studies in Australia 2005. Thus the road-tire interface may be a significant contributor to particle emissions from ultraclean vehicles. (c) 2005 Elsevier Ltd. All rights reserved.
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| 4. |
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| 5. |
- Nordebo, Sven, et al.
(author)
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A Systematic Approach to Robust Preconditioning for Gradient Based Inverse Scattering Algorithms
- 2008
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In: Inverse Problems. - : IOP Publishing. - 1361-6420 .- 0266-5611. ; 24:2, s. 025027-
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Journal article (peer-reviewed)abstract
- This paper presents a systematic approach to robust preconditioning for gradient-based nonlinear inverse scattering algorithms. In particular, one- and two-dimensional inverse problems are considered where the permittivity and conductivity profiles are unknown and the input data consist of the scattered field over a certain bandwidth. A time-domain least-squares formulation is employed and the inversion algorithm is based on a conjugate gradient or quasi-Newton algorithm together with an FDTD-electromagnetic solver. A Fisher information analysis is used to estimate the Hessian of the error functional. A robust preconditioner is then obtained by incorporating a parameter scaling such that the scaled Fisher information has a unit diagonal. By improving the conditioning of the Hessian, the convergence rate of the conjugate gradient or quasi-Newton methods are improved. The preconditioner is robust in the sense that the scaling, i.e. the diagonal Fisher information, is virtually invariant to the numerical resolution and the discretization model that is employed. Numerical examples of image reconstruction are included to illustrate the efficiency of the proposed technique. © 2008 IOP Publishing Ltd.
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| 6. |
- Nordebo, Sven, et al.
(author)
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A Green's function approach to Fisher information analysis and preconditioning in microwave tomography
- 2010
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In: Inverse Problems in Science and Engineering. - : Informa UK Limited. - 1741-5977 .- 1741-5985. ; 18:8, s. 1043-1063
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Journal article (peer-reviewed)abstract
- The Fisher Information Integral Operator (FIO) and related sensitivity analysis is formulated in a variational framework that is suitable for analytical Green's function and gradient-based approaches in microwave tomography. The main application considered here is for parameter sensitivity analysis and related preconditioning for gradient-based quasi-Newton inverse scattering algorithms. In particular, the Fisher information analysis can be used as a basic principle yielding a systematic approach to robust preconditioning, where the diagonal elements of the FIO kernel are used as targets for sensitivity equalization. The infinite-dimensional formulation has several practical advantages over the finite-dimensional Fisher Information Matrix (FIM) analysis approach. In particular, the FIO approach avoids the need of making a priori assumptions about the underlying discretization of the material such as the shape, orientation and positions of the assumed image pixels. Furthermore, the integral operator and its spectrum can be efficiently approximated by using suitable quadrature methods for numerical integration. The eigenfunctions of the integral operator, corresponding to the identifiable parameters via the significant eigenvalues and the corresponding Cramr-Rao bounds, constitute a suitable global basis for sensitivity and resolution analysis. As a generic numerical example, a two-dimensional inverse electromagnetic scattering problem is analysed and illustrates the spectral decomposition and the related resolution analysis. As an application example in microwave tomography, a simulation study has been performed to illustrate the parameter sensitivity analysis and to demonstrate the effect of the related preconditioning for gradient-based quasi-Newton inverse scattering algorithms.
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| 7. |
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| 8. |
- Nordebo, Sven, et al.
(author)
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Fisher information analysis and preconditioning in electrical impedance tomography
- 2010
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In: Journal of Physics: Conference Series 224 (2010), 1742-6588. - : IOP Publishing. - 1742-6596 .- 1742-6588. ; , s. 012057-
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Conference paper (peer-reviewed)abstract
- An adjoint field approach is used to formulate a general numerical framework for Fisher information based sensitivity analysis in electrical impedance tomography. General expressions are given for the gradients used in standard least squares optimization, i.e., the Jacobian related to the forward problem, and it is shown that these gradient expressions are consistent with commonly used electrode models such as the shunt model and the complete electrode model. By using the adjoint field formulations together with a variational analysis, it is also shown how the computation of the Fisher information can be integrated with the gradient calculations used for optimization. It is furthermore described how the Fisher information analysis and the related sensitivity map can be used in a preconditioning strategy to obtain a well balanced parameter sensitivity and improved performance for gradient based quasi-Newton optimization algorithms in electrical impedance tomography. Numerical simulations as well as reconstructions based on experimental data are used to illustrate the sensitivity analysis and the performance of the improved inversion algorithm in a four-electrode measurement set-up.
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| 9. |
- Nordebo, Sven, et al.
(author)
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Fisher information analysis in microwave tomography
- 2009
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In: The Third International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP09). - 9781424451807 ; , s. 217-220
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Conference paper (peer-reviewed)
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| 10. |
- Nordebo, Sven, et al.
(author)
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On the Design of Optimal Measurements for Antenna Near-Field Imaging Problems
- 2006
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In: AIP Conference Proceedings. - : AIP. ; 834, s. 234-249
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Conference paper (peer-reviewed)abstract
- A mathematical framework is introduced for optimization of antenna near-field imaging problems, based on the multipole expansion of the electromagnetic field, the Fisher information to quantify the quality of data and use of modern interior point convex optimization techniques. We consider the general problem of optimizing the measurement sensor allocation for parameter estimation in distributed systems, and in particular the problem of optimizing the measurement set-up for antenna near-field estimation. As an application example for antenna near-field imaging, we consider a relevant measurement set-up using cylindrical probing coordinates. The convex optimization problem is examined using duality theory, and it is shown that several structural properties of the optimal measurement problem can be exploited in developing an efficient interior point optimization method. In particular, we show that the cylindrical measurement set-up yields a Fisher information matrix with block diagonal structure, a feature which can be directly exploited in the optimization algorithm by reducing the number of dual decision variables.
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