Peter Maass

发表

2D and 3D MALDI-imaging: conceptual strategies for visualization and data mining.

Stefan Heldmann, Bernd Fischer, Herbert Thiele, 2014, Biochimica et biophysica acta.

Wideband approximation and wavelet transform

Peter Maass, 1992 .

Efficient Methods in Hyperthermia Treatment Planning

Peter Wust, Peter Maass, T. Köhler, 2000 .

FPGA acceleration by asynchronous parallelization for simultaneous image reconstruction and segmentation based on the Mumford-Shah regularization

Jason Cong, Peng Li, Ming Jiang, 2015, SPIE Optical Engineering + Applications.

3D Visualisierung von Organismen

Stefan Heldmann, Bernd Fischer, Theodore Alexandrov, 2012, GI-Jahrestagung.

Signal representation, uncertainty principles and localization measures

Bruno Torrésani, Chen Sagiv, Peter Maass, 2014, Adv. Comput. Math..

Modeling the influence of unbalances for ultra‐precision cutting processes

Ronny Ramlau, Peter Maass, Christina Brandt, 2011 .

Analysis of Invariance and Robustness via Invertibility of ReLU-Networks pdf

Pascal Fernsel, Peter Maass, Jens Behrmann, 2018, ArXiv.

A Survey on Surrogate Approaches to Non-negative Matrix Factorization

Pascal Fernsel, Peter Maass, P. Maass, 2018, Vietnam Journal of Mathematics.

FPGA Acceleration for Simultaneous Image Reconstruction and Segmentation based on the Mumford-Shah Regularization (Abstract Only)

Jason Cong, Peng Li, Li Shen, 2015, FPGA.

Deep Relevance Regularization: Interpretable and Robust Tumor Typing of Imaging Mass Spectrometry Data pdf

Christian Etmann, Peter Maass, Maximilian Schmidt, 2019, ArXiv.

Joint super-resolution image reconstruction and parameter identification in imaging operator: analysis of bilinear operator equations, numerical solution, and application to magnetic particle imaging pdf

Tobias Kluth, Ming Jiang, Peter Maass, 2020, Inverse Problems.

Mathematical methods in signal processing and digital image analysis

Rainer Dahlhaus, Jürgen Kurths, Jens Timmer, 2008 .

Adaptive wavelet methods and sparsity reconstruction for inverse heat conduction problems

Stephan Dahlke, Peter Maass, Thorsten Raasch, 2010, Adv. Comput. Math..

Singular Values for ReLU Layers

Emily J. King, Peter Maass, Sören Dittmer, 2018, IEEE Transactions on Neural Networks and Learning Systems.

A Deep Prior Approach to Magnetic Particle Imaging

Tobias Kluth, Peter Maass, Sören Dittmer, 2020, MLMIR@MICCAI.

FPGA Acceleration for Simultaneous Medical Image Reconstruction and Segmentation

Jason Cong, Peng Li, Pei Wang, 2014, FCCM 2014.

Reconstruction of Wideband Reflectivity Densities by Wavelet Transforms

Stephan Dahlke, Gerd Teschke, Peter Maass, 2003, Adv. Comput. Math..

Image Denoising and Quality Inspection of Micro Components Using Perona-Malik Diffusion☆

Bernd Scholz-Reiter, Iwona Piotrowska-Kurczewski, Daniel Weimer, 2013 .

Reports about 8 selected benchmark cases of model hierarchies

Michael Hintermüller, Gianluigi Rozza, Jean-David Benamou, 2018 .

Advances in Computational Mathematics, Special Issue on Localization, Diversity and Uncertainty in Signal Representations

Benjamin Ricaud, Peter Maass, Darian Onchis-Moaca, 2014 .

Method and apparatus for computer-assisted processing of a digitized image as well as machine-readable data carrier

Theodore Alexandrov, Peter Maass, Dennis Trede, 2011 .

Sparsity reconstruction in electrical impedance tomography: An experimental evaluation

Jari P. Kaipio, Bangti Jin, Tobias Kluth, 2012, J. Comput. Appl. Math..

Continuous Wavelet Methods in Signal Processing

W. Osten, Gerd Teschke, Peter Maass, 2001 .

Deep image prior for 3D magnetic particle imaging: A quantitative comparison of regularization techniques on Open MPI dataset pdf

Tobias Kluth, Peter Maass, Soren Dittmer, 2020, ArXiv.

Solving inverse problems using data-driven models

Simon R. Arridge, Ozan Öktem, Peter Maass, 2019, Acta Numerica.

On the Connection Between Adversarial Robustness and Saliency Map Interpretability pdf

Carola-Bibiane Schönlieb, Christian Etmann, Peter Maass, 2019, ICML.

Deep Learning for Trivial Inverse Problems

Peter Maass, 2019 .

FPGA Acceleration for Simultaneous Medical Image Reconstruction and Segmentation

Jason Cong, Peng Li, Ming Jiang, 2014, 2014 IEEE 22nd Annual International Symposium on Field-Programmable Custom Computing Machines.

Wavelets - Theorie und Anwendungen

Andreas Rieder, Peter Maass, Alfred K. Louis, 1994, Teubner Studienbücher Mathematik.

FROM THE FRONTIER

Peter Maass, 2004 .

Benchmark datasets for 3D MALDI- and DESI-imaging mass spectrometry

Franziska Hoffmann, Orlando Guntinas-Lichius, Kirill Veselkov, 2015, GigaScience.

On the Importance of Mathematical Methods for Analysis of MALDI-Imaging Mass Spectrometry Data

Theodore Alexandrov, Herbert Thiele, Dennis Trede, 2012, J. Integr. Bioinform..

Contour reconstruction in 3-D X-ray CT

Peter Maass, Alfred K. Louis, 1993, IEEE Trans. Medical Imaging.

Biomarker discovery in MALDI-TOF serum protein profiles using discrete wavelet transformation

Bart J. A. Mertens, Theodore Alexandrov, Herbert Thiele, 2009, Bioinform..

Deep learning for tumor classification in imaging mass spectrometry

Christian Etmann, Peter Maass, Jens Behrmann, 2017, Bioinform..

Ground Truth Free Denoising by Optimal Transport pdf

Carola-Bibiane Schönlieb, Peter Maass, Sören Dittmer, 2020, Numerical Algebra, Control and Optimization.

Wavelets: Theory and Applications

Andreas Rieder, Peter Maass, Alfred K. Louis, 1997 .

Conditional Normalizing Flows for Low-Dose Computed Tomography Image Reconstruction

Peter Maass, Maximilian Schmidt, Jens Behrmann, 2020, 2006.06270.

Detection and classification of material attributes-a practical application of wavelet analysis

Gerd Teschke, Peter Maass, Werner Willmann, 2000, IEEE Trans. Signal Process..

A partial differential equation for continuous nonlinear shrinkage filtering and its application for analyzing MMG data

Dirk A. Lorenz, Kristian Bredies, Gerd Teschke, 2004, SPIE Optics East.

Bilddatenkompression mit Wavelet—Methoden

V. Dicken, Peter Maass, Hans-Georg Stark, 1997 .

Condition monitoring of linear guideways using a matched wavelet approach

Henning Thielemann, Peter Maass, Ludger Prünte, 2008, Signal Process..

Mathematical models for surface characterization of machining processes

Oltmann Riemer, Peter Maass, Bernd Kuhfuß, 2008 .

Descent gradient methods for nonsmooth minimization problems in ill-posed problems

Dinh Nho Hào, Peter Maass, Michael Pidcock, 2016, J. Comput. Appl. Math..

A generalized conditional gradient method and its connection to an iterative shrinkage method

Dirk A. Lorenz, Kristian Bredies, Peter Maass, 2009, Comput. Optim. Appl..

Wavelet-accelerated regularization methods for hyperthermia treatment planning

Ronny Ramlau, Peter Maass, 1996, Int. J. Imaging Syst. Technol..

Spatial segmentation of imaging mass spectrometry data with edge-preserving image denoising and clustering.

Theodore Alexandrov, Herbert Thiele, Peter Maass, 2010, Journal of proteome research.

The LoDoPaB-CT Dataset: A Benchmark Dataset for Low-Dose CT Reconstruction Methods pdf

Peter Maass, Daniel Otero Baguer, Johannes Leuschner, 2019, ArXiv.

Supervised non-negative matrix factorization methods for MALDI imaging applications

Pascal Fernsel, Peter Maass, Tobias Boskamp, 2018, Bioinform..

Joint Bi-Modal Image Reconstruction Of Dot And Xct With An Extended Mumford-Shah Functional

Di He, Ming Jiang, Peter Maass, 2018, 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019).

A Projectional Ansatz to Reconstruction pdf

Peter Maass, Soren Dittmer, P. Maass, 2019, ArXiv.

Deep Learning and Inverse Problems

Simon R. Arridge, Maarten V. de Hoop, Michael Unser, 2019 .

A two-layered wavelet-based algorithm for efficient lossless and lossy image compression

Detlev Marpe, Jens Ricke, Gabi Blattermann, 2000, IEEE Trans. Circuits Syst. Video Technol..

Error analysis for filtered back projection reconstructions in Besov spaces pdf

Peter Maass, Matthias Beckmann, Judith Nickel, 2020, Inverse Problems.

Inverse Problems in Designing New Structural Materials

Iwona Piotrowska-Kurczewski, Peter Maass, Daniel Otero Baguer, 2020, Modeling, Simulation and Optimization of Complex Processes HPSC 2018.

Compounds, Drugs and Mathematical Image Processing

Dirk A. Lorenz, Peter Maass, Dennis Trede, 2010 .

Fast CG-Based Methods for Tikhonov-Phillips Regularization

Andreas Frommer, Peter Maass, A. Frommer, 1999, SIAM J. Sci. Comput..

Targeted Feature Extraction in MALDI Mass Spectrometry Imaging to Discriminate Proteomic Profiles of Breast and Ovarian Cancer

Dennis Trede, Janina Oetjen, Peter Maass, 2019, Proteomics. Clinical applications.

A robust estimation method for camera calibration with known rotation

Chen Sagiv, Peter Maass, Amir Egozi, 2015 .

The Uncertainty Principle Associated with the Continuous Shearlet Transform

Gitta Kutyniok, Stephan Dahlke, Chen Sagiv, 2008, Int. J. Wavelets Multiresolution Inf. Process..

Numerical experiments with MALDI Imaging data

Pierre Vandergheynst, Mohammad Golbabaee, Chen Sagiv, 2014, Adv. Comput. Math..

An adaptive discretization for Tikhonov-Phillips regularization with a posteriori parameter selection

Ronny Ramlau, Sergei V. Pereverzyev, Peter Maass, 2001, Numerische Mathematik.

Magnification of Label Maps With a Topology-Preserving Level-Set Method

Chen Sagiv, Theodore Alexandrov, Dennis Trede, 2012, IEEE Transactions on Image Processing.

Regularization by Architecture: A Deep Prior Approach for Inverse Problems

Tobias Kluth, Peter Maass, Sören Dittmer, 2019, Journal of Mathematical Imaging and Vision.

Tomographic methods for 2D reconstruction with the double crystal diffractometer

Peter Maass, W. Treimer, U. Feye-Treimer, 1992, IMPACT Comput. Sci. Eng..

An Optimal Control Problem in Medical Image Processing

Dirk A. Lorenz, Kristian Bredies, Peter Maass, 2005, Systems, Control, Modeling and Optimization.

A convex optimisation approach to robust observer-based H∞ control design of linear parameter-varying delayed systems

Hamid Reza Karimi, Peter Maass, P. Maass, 2008, Int. J. Model. Identif. Control..

Mathematical model of micro turning process

Hamid Reza Karimi, Peter Maass, Christina Brandt, 2009 .

EEG Signal Analysis by Continuous Wavelet Transform Techniques

Peter Maass, Alfred K. Louis, Gottfried Mayer-Kress, 1998 .

A Two-Step Soft Segmentation Procedure for MALDI Imaging Mass Spectrometry Data

Sergey I. Nikolenko, Theodore Alexandrov, Peter Maass, 2012, GCB.

Quantitative Comparison of Deep Learning-Based Image Reconstruction Methods for Low-Dose and Sparse-Angle CT Applications

Kees Joost Batenburg, Maureen van Eijnatten, Peter Maass, 2021, J. Imaging.

Is Deep Image Prior in Need of a Good Education? pdf

Bangti Jin, Peter Maass, Riccardo Barbano, 2021, ArXiv.

Regularized Orthogonal Nonnegative Matrix Factorization and K-means Clustering pdf

Pascal Fernsel, Peter Maass, P. Maass, 2021, ArXiv.

Conditional Invertible Neural Networks for Medical Imaging

Peter Maass, Johannes Leuschner, Alexander Denker, 2021, J. Imaging.

Deeply Supervised UNet for Semantic Segmentation to Assist Dermatopathological Assessment of Basal Cell Carcinoma

Nick Heilenkötter, Peter Maass, Tobias Boskamp, 2021, J. Imaging.

Generalization of the Change of Variables Formula with Applications to Residual Flows pdf

Peter Maass, Marvin N. Wright, Jens Behrmann, 2021, ArXiv.

Model uncertainty in magnetic particle imaging: Nonlinear problem formulation and model-based sparse reconstruction

Tobias Kluth, Peter Maass, P. Maass, 2017 .

A reconstruction algorithm for electrical impedance tomography based on sparsity regularization

Bangti Jin, Taufiquar Khan, Peter Maass, 2012 .

A generalized conditional gradient method for nonlinear operator equations with sparsity constraints

Dirk A. Lorenz, Kristian Bredies, Peter Maass, 2007 .

Iterated soft shrinkage with adaptive operator evaluations

Peter Maass, Thomas Bonesky, 2009 .

Wideband radar: the hyp transform

Peter Maass, P. Maass, 1989 .

A mollifier method for linear operator equations of the first kind

Peter Maass, Alfred K. Louis, P. Maass, 1990 .

Shrinkage versus deconvolution

Dirk A. Lorenz, Herbert Thiele, Peter Maass, 2007 .

Numerical methods for singular nonlinear integro-differential equations

Ernst Hairer, Peter Maass, 1987 .

Benchmark datasets for 3 D MALDI-and DESI-imaging mass spectrometry

Franziska Hoffmann, Orlando Guntinas-Lichius, Michael Becker, 2015 .

Interpolating Scaling Functions with Duals

Stephan Dahlke, Gerd Teschke, Peter Maass, 2004 .

Semismooth Newton and quasi-Newton methods in weighted ℓ1-regularization

Dinh Nho Hào, Peter Maass, Michael Pidcock, 2013 .

The x-ray transform: singular value decomposition and resolution

Peter Maass, P. Maass, 1987 .

MRI-compatible pipeline for three-dimensional MALDI imaging mass spectrometry using PAXgene fixation.

Stefan Heldmann, Michael Becker, Theodore Alexandrov, 2013, Journal of proteomics.

The Breaking Point

Peter Maass, 2005 .

Families of orthogonal two-dimensional wavelets

Peter Maass, 1996 .

Exploring three-dimensional matrix-assisted laser desorption/ionization imaging mass spectrometry data: three-dimensional spatial segmentation of mouse kidney.

Stefan Heldmann, Michael Becker, Theodore Alexandrov, 2012, Analytical chemistry.

The interior Radon transform

Peter Maass, P. Maass, 1992 .

Do Uncertainty Minimizers Attain Minimal Uncertainty?

Nir Sochen, Chen Sagiv, Peter Maass, 2010 .

Delay-range-dependent exponential H∞ synchronization of a class of delayed neural networks

Hamid Reza Karimi, Peter Maass, P. Maass, 2009 .