J. Modersitzki

• Professor
• Professor at University of Lübeck

Many inverse problems are phrased as optimization problems in which the objective function is the sum of a data-fidelity term and a regularization. Often, the Hessian of the fidelity term is computationally unavailable while the Hessian of the regularizer allows for cheap matrix-vector products. In this paper, we study an L-BFGS method that takes a...

Artificial intelligence has been used with great success for the segmentation of anatomical structures in medical imaging. We use these achievements to improve classical registration schemes. Particularly, we derive geometrical features such as centroids and principal axes of segments and use those in a combined approach. A smart filtering of the f...

ℓ-BFGS is the state-of-the-art optimization method for many large scale inverse problems. It has a small memory footprint and achieves superlinear convergence. The method approximates Hessian based on an initial approximation and an update rule that models current local curvature information. The initial approximation greatly affects the scaling of...

L-BFGS is the state-of-the-art optimization method for many large scale inverse problems. It has a small memory footprint and achieves superlinear convergence. The method approximates Hessian based on an initial approximation and an update rule that models current local curvature information. The initial approximation greatly affects the scaling of...

A novel crack capable image registration framework is proposed. The approach is designed for registration problems suffering from cracks, gaps, or holes. The approach enables discontinuous transformation fields and also features an automatically computed crack indicator function and therefore does not require a pre-segmentation. The new approach is...

A novel crack capable image registration framework is proposed. The approach is designed for registration problems suffering from cracks, gaps, or holes. The approach enables discontinuous transformation fields and also features an automatically computed crack indicator function and therefore does not require a pre-segmentation. The new approach is...

Multilevel strategies are an integral part of many image registration algorithms. These strategies are very well-known for avoiding undesirable local minima, providing an outstanding initial guess, and reducing overall computation time. State-of-the-art multilevel strategies build a hierarchy of dis-cretization in the spatial dimensions. In this pa...

Multilevel strategies are an integral part of many image registration algorithms. These strategies are very well-known for avoiding undesirable local minima, providing an outstanding initial guess, and reducing overall computation time. State-of-the-art multilevel strategies build a hierarchy of discretization in the spatial dimensions. In this pap...

Quantification of image similarity is a common problem in image processing. For pairs of two images, a variety of options is available and well-understood. However, some applications such as dynamic imaging or serial sectioning involve the analysis of image sequences and thus require a simultaneous and unbiased comparison of many images. This paper...

Image registration, especially the quantification of image similarity, is an important task in image processing. Various approaches for the comparison of two images are discussed in the literature. However, although most of these approaches perform very well in a two image scenario, an extension to a multiple images scenario deserves attention. In...

The comparison of images is an important task in image processing. For a comparison of two images, a variety of measures has been suggested. However, applications such as dynamic imaging or serial sectioning provide a series of many images to be compared. When these images are to be registered, the standard approach is to sequentially align the j-t...

Image registration, especially the quantification of image similarity, is an important task in image processing. Various approaches for the comparison of two images are discussed in the literature. However, although most of these approaches perform very well in a two image scenario, an extension to a multiple images scenario deserves attention. In...

The comparison of images is an important task in image processing. For a comparison of two images, a variety of measures has been suggested. However, applications such as dynamic imaging or serial sectioning provide a series of many images to be compared. When these images are to be registered, the standard approach is to sequentially align the j‐t...

The automatic detection and accurate localization of landmarks is a crucial task in medical imaging. It is necessary for tasks like diagnosis, surgical planning, and post-operative assessment. A common approach to localize multiple landmarks is to combine multiple independent localizers for individual landmarks with a spatial regularizer, e.g., a c...

One-compartment models are widely used to quantify hemodynamic parameters such as perfusion, blood volume and mean transit time. These parameters are routinely used for clinical diagnosis and monitoring of disease development and are thus of high relevance. However, it is known that common estimation techniques are discretization dependent and valu...

We present a novel algorithm for the registration of pulmonary CT scans. Our method is designed for large respiratory motion by integrating sparse keypoint correspondences into a dense continuous optimization framework. The detection of keypoint correspondences enables robustness against large deformations by jointly optimizing over a large number...

Quantification of image similarity is a common problem in image processing. For pairs of two images, a variety of options is available and well-understood. However, some applications such as dynamic imaging or serial sectioning involve the analysis of image sequences and thus require a simultaneous and unbiased comparison of many images. This paper...

The detection and localization of single or multiple landmarks is a crucial task in medical imaging. It is often required as initialization for other tasks like segmentation or registration. A common approach to localize multiple landmarks is to exploit their spatial correlations, e.g., by using a conditional random field (CRF) to incorporate geome...

Accurate optic disc (OD) segmentation and fovea detection in retinal fundus images are crucial for diagnosis in ophthalmology. We propose a robust and broadly applicable algorithm for automated, robust, reliable and consistent fovea detection based on OD segmentation. The OD segmentation is performed with morphological operations and Fuzzy C Means...

Image registration is a central problem in a variety of areas involving imaging techniques and is known to be challenging and ill-posed. Regularization functionals based on hyperelasticity provide a powerful mechanism for limiting the ill-posedness. A key feature of hyperelastic image registration approaches is their ability to model large deformat...

This paper presents a generic approach to highly efficient image registration in two and three dimensions. Both monomodal and multimodal registration problems are considered. We focus on the important class of affine-linear transformations in a derivative-based optimization framework. Our main contribution is an explicit formulation of the objectiv...

A fast and robust method for T1 estimation in MRI is the so-called variable flip angle technique. We introduce a novel family of T1 reconstruction methods from data acquired with various flip angles and propose a family member which combines the robustness of a nonlinear- with the computational advantages of a linear reconstruction. The constructed...

In this paper a novel Large Deformation Diffeomorphic Metric Mapping (LDDMM) scheme is presented which has significantly lower computational and memory demands than standard LDDMM but achieves the same accuracy. We exploit the smoothness of velocities and transformations by using a coarser discretization compared to the image resolution. This reduc...

This article presents a brief review on nonlinear registration techniques based on a variational formulation. The main advantages of this setting are its great modeling potential and its modular setting. This enables easy changes and adaptations for fine-tuning for particular applications. Furthermore, this setting also enables the integration of a...

The aim of this paper is to establish a nonlinear variational approach to the reconstruction of moving density images from indirect dynamic measurements. Our approach is to model the dynamics as a hyperelastic deformation of an initial density including preservation of mass. Consequently we derive a variational regularization model for the reconstr...

Objective: Image Registration of whole slide histology images allows the fusion of fine-grained information - like different immunohistochemical stains - from neighboring tissue slides. Traditionally, pathologists fuse this information by looking subsequently at one slide at a time. If the slides are digitized and accurately aligned at cell-level,...

Introduction: Over the last decade endovascular stenting of aortic aneurysm (EVAR) has been developed from single centre experiences to a standard procedure. With increasing clinical expertise and medical technology advances treatment of even complex aneurysms are feasible by endovascular methods. One integral part for the success of this minimall...

Defining similarity forms a challenging and relevant research topic in multimodal image registration. The frequently used mutual information disregards contextual information, which is shared across modalities. A recent popular approach, called modality independent neighbourhood descriptor, is based on local self-similarities of image patches and i...

A fully automatic method generating a whole body atlas from CT images is presented. The atlas serves as a reference space for annotations. It is based on a large collection of partially overlapping medical images and a registration scheme. The atlas itself consists of probabilistic tissue type maps and can represent anatomical variations. The regis...

Accurate and fast estimation of T1 relaxation times is a crucial ingredient for many applications in magnetic resonance imaging [1]. A fast way for T1 estimation is a model-based reconstruction from data obtained with variable flip angles as proposed in [2]. However, this technique requires multiple measurements thus patient movement can degrade th...

3D reconstruction and digital double staining offer pathologists many new insights into tissue structure and metabolism. Key to these applications is the precise registration of histological slide images, that is challenging in several ways. One major challenge are differently stained slides, that highlight different parts of the tissue. In this pa...

Image registration is particularly challenging if the images to be aligned contain non-corresponding regions. Using state-of-the-art algorithms typically leads to unwanted and unrealistic deformations in these regions. There are various approaches handling this problem which improve registration results, however each with a focus on specific applic...

Image registration is to automatically establish geometrical correspondences between two images. It is an essential task in almost all areas involving imaging. This chapter reviews mathematical techniques for nonlinear image registration and presents a general, unified, and flexible approach. Taking into account that image registration is an ill-po...

Biomedical imaging is an important and exponentially growing field in life sciences and clinical practice, which strongly depends on the advances in mathematical image processing. Biomedical data presents a number of particularities such as non‐standard acquisition techniques. Thus, biomedical imaging may be considered as an own field of research....

We present a CUDA implementation of a complete registra-tion algorithm, which is capable of aligning two multimodal images, us-ing affine linear transformations and normalized gradient fields. Through the extensive use of different memory types, well handled thread man-agement and efficient hardware interpolation we gained fast executing code. Cont...

Biomedical image registration faces challenging problems in- duced by the image acquisition process of the involved modality. A com- mon problem is the omnipresence of noise perturbations. A low signal- to-noise ratio – like in modern dynamic imaging with short acquisition times – may lead to failure or artifacts in standard image registration tech...

Objectives: Accurate registration of lung CT images is inevitable for numerous clinical applications. Usually, nonlinear intensity-based methods are used. Their accuracy is typically evaluated using corresponding anatomical points (landmarks; e.g. bifurcations of bronchial and vessel trees) annotated by medical experts in the images to register. A...

Dynamic contrast enhanced MR imaging (DCEMRI) of the kidneys requires proper motion correction and segmentation to enable an estimation of glomerular filtration rate (GFR) through pharmacokinetic modeling. Traditionally, co-registration, segmentation and pharmacokinetic modeling have been applied sequentially as separate processing steps. In this w...

Analysis of DCE-MRI data is often carried out by fitting parametric models. However, one major factor of uncertainty is the determination of the arterial input function (AIF). We introduce a novel approach to estimate kinetic parameters in DCE-MRI without an AIF. An existing method by Riabkov et al., where the AIF is introduced as an additional unk...

The treatment of chronic renal diseases usually involves the estimation of the glomerular filtration rate (GFR). The GFR can be estimated in vivo without blood samples by Pharmacokinetic methods, such as Sourbron's separable compartment model. These models employ non-linear curve fitting techniques to obtain model parameters fitting the model to co...

Full text can be downloaded (free) at: http://iopscience.iop.org/1742-6596/489/1/012038/ To enhance the measurements of radio-opaque cylindrical fiducial markers in low contrast x-ray and fluoroscopic images, a novel nonlinear marker enhancement filter (MEF) has been designed. It was primarily developed to assist in automatic initialization of a t...

Image registration is to automatically establish geometrical correspondences between two images. It is an essential task in almost all areas involving imaging. This chapter reviews mathematical techniques for nonlinear image registration and presents a general, unified, and flexible approach. Taking into account that image registration is an ill-po...

Echo Planar Imaging (EPI) is a MRI acquisition technique that is the backbone of widely used investigation techniques in neuro-science like, e.g., Diffusion Tensor Imaging (DTI). While EPI offers con-siderable reduction of the acquisition time one major drawback is its high sensitivity to susceptibility artifacts. Susceptibility differences be-twee...

Image registration is one of the most challenging problems in image processing, where ill-posedness arises due to noisy data as well as non-uniqueness and hence the choice of regularization is crucial. This paper presents hyperelasticity as a regularizer and introduces a new and stable numerical implementation. On one hand, hyperelastic registratio...

In positron emission tomography (PET) imaging, the segmentation of organs is necessary for many quantitative image analysis tasks, e.g., estimation of individual organ concentration or partial volume correction. To this end we present a fully automated approach for wholebody segmentation which enables large-scale and reproducible studies. The appro...

In this paper we present a fully automated atlas-based whole-body segmentation approach using a registration functional with joint segmentation based on our previous work. The passive contour distance is mathematically remodeled. The approach is validated on mouse data sets.

The aim of this work is to present an advanced motion correction pipeline for dual gating based on motion compensation. The pipeline is robust against noise and uses the whole statistic for the final image. We extend motion compensation by motion compensated reconstructions which allow a much finer dual gating for maximal reduction of motion artifa...

In single photon emission computed tomography (SPECT) reconstruction, the objective is to reconstruct the density of a radioactive marker inside a patient from projections. In this work, state-of-the-art reconstruction models for SPECT reconstruction with a so-called attenuation prototype are discussed. A multimodal correspondence problem is brough...

Diffusion weighted magnetic resonance imaging is a key investigation technique in modern neuroscience. In clinical settings, diffusion weighted imaging (DWI) and its extension to diffusion tensor imaging (DTI) is usually performed applying the technique of echo-planar imaging (EPI). EPI is the commonly available ultrafast acquisition technique for...

Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) of the kidney provides important information for the diagnosis of renal dysfunction. To this end, a time series of image volumes is acquired after injection of a contrast agent. The interpretation and pharmacokinetic analysis of the time series data is highly sensitive to motion artifac...

In this work, a novel multilevel approach to Single Photon Emission Computed Tomography (SPECT) reconstruction based on a so-called transformed attenuation prototype is presented. As our results indicate, the benefits of a multilevel strategy as known from literature can be observed as well. That is, we show results where a local minima of a single...

Positron Emission Tomography (PET) is a nuclear imaging technique of increasing importance e.g. in cardiovascular investigations. However, cardiac and respiratory motion of the patient degrade the image quality due to acquisition times in the order of minutes. Reconstructions without motion compensation are prone to spatial blurring and affected at...

This work deals with the single photon emission computed tomography (SPECT) reconstruction process. As a SPECT measurement also depends on unknown attenuation properties of the tissue, such a process is challenging. Furthermore, the given attenuation may not be a good approximation to the true attenuation field. Reasons are repositioning or movemen...

In der plastischen Chirurgie ist es zur Bestimmung der Therapie notwendig, den Schweregrad einer Verbrennung genau einzusch ätzen. Hierzu ist ein Verfahren entwickelt worden, das auf der Verarbeitung visueller Aufnahmen der Wunde in unterschiedlichen Farbspektren beruht. Diese müssen zur Weiterverarbeitung unbedingt deckungsgleich sein, so dass ein...

We consider image registration, which is the determination of a geometrical transformation between two data sets. In this paper we propose constrained variational methods which aim for controlling the change of area or volume under registration transformation. We prove an existence result, convergence of a finite element method, and present a simpl...

Image registration or image matching is a technique to establish meaningful correspondences between points in different scenes. It is a mandatory tool for various applications in medicine, geoscience, and other disciplines. However, obtaining plausible deformations is a complex task. For example, many applications require the transformations to be...

Adding external knowledge improves the results for ill-posed problems. In this paper we present a new computational framework for image registration when adding constraints on the transformation. We demonstrate that unconstrained registration can lead to ambiguous and non-physical results. Adding appropriate constraints introduces prior knowledge a...

Due to the long imaging times in SPECT, patient motion is inevitable and constitutes a serious problem for any reconstruction algorithm. The measured inconsistent projection data lead to reconstruction artifacts which can significantly affect the diagnostic accuracy of SPECT if not corrected. To address this problem a new approach for motion correc...

Interpolation is a key ingredient in many imaging routines. In this note, we present a thorough evaluation of an interpolation method based on exponential splines in tension. They are based on so-called tension parameters, which allow for a tuning of their properties. As it turns out, these interpolants have very many nice features, which are, howe...

Image registration is an important and active area of medical image processing. Given two images, the idea is to compute a reasonable displacement field which deforms one image such that it becomes similar to the other image. The design of an automatic registration scheme is a tricky task and often the computed displacement field has to be discarde...

Image registration and segmentation are two important tasks in medical image analysis. However, the validation of algorithms for non-linear registration in particular often poses significant challenges:1, 2 Anatomical labeling based on scans for the validation of segmentation algorithms is often not available, and is tedious to obtain. One possibil...

Adding external knowledge improves the results for ill-posed problems. In this paper we present a new multi-level optimization framework for image registration when adding landmark constraints on the transformation. Previous approaches are based on a fixed discretization and lack of allowing for continuous landmark positions that are not on grid po...

Molecular imaging is an important tool that has found wide-spread use in the diagnosis and observation of various diseases and has more recently been used in areas such as drug development in order to facilitate the observation and analysis of newly developed drugs. The amounts of data in drug development experiments may be very large due to the in...

In this paper we present a new and general framework for image registration when having additional constraints on the transformation. We demonstrate that registration without constraints leads to arbitrary results depending on the regularization and in particular produces non-physical deformations. Having additional constraints based on the images...

An important issue in computer-assisted surgery of the liver is a fast and reliable transfer of preoperative resection plans to the intraoperative situation. One problem is to match the planning data, derived from preoperative CT or MR images, with 3D ultrasound images of the liver, acquired during surgery. As the liver deforms significantly in the...

This book really shows how registration works: the flip-book appearing at the top right corners shows a registration of a human knee from bent to straight position (keeping bones rigid). Of course, the book also provides insight into concepts and practical tools. The presented framework exploits techniques from various fields such as image processi...

Image registration is the process of aligning two or more images of the same scene taken at different times, from different viewpoints and/or by different sensors. Image registration is a crucial step in imaging problems where the valuable information is contained in more than one image. Here, spatial alignment is required to properly integrate use...

The paper is concerned with image registration algorithms for the alignment of computer tomography (CT) and 3D-ultrasound (US) images of the liver. The necessity of registration arises from the surgeon's request to benefit from the planning data during surgery. The goal is to align the planning data, derived from pre-operative CT-images, with the c...

The paper is concerned with image registration algorithms for the alignment of computer tomography (CT) and 3D-ultrasound (US) images of the liver. The necessity of registration arises from the surgeon's request to benefit from the planning data during surgery. The goal is to align the planning data, derived from pre-operative CT-images, with the c...

Registration is a technique nowadays commonly used in medical imaging. A drawback of most of the current registration schemes is that all tissue is being considered as non-rigid (Staring et al., Proceedings of the SPIE 2006, vol. 6144, pp. 1–10, 2006). Therefore, rigid objects in an image, such as bony structures or surgical instruments, may be tra...

Three-dimensional (3D) image registration is a computationally intensive problem which is commonly solved in medical imaging. The complexity of the problem stems from its size and nonlinearity. In this paper we present an approach that drastically reduces the problem size by using adaptive mesh refinement. Our approach requires special and careful...

In vielen praktischen Problemstellungen ist der Anwender nur in wenigen ausgezeichneten Bildbereichen an einer hochgenauen Registrierung interessiert. Dieser Umstand wird in der vorliegenden Arbeit konsequent umgesetzt. Es wird eine Multiresolutionsstrategie vorgestellt, die es dem Anwender erstmalig erlaubt, auf ausgewählte Bildbereiche zu fokussi...

The physical (microtomy), optical (microscopy), and radiologic (tomography) sectioning of biological objects and their digitization lead to stacks of images. Due to the sectioning process and disturbances, movement of objects during imaging for example, adjacent images of the image stack are not optimally aligned to each other. Such mismatches have...

The goal of image registration is twofold. One goal is to enforce a certain similarity of two images by geometrically transforming one of the images. The second goal is to keep this transformation meaningful or regular. There exists a large amount of approaches aiming for regularity. Most of those are based on certain regularization techniques, oth...

A particular problem in image registration arises for multi-modal images taken from different imaging devices and/or modalities. Starting in 1995, mutual information has shown to be a very successful distance measure for multi-modal image registration. Therefore, mutual information is considered to be the state-of-the-art approach to multi-modal im...

Already for reasonable sized 3D images, image registration be- comes a computationally intensive task. Here, we introduce and ex- plore the concept of OcTree's for registration which drastically reduces the number of processed data and thus the computational costs. We show how to map the registration problem onto an OcTree and present a suitable op...

Die folgende Arbeit fasst die Entwicklung, sowie erste Ergebnisse eines Verfahrens zur Kalibrierung von Gammakameras, wie sie z.B. in Single Photon Emission Computed Tomography (SPECT) Geräten zum Einsatz kommen, zusammen. Um eine gleichbleibende Qualität von Gammakameraaufnahmen zu garantieren, ist es nötig die Gammakamera auf Homogenität und Line...

In the last decades there has been tremendous research towards the design of fully automatic non-rigid registration schemes. However, apart from the ITK based implementation of Rueckerts B-spline oriented approach, there is a lack of sound publicly available implementations of the modern schemes. The Flexible Image Registration Toolbox (FLIRT) is a...

Registration is a technique nowadays commonly used in med- ical imaging. A drawback of most of the current registration schemes is that all tissue is being considered as non-rigid. Therefore, rigid objects in an image, such as bony structures or surgical instruments, may be transformed non-rigidly. In this paper, we integrate the concept of lo- cal...

In the last decades there has been tremendous research to- wards the design of fully automatic non-rigid registration schemes. How- ever, apart from the ITK based implementation of Rueckerts B-spline oriented approach, there is a lack of sound publicly available implemen- tations of the modern schemes. The Flexible Image Registration Toolbox (FLIRT...

The aim of the human neuroscanning project is to build an atlas of the human brain, based on a variety of image modalities in particular histological sections of a prepared brain. Reconstructing essential information out of deformed images is a key problem. We describe a method to correct elastic deformations. Since the method is computational expe...

We present a novel approach for a combined homogenization and registration technique. Medical image data is often disturbed by inhomogeneities from staining, illumination or attenuation. State-of-the-art approaches tackle homogenization and registration separately. Our new method attacks both troublemakers simultaneously. It is modeled as a minimiz...

Image fusion or registration is central to many challenges in medical imaging today and has a vast range of applications. The purpose of this paper is to give an introduction to intensity based non-linear registration and fusion problems from a variational point of view. To do so, we review some of the most promising non-linear registration strateg...