Hans Lamecker

• Dipl. phys., Dr. rer. nat.
• Managing Director at 1000shapes GmbH

Objectives The shape is commonly used to describe the objects. State-of-the-art algorithms in medical imaging are predominantly diverging from computer vision, where voxel grids, meshes, point clouds, and implicit surface models are used. This is seen from the growing popularity of ShapeNet (51,300 models) and Princeton ModelNet (127,915 models). H...

We present MedShapeNet, a large collection of anatomical shapes (e.g., bones, organs, vessels) and 3D surgical instrument models. Prior to the deep learning era, the broad application of statistical shape models (SSMs) in medical image analysis is evidence that shapes have been commonly used to describe medical data. Nowadays, however, state-of-the...

Background Cardiac computed tomography (CCT) based computational fluid dynamics (CFD) allows to assess intracardiac flow features, which are hypothesized as an early predictor for heart diseases and may support treatment decisions. However, the understanding of intracardiac flow is challenging due to high variability in heart shapes and contractili...

Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit clinical decision support systems for diagnosis, surgery planning, and population-based analysis of spine and bone health. However, designing automated algorithms for spine...

Image-based patient-specific modelling of hemodynamics are gaining increased popularity as a diagnosis and outcome prediction solution for a variety of cardiovascular diseases. While their potential to improve diagnostic capabilities and thereby clinical outcome is widely recognized, these methods require considerable computational resources since...

The aim of this paper is to provide a comprehensive overview of the MICCAI 2020 AutoImplant Challenge1. The approaches and publications submitted and accepted within the challenge will be summarized and reported, highlighting common algorithmic trends and algorithmic diversity. Furthermore, the evaluation results will be presented, compared and dis...

Modeling of hemodynamics and artificial intelligence have great potential to support clinical diagnosis and decision making. While hemodynamics modeling is extremely time- and resource-consuming, machine learning (ML) typically requires large training data that are often unavailable. The aim of this study was to develop and evaluate a novel methodo...

Computational Fluid Dynamic calculations are a great assistance for rupture prediction of cerebral aneurysms. This procedure requires a consistent surface, as well as a separation of the blood vessel and aneurysm on this surface to calculate rupture-relevant scores. For this purpose we present an automatic pipeline, which generates a surface model...

We present an automated method for extrapolating missing regions in label data of the skull in an anatomically plausible manner. The ultimate goal is to design patient-specific cranial implants for correcting large, arbitrarily shaped defects of the skull that can, for example, result from trauma of the head. Our approach utilizes a 3D statistical...

Image-based patient-specific modeling of blood flow is a current state of the art approach in cardiovascular research proposed to support diagnosis and treatment decision. However, the approach is time-consuming, and the absence of large data sets limits the applicability of Machine Learning (ML) technology. This study employs Statistical Shape Mod...

This study’s objective was the generation of a standardized geometry of the healthy nasal cavity. An average geometry of the healthy nasal cavity was generated using a statistical shape model based on 25 symptom-free subjects. Airflow within the average geometry and these geometries was calculated using fluid simulations. Integral measures of the n...

The prevailing philosophy in oncologic neurosurgery, has shifted from maximally invasive resection to the preservation of neurologic function. The foundation of safe surgery is the multifaceted visualization of the target region and the surrounding eloquent tissue. Recent advancements in pre-operative and intraoperative visualization modalities hav...

Introduction Population-based models of morphological variability are useful for automating medical image processing tasks, diagnosis, device and tool design, education and training as well as exploratory hypothesis formation in clinical research. We present a method to (a) generate such a model of the thoracic aorta, (b) explore the morphological...

In our chapter we are describing how to reconstruct three-dimensional anatomy from medical image data and how to build Statistical 3D Shape Models out of many such reconstructions yielding a new kind of anatomy that not only allows quantitative analysis of anatomical variation but also a visual exploration and educational visualization. Future digi...

Successful functional surgery on the nasal framework requires reliable and comprehensive diagnosis. In this regard, the authors introduce a new methodology: Digital Analysis of Nasal Airflow (diANA). It is based on computational fluid dynamics, a statistical shape model of the healthy nasal cavity and rhinologic expertise. diANA necessitates an ano...

Functional surgery on the nasal framework requires referential criteria to objectively assess nasal breathing for indication and follow-up. This motivated us to generate a mean geometry of the nasal cavity based on a statistical shape model. In this study, the authors could demonstrate that the introduced nasal cavity's mean geometry features chara...

A population of 54 cases diagnosed with coarctation of the aorta (CoA) was investigated for correlations between complex 3D shape and clinical parameters. Based on a statistical shape model (SSM) of the aortic arch (AA) including supra-aortic branches, clustering was performed. The result confirmed the current clinical classification scheme (normal...

This talk focusses on the aerodynamics within an averaged geometry of the healthy nasal cavity.

Presentation of an averaged geometry of the healthy nasal cavity.

Purpose: Despite the success of total knee arthroplasty, there continues to be a significant proportion of patients who are dissatisfied. One explanation may be a shape mismatch between pre- and postoperative distal femurs. The purpose of this study was to investigate methods suitable for matching a statistical shape model (SSM) to intraoperativel...

The reconstruction of an object’s shape or surface from a set of 3D points plays an important role in medical image analysis, e.g. in anatomy reconstruction from tomographic measurements or in the process of aligning intra-operative navigation and preoperative planning data. In such scenarios, one usually has to deal with sparse data, which signifi...

Deformable model-based approaches to 3D image segmentation have been shown to be highly successful. Such methodology requires an appearance model that drives the deformation of a geometric model to the image data. Appearance models are usually either created heuristically or through supervised learning. Heuristic methods have been shown to work eff...

Paper available here: https://arxiv.org/abs/1602.08425 The reconstruction of an object's shape or surface from a set of 3D points is a common topic in materials and life sciences, computationally handled in computer graphics. Such points usually stem from optical or tactile 3D coordinate measuring equipment. Surface reconstruction also appears in...

Statistical shape models (SSM) describe the shape variability contained in a given population. They are able to describe large populations of complex shapes with few degrees of freedom. This makes them a useful tool for a variety of tasks that arise in computer-aided medicine. In this chapter we are going to explain the basic methodology of SSMs an...

Background Because of the anatomy of the mastoid and the size of the actuator, positioning of the Vibrant Bonebridge B-FMT can be difficult without prior evaluation of the individual computed tomography (CT) scan of the temporal bone. Development of a user-friendly CT data viewer to enable positioning of the B-FMT in the temporal bone model, whilst...

Aim: Information about the temporal bone size and variations of anatomical structures are crucial for a safe positioning of the Vibrant Bonebridge B-FMT. A radiological based preoperative planning of the surgical procedure decreases the surgical time and minimizes the risk of complications. Materials and methods: We developed a software tool, wh...

The authors report on the first experiences with the prototype of a surgical tool for cranial remodeling. The device enables the surgeon to transfer statistical information, represented in a model, into the disfigured bone. The model is derived from a currently evolving databank of normal head shapes. Ultimately, the databank will provide a set of...

We propose a novel GPU-based approach to render virtual X-ray projections of deformable tetrahedral meshes. These meshes represent the shape and the internal density distribution of a particular anatomical structure and are derived from statistical shape and intensity models (SSIMs). We apply our method to improve the geometric reconstruction of 3D...

The Large Deformation Diffeomorphic Metric Mapping (LDDMM) framework acting on currents is a conceptually powerful tool for matching highly varying shapes. In the classical approach, the numerical treatment is based on currents representing individual particles, and couples the discretization of shape and deformation. This design restricts the capa...

We present a software planning tool that provides intuitive visual feedback for �nding suitable positions of hearing implants in the human temporal bone. After an automatic reconstruction of the temporal bone anatomy the tool pre-positions the implant and allows the user to adjust its position interactively with simple 2D dragging and rotation oper...

Deformable surface models are often represented as triangular meshes in image segmentation applications. For a fast and easily regularized deformation onto the target object boundary, the vertices of the mesh are commonly moved along line segments (typically surface normals). However, in case of high mesh curvature, these lines may not intersect wi...

We propose a fully automatic method for tooth detection and classification in CT or cone-beam CT image data. First we compute an accurate segmentation of the maxilla bone. Based on this segmentation, our method computes a complete and optimal separation of the row of teeth into 16 subregions and classifies the resulting regions as existing or missi...

This paper presents a method for meshing multi-material domains with additional features curves. This requirement arises for instance in situations where smooth objects (e.g. anatomical structures) are combined with technical objects (e.g. implants, surgical screws). Our approach avoids the tedious process of generating a single consistent input su...

We consider Large Deformation Diffeomorphic Metric Map-ping of general m-currents. After stating an optimization algorithm in the function space of admissable morph generating velocity fields, two innovative aspects in this framework are presented and numerically in-vestigated: First, we spatially discretize the velocity field with conform-ing adap...

In this work we present an articulated statistical shape model (ASSM) of the human knee. The model incorporates statistical shape variation plus explicit degrees of freedom that model physiological joint motion. We also present a strategy for segmentation of the knee joint from medical image data. We show the potential of the model via an evaluatio...

Navigation systems based on intra-operative ultrasound have been introduced for different surgical procedures and interventions. The accuracy of the ultrasound probe calibration is a main contribution to the overall accuracy of the navigation system. Different calibration methods based on phantoms have been introduced. The challenge of the calibrat...

Temporal subtraction techniques using 2D image registration improve the detectability of interval changes from chest radiographs. Although such methods are well known for some time they are not widely used in radiologic practice. The reason is the occurrence of strong pose differences between two acquisitions with a time interval of months to years...

Deformable surface models are often represented as triangular meshes in image segmentation applications. For a fast and easily regularized deformation onto the target object boundary, the vertices of the mesh are commonly moved along line segments (typically surface normals). However, in case of high mesh curvature, these lines may intersect with t...

This paper presents a method for nonlinear registration of images, where there exists no one-to-one correspondence in parts of the image. Such a situation occurs for instance in the case where an atlas of normal anatomy shall be matched to pathological data, such as tumors, resections or lesions. Our idea is to use local confidence weights and to m...

This paper presents a method for nonlinear registration of images, where there exists no one-to-one correspondence in parts of the image. Such a situation occurs for instance in the case where an atlas of normal anatomy shall be matched to pathological data, such as tumors, resections or lesions. Our idea is to use local confidence weights and to m...

Source: Supplemental Data: 3D-The-Digital-Bee-Brain.: Rybak et al., 2010,Front. Syst. Neurosci., 25 July 2010 | doi: 10.3389/fnsys.2010.00030. Download PDF, open in Acrobat Reader ,drag right-mouse mouse over 'interactive view' in Figure 2A, allows you using the register of the modelTree view all object in 3D view

The honeybee standard brain (HSB) serves as an interactive tool for relating morphologies of bee brain neurons and provides a reference system for functional and bibliographical properties (http://www.neurobiologie.fu-berlin.de/beebrain/). The ultimate goal is to document not only the morphological network properties of neurons collected from separ...

This paper describes an approach for the three-dimensional (3D) shape and pose reconstruction of the human rib cage from few segmented two-dimensional (2D) projection images. Our work is aimed at supporting temporal subtraction techniques of subsequently acquired radiographs by establishing a method for the assessment of pose differences in sequenc...

We present an efficient finite element method to simulate a transversely isotropic nonlinear material for ligaments. The approach relies on tetrahedral elements and exploits the geometry to optimize computation of the derivatives of the strain energy. To better support incompressibility, deviatoric and dilational responses are uncoupled and a penal...

We present a method for fully automatic segmentation of the bones and cartilages of the human knee from MRI data. Based on statistical shape models and graph-based optimization, first the femoral and tibial bone surfaces are reconstructed. Starting from the bone sur-faces the cartilages are segmented simultaneously with a multi object technique usi...

Personalized simulation for therapy planning in the clinical routine requires fast and accurate computations. Finite-element (FE) simulations belong to the most commonly used approaches. Based on medical images the geometry of the patient's anatomy must be faithfully represented and discretized in a way to find a reasonable compromise between accur...

The exact localization of the mandibular nerve with respect to the bone is important for applications in dental implantology and maxillofacial surgery. Cone beam computed tomography (CBCT), often also called digital volume tomography (DVT), is increasingly utilized in maxillofacial or dental imaging. Compared to conventional CT, however, soft tissu...

We present a fully automatic method for 3D segmentation of the mandibular bone from CT data. The method includes an adaptation of statistical shape models of the mandible, the skull base and the mid-facial bones, followed by a simultaneous graph-based optimization of adjacent deformable models. The adaptation of the models to the image data is perf...

In this paper we propose a framework for fully automatic, robust and accurate segmentation of the human pelvis and proximal femur in CT data. We propose a composite statistical shape model of femur and pelvis with a flexible hip joint, for which we extend the common definition of statistical shape models as well as the common strategy for their ada...

This paper presents a comparison study between 10 automatic and six interactive methods for liver segmentation from contrast-enhanced CT images. It is based on results from the "MICCAI 2007 Grand Challenge" workshop, where 16 teams evaluated their algorithms on a common database. A collection of 20 clinical images with reference segmentations was p...

The request for software assistance is increasingly gaining importance in the field of orthopedic surgery. In the near future more people will need implants, which have to last longer. New developments in computer assisted therapy planning promise to significantly reduce the number of revisions and increase the longevity of an implant. For example...

For biomechanical simulations, the segmentation of multiple adjacent anatomical struc-tures from medical image data is often required. If adjacent structures are barely dis-tinguishable in image data, in general automatic segmentation methods for single struc-tures do not yield sufficiently accurate results. To improve segmentation accuracy in thes...

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...

We present an approach for extracting extremal feature lines of scalar indicators on surface meshes, based on discrete Morse Theory. By computing initial Morse-Smale complexes of the scalar indicators of the mesh, we obtain a candidate set of extremal feature lines of the surface. A hierarchy of Morse-Smale complexes is computed by prioritizing fea...

The Honeybee Brain Atlas serves as 3D database and communicative platform to accumulate structural data, i.e. reconstructed neurons, derived from confocal scans (Brandt et al., 2005) (www.neurobiologie.fu-berlin.de/beebrain/) (1). Transforming neurons into the atlas requires manual segmentation of neuropils within confocal images, a time-consuming...

For biomechanical simulations, the segmentation of multiple adjacent anatomical structures from medical image data is often required. If adjacent structures are hardly distinguishable in image data, automatic segmentation methods for single structures in general do not yield sufficiently accurate results. To improve segmentation accuracy in these c...

Image-based 3D atlases have been proven to be very useful in biological and medical research. They serve as spatial reference systems that enable researchers to integrate experimental data in a spatially coherent way and thus to relate diverse data from different experiments. Typically such atlases consist of tissue-separating surfaces. The next st...

We present an algorithm for automatic segmentation of the human pelvic bones from CT datasets that is based on the application of a statistical shape model. The proposed method is divided into three steps: 1) The averaged shape of the pelvis model is initially placed within the CT data using the Generalized Hough Transform, 2) the statistical shape...

Validation of non-rigid registration methods is still a chal- lenging task. Different evaluation criteria were published, yet no widely accepted gold standard exists. The aim of this paper is to provide quan- titative evaluation metrics suited for clinical 3D images containing vessel trees, such as liver or brain data. We present a method to identi...

This work presents an approach towards reconstructing lig- ament and tendon attachment sites from 3D medical image data. We apply statistical shape models with an additional free form step to re- construct the anatomical shape of the distal femur from CT data. After the shape fitting process the locations of ligament attachment sites, which are inc...

This work is concerned with the three-dimensional (3-d) shape and pose reconstruction of the human rib cage from few two-dimensional (2-d) radiographs. The reconstruction method is based on a statistical shape model of the rib cage that is adapted to the 2-d image data of a patient. An underlying optimization process minimizes a distance measure wh...

Surface-based brain atlases like the Honeybee Brain Atlas (www.neurobiologie.fu-berlin.de /beebrain/),(Brandt et al.,2005)1 compare neuronal morphologies in a 3D context, and serve as databases and communicative platforms. Transforming neurons into the atlas requires manually segmenting neuropils in confocal images, a time-consuming task requiring...

In some registration applications additional user knowledge is available, which can improve and accelerate the registration process, especially for non-rigid registration. This is particularly important in the transfer of pre-operative plans to the operating room, e.g. for navigation. In case of tubular structures, such as vessels, a geometric repr...

In some registration applications additional user knowledge is available, which can improve and accelerate the registration process, especially for non-rigid registration. This is particularly important in the transfer of pre-operative plans to the operating room, e.g. for navigation. In case of tubular structures, such as vessels, a geometric repr...

We present a fully automatic 3D segmentation method for the liver from contrast-enhanced CT data. It is based on a combination of a constrained free-form and statistical deformable model. The adap-tation of the model to the image data is performed according to a simple model of the typical intensity distribution around the liver boundary and neighb...

In a predominant amount of cases in orthodontics and orthognathic surgery, from the removal of wisdom teeth or cysts up to osteotomies, two-dimensional imaging is the first, and often the only method of the diagnostic process. However, without knowing the exact course of the mandibular nerve, the risk of an unintended lesion during an intervention...

… Abstract. Surgical intervention in cases of craniosynostosis often lacks objective criteria for the reshaping process of the skull. The application of a statistical 3D-shape model of the upper skull may provide an objective, yet patient-specific guidance for the remodelling. To this end, a statistical 3D-shape model of the upper skull is generate...

Häufig liegt einer computergestützten Operationsplanung lediglich ein Satz von wenigen 2D-Röntgenbildern zugrunde. Dennoch ist es ein Anliegen, auf Basis solcher Daten Rückschlüsse auf die dreidimensionale Anatomie des Patienten zu ziehen. In dieser Arbeit wird ein Verfahren vorgestellt, das mithilfe eines statistischen 3D-Formmodells (SFM) des Bec...

In many cases X-ray images are the only basis for surgery planning. Nevertheless it is desirable to draw conclusions about the 3D-anatomy of the patient from such data. This work presents a method to reconstruct 3D shapes from few digital X-ray images on the basis of 3D-statistical shape models. At the core of this method lies an algorithm which op...

Computer assisted planning in cranio-maxillofacial surgery often requires the segmentation and reconstruction of the mandibular bone from CT data. A common imaging modality is cone-beam volumetric tomography, which requires only low doses of radiation yet suffers from small signal to noise ratio and strong artefacts in the presence of metal. This w...

The exact localization of intrahepatic vessels in relation to a tumour is an important issue in oncological liver surgery. For computer-assisted preoperative planning of surgical procedures high quality vessel models are required. In this work we show how to generate such models on the basis of registered CT or MRI data at different phases of contr...

The exact localization of intrahepatic vessels in relation to a tumour is an important issue in oncological liver surgery. For computer-assisted preoperative planning of surgical procedures high quality vessel models are required. In this work we show how to generate such models on the basis of registered CT or MRI data at different phases of contr...

A statistical 3D shape model of a regularly developed human mandible is presented. The shape model (often referred to as an atlas) is created from 11 tomographic data sets, representing a mean mandibular shape including all of its variations to any shape of the underlying training set. The atlas will serve as a foundation for the reconstruction of...

Registration based on B-spline transformations has attracted much attention in medical image processing recently. Non-rigid registration provides the basis for many important techniques, such as statistical shape modeling. Validating the results, however, remains difficult--especially in intersubject registration. This work explores the ability of...

Organ deformation between preoperative image data and the patient in the OR is the main obstacle for using surgical navigation sys- tems in liver surgery. Our approach is to provide accurate navigation via intraoperative 3D ultrasound. These ultrasound data are augmented with preoperative anatomical models and planning data as an important addition...

Image-guided diagnosis and therapy are widely used in medicine nowadays.

An overview of the current status of the development of our navigation system for resection of liver tumours is given. The system is based on intraoperative three-dimensional (3D) ultrasound volumes for image-guided navigation of surgical instruments. It is also possible to perform a virtual 3D planning of the tumour resection and to non-rigidly re...

The timing and extent of surgery continue to be a matter of discussion in current craniosynostosis management. We retrospectively reviewed the first 159 children seen from 1996 to 2000 of a total of 243 patients presenting with suspected craniosynostosis. We did not establish a surgical indication in 74 children (47%), either because their malforma...

Statistical models of shape are a promising approach for robust and automatic segmentation of medical image data. This work describes the construction of a statistical shape model of the pelvic bone. An interactive approach is proposed for solving the correspondence problem which is able to handle shapes of arbitrary topology, suitable for the genu...

Models of the 3D shape of anatomical objects and the knowledge about their statistical variability are of great benefit in many computer assisted medical applications like images analysis, therapy or surgery planning. Statistical model of shapes have successfully been applied to automate the task of image segmentation. The generation of 3D statisti...

Die chirurgische Entfernung von Tumoren aus dem Beckenknochen erfordert oft die Implantation einer für die individuelle Beckengeometrie angepassten Prothese, um den fehlenden Knochenanteil zu ersetzen. Die computergestützte Planung einer solchen Prothese ermöglicht zum einen eine Beschleunigung der Prothesenkonstruktion und ist zum anderen eine wic...

This paper presents an automatic approach for segmentation of the liver from computer tomography (CT) images based on a 3D statistical shape model. Segmentation of the liver is an important prerequisite in liver surgery planning. One of the major challenges in building a 3D shape model from a training set of segmented instances of an object is the...

Image-guided diagnosis and therapy are widely used in medicine nowadays. Going one step further involves methods that allow physicians to further...

This work presents first quantitative results of a method for automatic liver segmentation from CT data. It is based on a 3D deformable model approach using a-priori statistical information about the shape of the liver gained from a training set. The model is adapted to the data in an iterative process by analysis of the grey value profiles along i...

Statistische Formmodelle haben sich als sehr zuverlässig für die medizinsche Bildsegmentierung erwiesen. Echte dreidimensionale Segmentierung scheitert jedoch häufig an der aufwändigen Korrespondenzbestimmung zwischen 3D Geometrien, die eine Voraussetzung für den Aufbau eines statistischen Formmodells ist. In dieser Arbeit wird ein interaktives Ver...

Segmentierungsverfahren, die auf statistischen Formmodellen basieren, sind erfolgsversprechend für automatische und robuste Segmentierung medizinischer Bilddaten. In dieser Arbeit wird ein Softwarepaket vorgestellt, in dem die Erzeugung statistischer Modelle, deren Anwendung zur Segmentierung unterschiedlicher Bildmodalitäten und Evaluationsmethode...

The use of statistical shape models is a promising approach for robust segmentation of medical images. One of the major challenges in building a 3D shape model from a training set of segmented instances of an object is the determination of the correspondence between them. We propose a novel geometric approach that is based on minimizing the distort...

Methods. The main challenge for performing statistical analysis of three- dimensional shapes lies in the identification of corresponding points on the surfaces of different individual shapes. We adopt the method of consistent patch decomposition and parameterization (2) to solve this problem. All shapes are represented as triangulated surfaces, whi...

We present a unied,approach for consistent remeshing of arbitrary non-manifold triangle meshes with additional user-dened feature lines, which together form a feature skeleton. Our method is based on local operations only and produces meshes of high regularity and triangle quality while preserving the geometry as well as topology of the feature ske...