Automated detection of fiducial screws from CT/DVT volume data for image-guided ENT surgery

This paper presents an automated solution for precise detection of fiducial screws from three-dimensional (3D) Computerized Tomography (CT)/Digital Volume Tomography (DVT) data for image-guided ENT surgery. Unlike previously published solutions, we regard the detection of the fiducial screws from the CT/DVT volume data as a pose estimation problem. We thus developed a model-based solution. Starting from a user-supplied initialization, our solution detects the fiducial screws by iteratively matching a computer aided design (CAD) model of the fiducial screw to features extracted from the CT/DVT data. We validated our solution on one conventional CT dataset and on five DVT volume datasets, resulting in a total detection of 24 fiducial screws. Our experimental results indicate that the proposed solution achieves much higher reproducibility and precision than the manual detection. Further comparison shows that the proposed solution produces better results on the DVT dataset than on the conventional CT dataset.

Getting in touch-3D printing in Forensic Imaging

With the increasing use of medical imaging in forensics, as well as the technological advances in rapid prototyping, we suggest combining these techniques to generate displays of forensic findings. We used computed tomography (CT), CT angiography, magnetic resonance imaging (MRI) and surface scanning with photogrammetry in conjunction with segmentation techniques to generate 3D polygon meshes. Based on these data sets, a 3D printer created colored models of the anatomical structures. Using this technique, we could create models of bone fractures, vessels, cardiac infarctions, ruptured organs as well as bitemark wounds. The final models are anatomically accurate, fully colored representations of bones, vessels and soft tissue, and they demonstrate radiologically visible pathologies. The models are more easily understood by laypersons than volume rendering or 2D reconstructions. Therefore, they are suitable for presentations in courtrooms and for educational purposes.

Combining 3D tracking and surgical instrumentation to determine the stiffness of spinal motion segments: a validation study

The spine is a complex structure that provides motion in three directions: flexion and extension, lateral bending and axial rotation. So far, the investigation of the mechanical and kinematic behavior of the basic unit of the spine, a motion segment, is predominantly a domain of in vitro experiments on spinal loading simulators. Most existing approaches to measure spinal stiffness intraoperatively in an in vivo environment use a distractor. However, these concepts usually assume a planar loading and motion. The objective of our study was to develop and validate an apparatus, that allows to perform intraoperative in vivo measurements to determine both the applied force and the resulting motion in three dimensional space. The proposed setup combines force measurement with an instrumented distractor and motion tracking with an optoelectronic system. As the orientation of the applied force and the three dimensional motion is known, not only force-displacement, but also moment-angle relations could be determined. The validation was performed using three cadaveric lumbar ovine spines. The lateral bending stiffness of two motion segments per specimen was determined with the proposed concept and compared with the stiffness acquired on a spinal loading simulator which was considered to be gold standard. The mean values of the stiffness computed with the proposed concept were within a range of ±15% compared to data obtained with the spinal loading simulator under applied loads of less than 5 Nm.

Kernel density correlation based non-rigid point set matching for statistical model-based 2D/3D reconstruction

This paper presents a kernel density correlation based nonrigid point set matching method and shows its application in statistical model based 2D/3D reconstruction of a scaled, patient-specific model from an un-calibrated x-ray radiograph. In this method, both the reference point set and the floating point set are first represented using kernel density estimates. A correlation measure between these two kernel density estimates is then optimized to find a displacement field such that the floating point set is moved to the reference point set. Regularizations based on the overall deformation energy and the motion smoothness energy are used to constraint the displacement field for a robust point set matching. Incorporating this non-rigid point set matching method into a statistical model based 2D/3D reconstruction framework, we can reconstruct a scaled, patient-specific model from noisy edge points that are extracted directly from the x-ray radiograph by an edge detector. Our experiment conducted on datasets of two patients and six cadavers demonstrates a mean reconstruction error of 1.9 mm

Personalized X-Ray Reconstruction of the Proximal Femur via Intensity-Based Non-rigid 2D-3D Registration

This paper presents a new approach for reconstructing a patient-specific shape model and internal relative intensity distribution of the proximal femur from a limited number (e.g., 2) of calibrated C-arm images or X-ray radiographs. Our approach uses independent shape and appearance models that are learned from a set of training data to encode the a priori information about the proximal femur. An intensity-based non-rigid 2D-3D registration algorithm is then proposed to deformably fit the learned models to the input images. The fitting is conducted iteratively by minimizing the dissimilarity between the input images and the associated digitally reconstructed radiographs of the learned models together with regularization terms encoding the strain energy of the forward deformation and the smoothness of the inverse deformation. Comprehensive experiments conducted on images of cadaveric femurs and on clinical datasets demonstrate the efficacy of the present approach.

Investigating the interaction of cellulose nanofibers derived from cotton with a sophisticated 3D human lung cell coculture

Cellulose nanofibers are an attractive component of a broad range of nanomaterials. Their intriguing mechanical properties and low cost, as well as the renewable nature of cellulose make them an appealing alternative to carbon nanotubes (CNTs), which may pose a considerable health risk when inhaled. Little is known, however, concerning the potential toxicity of aerosolized cellulose nanofibers. Using a 3D in vitro triple cell coculture model of the human epithelial airway barrier, it was observed that cellulose nanofibers isolated from cotton (CCN) elicited a significantly (p < 0.05) lower cytotoxicity and (pro-)inflammatory response than multiwalled CNTs (MWCNTs) and crocidolite asbestos fibers (CAFs). Electron tomography analysis also revealed that the intracellular localization of CCNs is different from that of both MWCNTs and CAFs, indicating fundamental differences between each different nanofibre type in their interaction with the human lung cell coculture. Thus, the data shown in the present study highlights that not only the length and stiffness determine the potential detrimental (biological) effects of any nanofiber, but that the material used can significantly affect nanofiber-cell interactions.

dGEMRIC and subsequent T1 mapping of the hip at 1.5 Tesla: normative data on zonal and radial distribution in asymptomatic volunteers

To characterize the zonal distribution of three-dimensional (3D) T1 mapping in the hip joint of asymptomatic adult volunteers.

Importance of 3D-CT imaging in single-bullet cranioencephalic gunshot wounds

PURPOSE: The aim of this paper is to demonstrate that computed tomography (CT) and three-dimensional (3D) CT imaging techniques can be useful tools for evaluating gunshot wounds of the skull in forensic medicine. Three purposes can be achieved: (1) identifying and recognising the bullet entrance wound - and exit wound, if present; (2) recognising the bullet's intracranial course by studying damage to bone and brain tissue; (3) suggesting hypotheses as to the dynamics of the event. MATERIALS AND METHODS: Ten cadavers of people who died of a fatal head injury caused by a single gunshot were imaged with total-body CT prior to conventional autoptic examination. Three-dimensional-CT reconstructions were obtained with the volume-rendering technique, and data were analysed by two independent observers and compared with autopsy results. RESULTS: In our experience, CT analysis and volumetric reconstruction techniques allowed the identification of the bullet entrance and exit wounds and intracranial trajectory, as well as helping to formulate a hypothesis on the extracranial trajectory to corroborate circumstantial evidence. CONCLUSIONS: CT imaging techniques are excellent tools for addressing the most important questions of forensic medicine in the case of gunshot wounds of the skull, with results as good as (or sometimes better than) traditional autoptic methods.

Extended CT scale overcomes restoration caused streak artifacts for dental identification in CT--3D color encoded automatic discrimination of dental restorations

OBJECTIVE: Besides DNA, dental radiographs play a major role in the identification of victims in mass casualties or in corpses with major postmortem alterations. Computed tomography (CT) is increasingly applied in forensic investigations and is used to scan the dentition of deceased persons within minutes. We investigated different restoration materials concerning their radiopacity in CT for dental identification purposes. METHODS: Extracted teeth with different filling materials (composite, amalgam, ceramic, temporary fillings) were CT scanned. Radiopacities of the filling materials were analyzed in extended CT scale images. RESULTS: Radiopacity values ranged from 6000-8500HU (temporary fillings), 4500-17000HU (composite fillings) and >30710HU (Amalgam and Gold). The values were used to define presets for a 3D colored volume rendering software. CONCLUSIONS: The effects of filling material caused streak artifacts could be distinctively reduced for the assessment of the dental status and a postprocessing algorithm was introduced that allows for 3D color encoded visualization and discrimination of different dental restorations based on postmortem CT data.

3D documentation of footwear impressions and tyre tracks in snow with high resolution optical surface scanning

The three-dimensional documentation of footwear and tyre impressions in snow offers an opportunity to capture additional fine detail for the identification as present photographs. For this approach, up to now, different casting methods have been used. Casting of footwear impressions in snow has always been a difficult assignment. This work demonstrates that for the three-dimensional documentation of impressions in snow the non-destructive method of 3D optical surface scanning is suitable. The new method delivers more detailed results of higher accuracy than the conventional casting techniques. The results of this easy to use and mobile 3D optical surface scanner were very satisfactory in different meteorological and snow conditions. The method is also suitable for impressions in soil, sand or other materials. In addition to the side by side comparison, the automatic comparison of the 3D models and the computation of deviations and accuracy of the data simplify the examination and delivers objective and secure results. The results can be visualized efficiently. Data exchange between investigating authorities at a national or an international level can be achieved easily with electronic data carriers.

Assessment of spline-based 2D-3D registration for image-guided spine surgery

2D-3D registration of pre-operative 3D volumetric data with a series of calibrated and undistorted intra-operative 2D projection images has shown great potential in CT-based surgical navigation because it obviates the invasive procedure of the conventional registration methods. In this study, a recently introduced spline-based multi-resolution 2D-3D image registration algorithm has been adapted together with a novel least-squares normalized pattern intensity (LSNPI) similarity measure for image guided minimally invasive spine surgery. A phantom and a cadaver together with their respective ground truths were specially designed to experimentally assess possible factors that may affect the robustness, accuracy, or efficiency of the registration. Our experiments have shown that it is feasible for the assessed 2D-3D registration algorithm to achieve sub-millimeter accuracy in a realistic setup in less than one minute.

Brain atrophy in pure and complicated hereditary spastic paraparesis: a quantitative 3D MRI study

Hereditary spastic paraparesis (HSP) is a heterogeneous group of neurodegenerative disorders with progressive lower limb spasticity, categorized into pure (p-HSP) and complicated forms (c-HSP). The purpose of this study was to evaluate if brain volumes in HSP were altered compared with a control population. Brain volumes were determined in patients suffering from HSP, including both p-HSP (n = 21) and c-HSP type (n = 12), and 30 age-matched healthy controls, using brain parenchymal fractions (BPF) calculated from 3D MRI data in an observer-independent procedure. In addition, the tissue segments of grey and white matter were analysed separately. In HSP patients, BPF were significantly reduced compared with controls both for the whole patient group (P < 0.001) and for both subgroups, indicating considerable brain atrophy. In contrast to controls who showed a decline of brain volumes with age, this physiological phenomenon was less pronounced in HSP. Therefore, global brain parenchyma reduction, involving both grey and white matter, seems to be a feature in both subtypes of HSP. Atrophy was more pronounced in c-HSP, consistent with the more severe phenotype including extramotor involvement. Thus, global brain atrophy, detected by MRI-based brain volume quantification, is a biological marker in HSP subtypes.

3D C-arm as an alternative modality to CT in postmortem imaging: technical feasibility

OBJECT: The aim of our study was to demonstrate the image quality of the new device using human cadavers, extending the horizon of available imaging modalities in forensic medicine. MATERIALS AND METHODS: Six human cadavers were examined, revealing C-arm data sets of the head, neck thorax, abdomen and pelvis. High-resolution mode was performed with 500 fluoroscopy shots during a 190 degrees orbital movement with a constant tube voltage of 100 kV and a current of 4.6 mA. Based on these data sets subsequent three-dimensional reconstructions were generated. RESULTS: Reconstructed data sets revealed high-resolution images of all skeletal structures in a near-CT quality. The same image quality was available in all reconstruction planes. Artefacts caused by restorative dental materials are less accentuated in CBCT data sets. The system configuration was not powerful enough to generate sufficient images of intracranial structures. CONCLUSION: After the here-demonstrated encouraging preliminary results, the forensic indications that would be suitable for imaging with a 3D C-arm have to be defined. Promising seems the visualization local limited region of interest as the cervical spine or the facial skeleton.

Accurate and robust reconstruction of proximal femur from sparse intraoperative data and dense point distribution model for surgical navigation

Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.

An integrated approach for reconstructing surface models of the proximal femur from sparse input data for surgical navigation

A patient-specific surface model of the proximal femur plays an important role in planning and supporting various computer-assisted surgical procedures including total hip replacement, hip resurfacing, and osteotomy of the proximal femur. The common approach to derive 3D models of the proximal femur is to use imaging techniques such as computed tomography (CT) or magnetic resonance imaging (MRI). However, the high logistic effort, the extra radiation (CT-imaging), and the large quantity of data to be acquired and processed make them less functional. In this paper, we present an integrated approach using a multi-level point distribution model (ML-PDM) to reconstruct a patient-specific model of the proximal femur from intra-operatively available sparse data. Results of experiments performed on dry cadaveric bones using dozens of 3D points are presented, as well as experiments using a limited number of 2D X-ray images, which demonstrate promising accuracy of the present approach.