Automatic contour extraction from 2D neuron images

This work describes a novel methodology for automatic contour extraction from 2D images of 3D neurons (e.g. camera lucida images and other types of 2D microscopy). Most contour-based shape analysis methods cannot be used to characterize such cells because of overlaps between neuronal processes. The proposed framework is specifically aimed at the problem of contour following even in presence of multiple overlaps. First, the input image is preprocessed in order to obtain an 8-connected skeleton with one-pixel-wide branches, as well as a set of critical regions (i.e., bifurcations and crossings). Next, for each subtree, the tracking stage iteratively labels all valid pixel of branches, tip to a critical region, where it determines the suitable direction to proceed. Finally, the labeled skeleton segments are followed in order to yield the parametric contour of the neuronal shape under analysis. The reported system was successfully tested with respect to several images and the results from a set of three neuron images are presented here, each pertaining to a different class, i.e. alpha, delta and epsilon ganglion cells, containing a total of 34 crossings. The algorithms successfully got across all these overlaps. The method has also been found to exhibit robustness even for images with close parallel segments. The proposed method is robust and may be implemented in an efficient manner. The introduction of this approach should pave the way for more systematic application of contour-based shape analysis methods in neuronal morphology. (C) 2008 Elsevier B.V. All rights reserved.

Building roof contour extraction from LiDAR data

This paper proposes a method for the automatic extraction of building roof contours from a LiDAR-derived digital surface model (DSM). The method is based on two steps. First, to detect aboveground objects (buildings, trees, etc.), the DSM is segmented through a recursive splitting technique followed by a region merging process. Vectorization and polygonization are used to obtain polyline representations of the detected aboveground objects. Second, building roof contours are identified from among the aboveground objects by optimizing a Markov-random-field-based energy function that embodies roof contour attributes and spatial constraints. Preliminary results have shown that the proposed methodology works properly.

Automatic extraction of femur contours from calibrated fluoroscopic images

Automatic identification and extraction of bone contours from X-ray images is an essential first step task for further medical image analysis. In this paper we propose a 3D statistical model based framework for the proximal femur contour extraction from calibrated X-ray images. The automatic initialization is solved by an estimation of Bayesian network algorithm to fit a multiple component geometrical model to the X-ray data. The contour extraction is accomplished by a non-rigid 2D/3D registration between a 3D statistical model and the X-ray images, in which bone contours are extracted by a graphical model based Bayesian inference. Preliminary experiments on clinical data sets verified its validity

Extração de contornos de telhados usando princípios de Snake Balloon

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Extração automática de contornos de telhados de edifícios em um modelo digital de elevação, utilizando inferência Bayesiana e campos aleatórios de Markov

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Methodological improvement of 3D fluoroscopic analysis for the robust quantification of 3D kinematics of human joints

3D video-fluoroscopy is an accurate but cumbersome technique to estimate natural or prosthetic human joint kinematics. This dissertation proposes innovative methodologies to improve the 3D fluoroscopic analysis reliability and usability. Being based on direct radiographic imaging of the joint, and avoiding soft tissue artefact that limits the accuracy of skin marker based techniques, the fluoroscopic analysis has a potential accuracy of the order of mm/deg or better. It can provide fundamental informations for clinical and methodological applications, but, notwithstanding the number of methodological protocols proposed in the literature, time consuming user interaction is exploited to obtain consistent results. The user-dependency prevented a reliable quantification of the actual accuracy and precision of the methods, and, consequently, slowed down the translation to the clinical practice. The objective of the present work was to speed up this process introducing methodological improvements in the analysis. In the thesis, the fluoroscopic analysis was characterized in depth, in order to evaluate its pros and cons, and to provide reliable solutions to overcome its limitations. To this aim, an analytical approach was followed. The major sources of error were isolated with in-silico preliminary studies as: (a) geometric distortion and calibration errors, (b) 2D images and 3D models resolutions, (c) incorrect contour extraction, (d) bone model symmetries, (e) optimization algorithm limitations, (f) user errors. The effect of each criticality was quantified, and verified with an in-vivo preliminary study on the elbow joint. The dominant source of error was identified in the limited extent of the convergence domain for the local optimization algorithms, which forced the user to manually specify the starting pose for the estimating process. To solve this problem, two different approaches were followed: to increase the optimal pose convergence basin, the local approach used sequential alignments of the 6 degrees of freedom in order of sensitivity, or a geometrical feature-based estimation of the initial conditions for the optimization; the global approach used an unsupervised memetic algorithm to optimally explore the search domain. The performances of the technique were evaluated with a series of in-silico studies and validated in-vitro with a phantom based comparison with a radiostereometric gold-standard. The accuracy of the method is joint-dependent, and for the intact knee joint, the new unsupervised algorithm guaranteed a maximum error lower than 0.5 mm for in-plane translations, 10 mm for out-of-plane translation, and of 3 deg for rotations in a mono-planar setup; and lower than 0.5 mm for translations and 1 deg for rotations in a bi-planar setups. The bi-planar setup is best suited when accurate results are needed, such as for methodological research studies. The mono-planar analysis may be enough for clinical application when the analysis time and cost may be an issue. A further reduction of the user interaction was obtained for prosthetic joints kinematics. A mixed region-growing and level-set segmentation method was proposed and halved the analysis time, delegating the computational burden to the machine. In-silico and in-vivo studies demonstrated that the reliability of the new semiautomatic method was comparable to a user defined manual gold-standard. The improved fluoroscopic analysis was finally applied to a first in-vivo methodological study on the foot kinematics. Preliminary evaluations showed that the presented methodology represents a feasible gold-standard for the validation of skin marker based foot kinematics protocols.

Features extraction based on the Discrete Hartley Transform for closed contour

In this paper the authors propose a new closed contour descriptor that could be seen as a Feature Extractor of closed contours based on the Discrete Hartley Transform (DHT), its main characteristic is that uses only half of the coefficients required by Elliptical Fourier Descriptors (EFD) to obtain a contour approximation with similar error measure. The proposed closed contour descriptor provides an excellent capability of information compression useful for a great number of AI applications. Moreover it can provide scale, position and rotation invariance, and last but not least it has the advantage that both the parameterization and the reconstructed shape from the compressed set can be computed very efficiently by the fast Discrete Hartley Transform (DHT) algorithm. This Feature Extractor could be useful when the application claims for reversible features and when the user needs and easy measure of the quality for a given level of compression, scalable from low to very high quality.

Stability of Contour Augmentation and Esthetic Outcomes of Implant Supported Single Crowns in the Esthetic Zone. 3-Year Results of a Prospective Study With Early Implant Placement Post Extraction

Early implant placement is one of the treatment options after tooth extraction. Implant surgery is performed after a healing period of 4 to 8 weeks and combined with a simultaneous contour augmentation using the guided bone regeneration technique to rebuild stable esthetic facial hard- and soft-tissue contours.

Long-term stability of contour augmentation with early implant placement following single tooth extraction in the esthetic zone: a prospective, cross-sectional study in 41 patients with a 5- to 9-year follow-up

BACKGROUND Early implant placement with simultaneous contour augmentation is documented with short- and medium-term studies. The long-term stability of contour augmentation is uncertain. METHODS In this prospective, cross-sectional study, 41 patients with an implant-borne single crown were examined twice, in 2006 and 2010. Clinical, radiologic, and esthetic parameters were assessed at both examinations. In addition, a cone beam computed tomographic (CBCT) image was obtained during the second examination to assess the dimensions of the facial bone wall. RESULTS All 41 implants demonstrated ankylotic stability without signs of peri-implant infection at both examinations. The clinical parameters remained stable over time. Satisfactory esthetic outcomes were noted, as assessed by the pink and white esthetic score (PES/WES) indices. Overall, the PES scores were slightly higher than the WES scores. None of the implants developed mucosal recession over time, as confirmed by values of the distance between implant shoulder and mucosal margin and cast measurements. The periapical radiographs yielded stable peri-implant bone levels, with a mean distance between implant shoulder and first visible bone-implant contact value of 2.18 mm. The CBCT analysis demonstrated a mean thickness of the facial bone wall ≈2.2 mm. In two implants (4.9%) no facial bone wall was detectable radiographically. CONCLUSIONS This prospective cross-sectional study demonstrates stable peri-implant hard and soft tissues for all 41 implants examined and satisfactory esthetic outcomes overall. The follow-up of 5 to 9 years confirmed again that the risk for mucosal recession is low with early implant placement. In addition, contour augmentation with guided bone regeneration was able to establish and maintain a facial bone wall in 95% of patients.

Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis Elegans

In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals’ transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey’s biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention

Topological multi-contour decomposition for image analysis and image retrieval

Successful classification, information retrieval and image analysis tools are intimately related with the quality of the features employed in the process. Pixel intensities, color, texture and shape are, generally, the basis from which most of the features are Computed and used in such fields. This papers presents a novel shape-based feature extraction approach where an image is decomposed into multiple contours, and further characterized by Fourier descriptors. Unlike traditional approaches we make use of topological knowledge to generate well-defined closed contours, which are efficient signatures for image retrieval. The method has been evaluated in the CBIR context and image analysis. The results have shown that the multi-contour decomposition, as opposed to a single shape information, introduced a significant improvement in the discrimination power. (c) 2008 Elsevier B.V. All rights reserved,

Extraction of Building Roof Contours From LiDAR Data Using a Markov-Random-Field-Based Approach

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Influence of implants with different sizes and configurations installed immediately into extraction sockets on peri-implant hard and soft tissues: an experimental study in dogs

Aim: To study the influence on the healing of soft and hard peri-implant tissues when implants of different sizes and configurations were installed into sockets immediately after tooth extraction.Material and methods: Transmucosal cylindrical implants, 3.3 mm in diameter in the control sites, and conical 5 mm in diameter in the test sites, were installed into the distal socket of the fourth mandibular premolars in dogs immediately after tooth extraction. After 4 months, the hard and soft tissue healing was evaluated histologically. Results: All implants were integrated in mineralized mature bone. Both at the test and control sites, the alveolar crest underwent resorption. The buccal bony surface at the implant test sites (conical; 3.8 mm) was more resorbed compared with the control sites (cylindrical; 1.6 mm). The soft tissue dimensions were similar in both groups. However, in relation to the implant shoulder, the peri-implant mucosa was located more apically at the test compared with the control sites.Conclusion: The present study confirmed that the distance between the implant surface and the outer contour of the buccal alveolar bony crest influenced the degree of resorption of the buccal bone plate. Consequently, in relation to the implant shoulder, the peri-implant mucosa will be established at a more apical level, if the distance between the implant surface and the outer contour of the alveolar crest is small.

A digital evaluation of alveolar ridge preservation at implants placed immediately into extraction sockets: an experimental study in the dog

Objective: To compare with pristine sites bone resorption and soft tissue adaptation at implants placed immediately into extraction sockets (IPIES) in conjunction with deproteinized bovine bone mineral (DBBM) particles and a collagen membrane.Material and methods: The mesial root of the third premolar in the left side of the mandible was endodontically treated (Test). Flaps were elevated, the tooth hemi-sectioned, and the distal root removed to allow the immediate installation of an implant into the extraction socket in a lingual position. DBBM particles were placed into the defect and on the outer contour of the buccal bony ridge, concomitantly with the placement of a collagen membrane. A non-submerged healing was allowed. The premolar on the right side of the mandible was left in situ (control). Ground sections from the center of the implant as well as from the center of the distal root of the third premolar of the opposite side of the mandible were obtained. The histological image from the implant site was superimposed to that of the contralateral pristine distal alveolus, and dimensional variation evaluated for the hard tissue and the alveolar ridge.Results: After 3 months of healing, both histological and photographic evaluation revealed a reduction of hard and soft tissue dimensions.Conclusion: The contour augmentation performed with DBBM particles and a collagen membrane at the buccal aspects of implants placed IPIES was not able to maintain the tissue volume.

Early implant placement following single-tooth extraction in the esthetic zone: biologic rationale and surgical procedures

Early implant placement is one treatment option for implant therapy following single-tooth extraction in the anterior maxilla. The surgical technique presented here is characterized by tooth extraction without flap elevation, a 4- to 8-week soft tissue healing period, implant placement in a correct three-dimensional position, simultaneous contour augmentation on the facial aspect with guided bone regeneration using a bioabsorbable collagen membrane combined with autogenous bone chips and a low-substitution bone filler, and tension-free primary wound closure. The surgical step-by-step procedure is presented with a case report. In addition, the biologic rationale is discussed.