Detection of breast cancer in automated 3D breast ultrasound

NASA Astrophysics Data System (ADS)

Tan, Tao; Platel, Bram; Mus, Roel; Karssemeijer, Nico

2012-03-01

Automated 3D breast ultrasound (ABUS) is a novel imaging modality, in which motorized scans of the breasts are made with a wide transducer through a membrane under modest compression. The technology has gained high interest and may become widely used in screening of dense breasts, where sensitivity of mammography is poor. ABUS has a high sensitivity for detecting solid breast lesions. However, reading ABUS images is time consuming, and subtle abnormalities may be missed. Therefore, we are developing a computer aided detection (CAD) system to help reduce reading time and errors. In the multi-stage system we propose, segmentations of the breast and nipple are performed, providing landmarks for the detection algorithm. Subsequently, voxel features characterizing coronal spiculation patterns, blobness, contrast, and locations with respect to landmarks are extracted. Using an ensemble of classifiers, a likelihood map indicating potential malignancies is computed. Local maxima in the likelihood map are determined using a local maxima detector and form a set of candidate lesions in each view. These candidates are further processed in a second detection stage, which includes region segmentation, feature extraction and a final classification. Region segmentation is performed using a 3D spiral-scanning dynamic programming method. Region features include descriptors of shape, acoustic behavior and texture. Performance was determined using a 78-patient dataset with 93 images, including 50 malignant lesions. We used 10-fold cross-validation. Using FROC analysis we found that the system obtains a lesion sensitivity of 60% and 70% at 2 and 4 false positives per image respectively.

Speeding up 3D speckle tracking using PatchMatch

NASA Astrophysics Data System (ADS)

Zontak, Maria; O'Donnell, Matthew

2016-03-01

Echocardiography provides valuable information to diagnose heart dysfunction. A typical exam records several minutes of real-time cardiac images. To enable complete analysis of 3D cardiac strains, 4-D (3-D+t) echocardiography is used. This results in a huge dataset and requires effective automated analysis. Ultrasound speckle tracking is an effective method for tissue motion analysis. It involves correlation of a 3D kernel (block) around a voxel with kernels in later frames. The search region is usually confined to a local neighborhood, due to biomechanical and computational constraints. For high strains and moderate frame-rates, however, this search region will remain large, leading to a considerable computational burden. Moreover, speckle decorrelation (due to high strains) leads to errors in tracking. To solve this, spatial motion coherency between adjacent voxels should be imposed, e.g., by averaging their correlation functions.1 This requires storing correlation functions for neighboring voxels, thus increasing memory demands. In this work, we propose an efficient search using PatchMatch, 2 a powerful method to find correspondences between images. Here we adopt PatchMatch for 3D volumes and radio-frequency signals. As opposed to an exact search, PatchMatch performs random sampling of the search region and propagates successive matches among neighboring voxels. We show that: 1) Inherently smooth offset propagation in PatchMatch contributes to spatial motion coherence without any additional processing or memory demand. 2) For typical scenarios, PatchMatch is at least 20 times faster than the exact search, while maintaining comparable tracking accuracy.

Automated building of organometallic complexes from 3D fragments.

PubMed

Foscato, Marco; Venkatraman, Vishwesh; Occhipinti, Giovanni; Alsberg, Bjørn K; Jensen, Vidar R

2014-07-28

A method for the automated construction of three-dimensional (3D) molecular models of organometallic species in design studies is described. Molecular structure fragments derived from crystallographic structures and accurate molecular-level calculations are used as 3D building blocks in the construction of multiple molecular models of analogous compounds. The method allows for precise control of stereochemistry and geometrical features that may otherwise be very challenging, or even impossible, to achieve with commonly available generators of 3D chemical structures. The new method was tested in the construction of three sets of active or metastable organometallic species of catalytic reactions in the homogeneous phase. The performance of the method was compared with those of commonly available methods for automated generation of 3D models, demonstrating higher accuracy of the prepared 3D models in general, and, in particular, a much wider range with respect to the kind of chemical structures that can be built automatically, with capabilities far beyond standard organic and main-group chemistry.

Third generation anthropomorphic physical phantom for mammography and DBT: incorporating voxelized 3D printing and uniform chest wall QC region

NASA Astrophysics Data System (ADS)

Zhao, Christine; Solomon, Justin; Sturgeon, Gregory M.; Gehm, Michael E.; Catenacci, Matthew; Wiley, Benjamin J.; Samei, Ehsan; Lo, Joseph Y.

2017-03-01

Physical breast phantoms provide a standard method to test, optimize, and develop clinical mammography systems, including new digital breast tomosynthesis (DBT) systems. In previous work, we produced an anthropomorphic phantom based on 500x500x500 μm breast CT data using commercial 3D printing. We now introduce an improved phantom based on a new cohort of virtual models with 155x155x155 μm voxels and fabricated through voxelized 3D printing and dithering, which confer higher resolution and greater control over contrast. This new generation includes a uniform chest wall extension for evaluating conventional QC metrics. The uniform region contains a grayscale step wedge, chest wall coverage markers, fiducial markers, spheres, and metal ink stickers of line pairs and edges to assess contrast, resolution, artifact spread function, MTF, and other criteria. We also experimented with doping photopolymer material with calcium, iodine, and zinc to increase our current contrast. In particular, zinc was discovered to significantly increase attenuation beyond 100% breast density with a linear relationship between zinc concentration and attenuation or breast density. This linear relationship was retained when the zinc-doped material was applied in conjunction with 3D printing. As we move towards our long term goal of phantoms that are indistinguishable from patients, this new generation of anthropomorphic physical breast phantom validates our voxelized printing process, demonstrates the utility of a uniform QC region with features from 3D printing and metal ink stickers, and shows potential for improved contrast via doping.

Automated classification of RNA 3D motifs and the RNA 3D Motif Atlas

PubMed Central

Petrov, Anton I.; Zirbel, Craig L.; Leontis, Neocles B.

2013-01-01

The analysis of atomic-resolution RNA three-dimensional (3D) structures reveals that many internal and hairpin loops are modular, recurrent, and structured by conserved non-Watson–Crick base pairs. Structurally similar loops define RNA 3D motifs that are conserved in homologous RNA molecules, but can also occur at nonhomologous sites in diverse RNAs, and which often vary in sequence. To further our understanding of RNA motif structure and sequence variability and to provide a useful resource for structure modeling and prediction, we present a new method for automated classification of internal and hairpin loop RNA 3D motifs and a new online database called the RNA 3D Motif Atlas. To classify the motif instances, a representative set of internal and hairpin loops is automatically extracted from a nonredundant list of RNA-containing PDB files. Their structures are compared geometrically, all-against-all, using the FR3D program suite. The loops are clustered into motif groups, taking into account geometric similarity and structural annotations and making allowance for a variable number of bulged bases. The automated procedure that we have implemented identifies all hairpin and internal loop motifs previously described in the literature. All motif instances and motif groups are assigned unique and stable identifiers and are made available in the RNA 3D Motif Atlas (http://rna.bgsu.edu/motifs), which is automatically updated every four weeks. The RNA 3D Motif Atlas provides an interactive user interface for exploring motif diversity and tools for programmatic data access. PMID:23970545

Fast, Automated, Scalable Generation of Textured 3D Models of Indoor Environments

DTIC Science & Technology

2014-12-18

expensive travel and on-site visits. Different applications require models of different complexities, both with and without furniture geometry. The...environment and to localize the system in the environment over time. The datasets shown in this paper were generated by a backpack -mounted system that uses 2D...voxel is found to intersect the line segment from a scanner to a corresponding scan point. If a laser passes through a voxel, that voxel is considered

Evaluation of brain perfusion in specific Brodmann areas in Frontotemporal dementia and Alzheimer disease using automated 3-D voxel based analysis

NASA Astrophysics Data System (ADS)

Valotassiou, V.; Papatriantafyllou, J.; Sifakis, N.; Karageorgiou, C.; Tsougos, I.; Tzavara, C.; Zerva, C.; Georgoulias, P.

2009-05-01

Introduction. Brain perfusion studies with single-photon emission computed tomography (SPECT) have been applied in demented patients to provide better discrimination between frontotemporal dementia (FTD) and Alzheimer's disease (AD). Aim. To assess the perfusion of specific Brodmann (Br) areas of the brain cortex in FTD and AD patients, using NeuroGam processing program to provide 3D voxel-by-voxel cerebral SPECT analysis. Material and methods. We studied 34 consecutive patients. We used the established criteria for the diagnosis of dementia and the specific established criteria for the diagnosis of FTD and AD. All the patients had a neuropsychological evaluation with a battery of tests including the mini-mental state examination (MMSE).Twenty-six patients (16 males, 10 females, mean age 68.76±6.51 years, education 11.81±4.25 years, MMSE 16.69±9.89) received the diagnosis of FTD and 8 patients (all females, mean age 71.25±10.48 years, education 10±4.6 years, MMSE 12.5±3.89) the diagnosis of AD. All the patients underwent a brain SPECT. We applied the NeuroGam Software for the evaluation of brain perfusion in specific Br areas in the left (L) and right (R) hemispheres. Results. Statistically significant hypoperfusion in FTD compared to AD patients, was found in the following Br areas: 11L (p<0.0001), 11R, 20L, 20R, 32L, 38L, 38R, 44L (p<0.001), 32R, 36L, 36R, 45L, 45R, 47R (p<0.01), 9L, 21L, 39R, 44R, 46R, 47L (p<0.05). On the contrary, AD patients presented significant (p<0.05) hypoperfusion in 7R and 39R Br areas. Conclusion. NeuroGam processing program of brain perfusion SPECT could result in enhanced accuracy for the differential diagnosis between AD and FTD patients.

Cerebral morphology and dopamine D2/D3receptor distribution in humans: A combined [18F]fallypride and voxel-based morphometry study

PubMed Central

Woodward, Neil D.; Zald, David H.; Ding, Zhaohua; Riccardi, Patrizia; Ansari, M. Sib; Baldwin, Ronald M.; Cowan, Ronald L.; Li, Rui; Kessler, Robert M.

2009-01-01

The relationship between cerebral morphology and the expression of dopamine receptors has not been extensively studied in humans. Elucidation of such relationships may have important methodological implications for clinical studies of dopamine receptor ligand binding differences between control and patient groups. The association between cerebral morphology and dopamine receptor distribution was examined in 45 healthy subjects who completed T1-weighted structural MRI and PET scanning with the D2/D3 ligand [18F]fallypride. Optimized voxel-based morphometry was used to create grey matter volume and density images. Grey matter volume and density images were correlated with binding potential (BPND) images on a voxel-by-voxel basis using the Biological Parametric Mapping toolbox. Associations between cerebral morphology and BPND were also examined for selected regions-of-interest (ROIs) after spatial normalization. Voxel-wise analyses indicated that grey matter volume and density positively correlated with BPND throughout the midbrain, including the substantia nigra. Positive correlations were observed in medial cortical areas, including anterior cingulate and medial prefrontal cortex, and circumscribed regions of the temporal, frontal, and parietal lobes. ROI analyses revealed significant positive correlations between BPND and cerebral morphology in the caudate, thalamus, and amygdala. Few negative correlations between morphology and BPND were observed. Overall, grey matter density appeared more strongly correlated with BPND than grey matter volume. Cerebral morphology, particularly grey matter density, correlates with [18F]fallypride BPND in a regionally specific manner. Clinical studies comparing dopamine receptor availability between clinical and control groups may benefit by accounting for potential differences in cerebral morphology that exist even after spatial normalization. PMID:19457373

Cerebral morphology and dopamine D2/D3 receptor distribution in humans: a combined [18F]fallypride and voxel-based morphometry study.

PubMed

Woodward, Neil D; Zald, David H; Ding, Zhaohua; Riccardi, Patrizia; Ansari, M Sib; Baldwin, Ronald M; Cowan, Ronald L; Li, Rui; Kessler, Robert M

2009-05-15

The relationship between cerebral morphology and the expression of dopamine receptors has not been extensively studied in humans. Elucidation of such relationships may have important methodological implications for clinical studies of dopamine receptor ligand binding differences between control and patient groups. The association between cerebral morphology and dopamine receptor distribution was examined in 45 healthy subjects who completed T1-weighted structural MRI and PET scanning with the D(2)/D(3) ligand [(18)F]fallypride. Optimized voxel-based morphometry was used to create grey matter volume and density images. Grey matter volume and density images were correlated with binding potential (BP(ND)) images on a voxel-by-voxel basis using the Biological Parametric Mapping toolbox. Associations between cerebral morphology and BP(ND) were also examined for selected regions-of-interest (ROIs) after spatial normalization. Voxel-wise analyses indicated that grey matter volume and density positively correlated with BP(ND) throughout the midbrain, including the substantia nigra. Positive correlations were observed in medial cortical areas, including anterior cingulate and medial prefrontal cortex, and circumscribed regions of the temporal, frontal, and parietal lobes. ROI analyses revealed significant positive correlations between BP(ND) and cerebral morphology in the caudate, thalamus, and amygdala. Few negative correlations between morphology and BP(ND) were observed. Overall, grey matter density appeared more strongly correlated with BP(ND) than grey matter volume. Cerebral morphology, particularly grey matter density, correlates with [(18)F]fallypride BP(ND) in a regionally specific manner. Clinical studies comparing dopamine receptor availability between clinical and control groups may benefit by accounting for potential differences in cerebral morphology that exist even after spatial normalization.

Automated prescription of oblique brain 3D magnetic resonance spectroscopic imaging.

PubMed

Ozhinsky, Eugene; Vigneron, Daniel B; Chang, Susan M; Nelson, Sarah J

2013-04-01

Two major difficulties encountered in implementing Magnetic Resonance Spectroscopic Imaging (MRSI) in a clinical setting are limited coverage and difficulty in prescription. The goal of this project was to automate completely the process of 3D PRESS MRSI prescription, including placement of the selection box, saturation bands and shim volume, while maximizing the coverage of the brain. The automated prescription technique included acquisition of an anatomical MRI image, optimization of the oblique selection box parameters, optimization of the placement of outer-volume suppression saturation bands, and loading of the calculated parameters into a customized 3D MRSI pulse sequence. To validate the technique and compare its performance with existing protocols, 3D MRSI data were acquired from six exams from three healthy volunteers. To assess the performance of the automated 3D MRSI prescription for patients with brain tumors, the data were collected from 16 exams from 8 subjects with gliomas. This technique demonstrated robust coverage of the tumor, high consistency of prescription and very good data quality within the T2 lesion. Copyright © 2012 Wiley Periodicals, Inc.

Chest wall segmentation in automated 3D breast ultrasound scans.

PubMed

Tan, Tao; Platel, Bram; Mann, Ritse M; Huisman, Henkjan; Karssemeijer, Nico

2013-12-01

In this paper, we present an automatic method to segment the chest wall in automated 3D breast ultrasound images. Determining the location of the chest wall in automated 3D breast ultrasound images is necessary in computer-aided detection systems to remove automatically detected cancer candidates beyond the chest wall and it can be of great help for inter- and intra-modal image registration. We show that the visible part of the chest wall in an automated 3D breast ultrasound image can be accurately modeled by a cylinder. We fit the surface of our cylinder model to a set of automatically detected rib-surface points. The detection of the rib-surface points is done by a classifier using features representing local image intensity patterns and presence of rib shadows. Due to attenuation of the ultrasound signal, a clear shadow is visible behind the ribs. Evaluation of our segmentation method is done by computing the distance of manually annotated rib points to the surface of the automatically detected chest wall. We examined the performance on images obtained with the two most common 3D breast ultrasound devices in the market. In a dataset of 142 images, the average mean distance of the annotated points to the segmented chest wall was 5.59 ± 3.08 mm. Copyright © 2012 Elsevier B.V. All rights reserved.

A universal algorithm for an improved finite element mesh generation Mesh quality assessment in comparison to former automated mesh-generators and an analytic model.

PubMed

Kaminsky, Jan; Rodt, Thomas; Gharabaghi, Alireza; Forster, Jan; Brand, Gerd; Samii, Madjid

2005-06-01

The FE-modeling of complex anatomical structures is not solved satisfyingly so far. Voxel-based as opposed to contour-based algorithms allow an automated mesh generation based on the image data. Nonetheless their geometric precision is limited. We developed an automated mesh-generator that combines the advantages of voxel-based generation with improved representation of the geometry by displacement of nodes on the object-surface. Models of an artificial 3D-pipe-section and a skullbase were generated with different mesh-densities using the newly developed geometric, unsmoothed and smoothed voxel generators. Compared to the analytic calculation of the 3D-pipe-section model the normalized RMS error of the surface stress was 0.173-0.647 for the unsmoothed voxel models, 0.111-0.616 for the smoothed voxel models with small volume error and 0.126-0.273 for the geometric models. The highest element-energy error as a criterion for the mesh quality was 2.61x10(-2) N mm, 2.46x10(-2) N mm and 1.81x10(-2) N mm for unsmoothed, smoothed and geometric voxel models, respectively. The geometric model of the 3D-skullbase resulted in the lowest element-energy error and volume error. This algorithm also allowed the best representation of anatomical details. The presented geometric mesh-generator is universally applicable and allows an automated and accurate modeling by combining the advantages of the voxel-technique and of improved surface-modeling.

Improving automated 3D reconstruction methods via vision metrology

NASA Astrophysics Data System (ADS)

Toschi, Isabella; Nocerino, Erica; Hess, Mona; Menna, Fabio; Sargeant, Ben; MacDonald, Lindsay; Remondino, Fabio; Robson, Stuart

2015-05-01

This paper aims to provide a procedure for improving automated 3D reconstruction methods via vision metrology. The 3D reconstruction problem is generally addressed using two different approaches. On the one hand, vision metrology (VM) systems try to accurately derive 3D coordinates of few sparse object points for industrial measurement and inspection applications; on the other, recent dense image matching (DIM) algorithms are designed to produce dense point clouds for surface representations and analyses. This paper strives to demonstrate a step towards narrowing the gap between traditional VM and DIM approaches. Efforts are therefore intended to (i) test the metric performance of the automated photogrammetric 3D reconstruction procedure, (ii) enhance the accuracy of the final results and (iii) obtain statistical indicators of the quality achieved in the orientation step. VM tools are exploited to integrate their main functionalities (centroid measurement, photogrammetric network adjustment, precision assessment, etc.) into the pipeline of 3D dense reconstruction. Finally, geometric analyses and accuracy evaluations are performed on the raw output of the matching (i.e. the point clouds) by adopting a metrological approach. The latter is based on the use of known geometric shapes and quality parameters derived from VDI/VDE guidelines. Tests are carried out by imaging the calibrated Portable Metric Test Object, designed and built at University College London (UCL), UK. It allows assessment of the performance of the image orientation and matching procedures within a typical industrial scenario, characterised by poor texture and known 3D/2D shapes.

Increasing the automation of a 2D-3D registration system.

PubMed

Varnavas, Andreas; Carrell, Tom; Penney, Graeme

2013-02-01

Routine clinical use of 2D-3D registration algorithms for Image Guided Surgery remains limited. A key aspect for routine clinical use of this technology is its degree of automation, i.e., the amount of necessary knowledgeable interaction between the clinicians and the registration system. Current image-based registration approaches usually require knowledgeable manual interaction during two stages: for initial pose estimation and for verification of produced results. We propose four novel techniques, particularly suited to vertebra-based registration systems, which can significantly automate both of the above stages. Two of these techniques are based upon the intraoperative "insertion" of a virtual fiducial marker into the preoperative data. The remaining two techniques use the final registration similarity value between multiple CT vertebrae and a single fluoroscopy vertebra. The proposed methods were evaluated with data from 31 operations (31 CT scans, 419 fluoroscopy images). Results show these methods can remove the need for manual vertebra identification during initial pose estimation, and were also very effective for result verification, producing a combined true positive rate of 100% and false positive rate equal to zero. This large decrease in required knowledgeable interaction is an important contribution aiming to enable more widespread use of 2D-3D registration technology.

Fast, Automated, Photo realistic, 3D Modeling of Building Interiors

DTIC Science & Technology

2016-09-12

project, we developed two algorithmic pipelines for GPS-denied indoor mobile 3D mapping using an ambulatory backpack system. By mounting scanning...equipment on a backpack system, a human operator can traverse the interior of a building to produce a high-quality 3D reconstruction. In each of our...Unlimited UU UU UU UU 12-09-2016 1-May-2011 30-Jun-2015 Final Report: Fast, Automated, Photo-realistic, 3D Modeling of Building Interiors (ATTN

Ankle-Foot Orthosis Made by 3D Printing Technique and Automated Design Software

PubMed Central

Cha, Yong Ho; Lee, Keun Ho; Ryu, Hong Jong; Joo, Il Won; Seo, Anna; Kim, Dong-Hyeon

2017-01-01

We described 3D printing technique and automated design software and clinical results after the application of this AFO to a patient with a foot drop. After acquiring a 3D modelling file of a patient's lower leg with peroneal neuropathy by a 3D scanner, we loaded this file on the automated orthosis software and created the “STL” file. The designed AFO was printed using a fused filament fabrication type 3D printer, and a mechanical stress test was performed. The patient alternated between the 3D-printed and conventional AFOs for 2 months. There was no crack or damage, and the shape and stiffness of the AFO did not change after the durability test. The gait speed increased after wearing the conventional AFO (56.5 cm/sec) and 3D-printed AFO (56.5 cm/sec) compared to that without an AFO (42.2 cm/sec). The patient was more satisfied with the 3D-printed AFO than the conventional AFO in terms of the weight and ease of use. The 3D-printed AFO exhibited similar functionality as the conventional AFO and considerably satisfied the patient in terms of the weight and ease of use. We suggest the possibility of the individualized AFO with 3D printing techniques and automated design software. PMID:28827977

Fine-resolution voxel S values for constructing absorbed dose distributions at variable voxel size.

PubMed

Dieudonné, Arnaud; Hobbs, Robert F; Bolch, Wesley E; Sgouros, George; Gardin, Isabelle

2010-10-01

This article presents a revised voxel S values (VSVs) approach for dosimetry in targeted radiotherapy, allowing dose calculation for any voxel size and shape of a given SPECT or PET dataset. This approach represents an update to the methodology presented in MIRD pamphlet no. 17. VSVs were generated in soft tissue with a fine spatial sampling using the Monte Carlo (MC) code MCNPX for particle emissions of 9 radionuclides: (18)F, (90)Y, (99m)Tc, (111)In, (123)I, (131)I, (177)Lu, (186)Re, and (201)Tl. A specific resampling algorithm was developed to compute VSVs for desired voxel dimensions. The dose calculation was performed by convolution via a fast Hartley transform. The fine VSVs were calculated for cubic voxels of 0.5 mm for electrons and 1.0 mm for photons. Validation studies were done for (90)Y and (131)I VSV sets by comparing the revised VSV approach to direct MC simulations. The first comparison included 20 spheres with different voxel sizes (3.8-7.7 mm) and radii (4-64 voxels) and the second comparison a hepatic tumor with cubic voxels of 3.8 mm. MC simulations were done with MCNPX for both. The third comparison was performed on 2 clinical patients with the 3D-RD (3-Dimensional Radiobiologic Dosimetry) software using the EGSnrc (Electron Gamma Shower National Research Council Canada)-based MC implementation, assuming a homogeneous tissue-density distribution. For the sphere model study, the mean relative difference in the average absorbed dose was 0.20% ± 0.41% for (90)Y and -0.36% ± 0.51% for (131)I (n = 20). For the hepatic tumor, the difference in the average absorbed dose to tumor was 0.33% for (90)Y and -0.61% for (131)I and the difference in average absorbed dose to the liver was 0.25% for (90)Y and -1.35% for (131)I. The comparison with the 3D-RD software showed an average voxel-to-voxel dose ratio between 0.991 and 0.996. The calculation time was below 10 s with the VSV approach and 50 and 15 h with 3D-RD for the 2 clinical patients. This new VSV

Dosimetry for nonuniform activity distributions: a method for the calculation of 3D absorbed-dose distribution without the use of voxel S-values, point kernels, or Monte Carlo simulations.

PubMed

Traino, A C; Marcatili, S; Avigo, C; Sollini, M; Erba, P A; Mariani, G

2013-04-01

Nonuniform activity within the target lesions and the critical organs constitutes an important limitation for dosimetric estimates in patients treated with tumor-seeking radiopharmaceuticals. The tumor control probability and the normal tissue complication probability are affected by the distribution of the radionuclide in the treated organ/tissue. In this paper, a straightforward method for calculating the absorbed dose at the voxel level is described. This new method takes into account a nonuniform activity distribution in the target/organ. The new method is based on the macroscopic S-values (i.e., the S-values calculated for the various organs, as defined in the MIRD approach), on the definition of the number of voxels, and on the raw-count 3D array, corrected for attenuation, scatter, and collimator resolution, in the lesion/organ considered. Starting from these parameters, the only mathematical operation required is to multiply the 3D array by a scalar value, thus avoiding all the complex operations involving the 3D arrays. A comparison with the MIRD approach, fully described in the MIRD Pamphlet No. 17, using S-values at the voxel level, showed a good agreement between the two methods for (131)I and for (90)Y. Voxel dosimetry is becoming more and more important when performing therapy with tumor-seeking radiopharmaceuticals. The method presented here does not require calculating the S-values at the voxel level, and thus bypasses the mathematical problems linked to the convolution of 3D arrays and to the voxel size. In the paper, the results obtained with this new simplified method as well as the possibility of using it for other radionuclides commonly employed in therapy are discussed. The possibility of using the correct density value of the tissue/organs involved is also discussed.

A visual LISP program for voxelizing AutoCAD solid models

NASA Astrophysics Data System (ADS)

Marschallinger, Robert; Jandrisevits, Carmen; Zobl, Fritz

2015-01-01

AutoCAD solid models are increasingly recognized in geological and geotechnical 3D modeling. In order to bridge the currently existing gap between AutoCAD solid models and the grid modeling realm, a Visual LISP program is presented that converts AutoCAD solid models into voxel arrays. Acad2Vox voxelizer works on a 3D-model that is made up of arbitrary non-overlapping 3D-solids. After definition of the target voxel array geometry, 3D-solids are scanned at grid positions and properties are streamed to an ASCII output file. Acad2Vox has a novel voxelization strategy that combines a hierarchical reduction of sampling dimensionality with an innovative use of AutoCAD-specific methods for a fast and memory-saving operation. Acad2Vox provides georeferenced, voxelized analogs of 3D design data that can act as regions-of-interest in later geostatistical modeling and simulation. The Supplement includes sample geological solid models with instructions for practical work with Acad2Vox.

Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method

NASA Astrophysics Data System (ADS)

McIntosh, Chris; Welch, Mattea; McNiven, Andrea; Jaffray, David A.; Purdie, Thomas G.

2017-08-01

Recent works in automated radiotherapy treatment planning have used machine learning based on historical treatment plans to infer the spatial dose distribution for a novel patient directly from the planning image. We present a probabilistic, atlas-based approach which predicts the dose for novel patients using a set of automatically selected most similar patients (atlases). The output is a spatial dose objective, which specifies the desired dose-per-voxel, and therefore replaces the need to specify and tune dose-volume objectives. Voxel-based dose mimicking optimization then converts the predicted dose distribution to a complete treatment plan with dose calculation using a collapsed cone convolution dose engine. In this study, we investigated automated planning for right-sided oropharaynx head and neck patients treated with IMRT and VMAT. We compare four versions of our dose prediction pipeline using a database of 54 training and 12 independent testing patients by evaluating 14 clinical dose evaluation criteria. Our preliminary results are promising and demonstrate that automated methods can generate comparable dose distributions to clinical. Overall, automated plans achieved an average of 0.6% higher dose for target coverage evaluation criteria, and 2.4% lower dose at the organs at risk criteria levels evaluated compared with clinical. There was no statistically significant difference detected in high-dose conformity between automated and clinical plans as measured by the conformation number. Automated plans achieved nine more unique criteria than clinical across the 12 patients tested and automated plans scored a significantly higher dose at the evaluation limit for two high-risk target coverage criteria and a significantly lower dose in one critical organ maximum dose. The novel dose prediction method with dose mimicking can generate complete treatment plans in 12-13 min without user interaction. It is a promising approach for fully automated treatment

Fully automated treatment planning for head and neck radiotherapy using a voxel-based dose prediction and dose mimicking method.

PubMed

McIntosh, Chris; Welch, Mattea; McNiven, Andrea; Jaffray, David A; Purdie, Thomas G

2017-07-06

Recent works in automated radiotherapy treatment planning have used machine learning based on historical treatment plans to infer the spatial dose distribution for a novel patient directly from the planning image. We present a probabilistic, atlas-based approach which predicts the dose for novel patients using a set of automatically selected most similar patients (atlases). The output is a spatial dose objective, which specifies the desired dose-per-voxel, and therefore replaces the need to specify and tune dose-volume objectives. Voxel-based dose mimicking optimization then converts the predicted dose distribution to a complete treatment plan with dose calculation using a collapsed cone convolution dose engine. In this study, we investigated automated planning for right-sided oropharaynx head and neck patients treated with IMRT and VMAT. We compare four versions of our dose prediction pipeline using a database of 54 training and 12 independent testing patients by evaluating 14 clinical dose evaluation criteria. Our preliminary results are promising and demonstrate that automated methods can generate comparable dose distributions to clinical. Overall, automated plans achieved an average of 0.6% higher dose for target coverage evaluation criteria, and 2.4% lower dose at the organs at risk criteria levels evaluated compared with clinical. There was no statistically significant difference detected in high-dose conformity between automated and clinical plans as measured by the conformation number. Automated plans achieved nine more unique criteria than clinical across the 12 patients tested and automated plans scored a significantly higher dose at the evaluation limit for two high-risk target coverage criteria and a significantly lower dose in one critical organ maximum dose. The novel dose prediction method with dose mimicking can generate complete treatment plans in 12-13 min without user interaction. It is a promising approach for fully automated treatment

Framework for Automated GD&T Inspection Using 3D Scanner

NASA Astrophysics Data System (ADS)

Pathak, Vimal Kumar; Singh, Amit Kumar; Sivadasan, M.; Singh, N. K.

2018-04-01

Geometric Dimensioning and Tolerancing (GD&T) is a typical dialect that helps designers, production faculty and quality monitors to convey design specifications in an effective and efficient manner. GD&T has been practiced since the start of machine component assembly but without overly naming it. However, in recent times industries have started increasingly emphasizing on it. One prominent area where most of the industries struggle with is quality inspection. Complete inspection process is mostly human intensive. Also, the use of conventional gauges and templates for inspection purpose highly depends on skill of workers and quality inspectors. In industries, the concept of 3D scanning is not new but is used only for creating 3D drawings or modelling of physical parts. However, the potential of 3D scanning as a powerful inspection tool is hardly explored. This study is centred on designing a procedure for automated inspection using 3D scanner. Linear, geometric and dimensional inspection of the most popular test bar-stepped bar, as a simple example was also carried out as per the new framework. The new generation engineering industries would definitely welcome this automated inspection procedure being quick and reliable with reduced human intervention.

Automated 3D Ultrasound Image Segmentation to Aid Breast Cancer Image Interpretation

PubMed Central

Gu, Peng; Lee, Won-Mean; Roubidoux, Marilyn A.; Yuan, Jie; Wang, Xueding; Carson, Paul L.

2015-01-01

Segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. Differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3D) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3D ultrasound volumes into three major tissue types: cyst/mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3D whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer. PMID:26547117

Automated 3D ultrasound image segmentation for assistant diagnosis of breast cancer

NASA Astrophysics Data System (ADS)

Wang, Yuxin; Gu, Peng; Lee, Won-Mean; Roubidoux, Marilyn A.; Du, Sidan; Yuan, Jie; Wang, Xueding; Carson, Paul L.

2016-04-01

Segmentation of an ultrasound image into functional tissues is of great importance to clinical diagnosis of breast cancer. However, many studies are found to segment only the mass of interest and not all major tissues. Differences and inconsistencies in ultrasound interpretation call for an automated segmentation method to make results operator-independent. Furthermore, manual segmentation of entire three-dimensional (3D) ultrasound volumes is time-consuming, resource-intensive, and clinically impractical. Here, we propose an automated algorithm to segment 3D ultrasound volumes into three major tissue types: cyst/mass, fatty tissue, and fibro-glandular tissue. To test its efficacy and consistency, the proposed automated method was employed on a database of 21 cases of whole breast ultrasound. Experimental results show that our proposed method not only distinguishes fat and non-fat tissues correctly, but performs well in classifying cyst/mass. Comparison of density assessment between the automated method and manual segmentation demonstrates good consistency with an accuracy of 85.7%. Quantitative comparison of corresponding tissue volumes, which uses overlap ratio, gives an average similarity of 74.54%, consistent with values seen in MRI brain segmentations. Thus, our proposed method exhibits great potential as an automated approach to segment 3D whole breast ultrasound volumes into functionally distinct tissues that may help to correct ultrasound speed of sound aberrations and assist in density based prognosis of breast cancer.

Improving automated multiple sclerosis lesion segmentation with a cascaded 3D convolutional neural network approach.

PubMed

Valverde, Sergi; Cabezas, Mariano; Roura, Eloy; González-Villà, Sandra; Pareto, Deborah; Vilanova, Joan C; Ramió-Torrentà, Lluís; Rovira, Àlex; Oliver, Arnau; Lladó, Xavier

2017-07-15

In this paper, we present a novel automated method for White Matter (WM) lesion segmentation of Multiple Sclerosis (MS) patient images. Our approach is based on a cascade of two 3D patch-wise convolutional neural networks (CNN). The first network is trained to be more sensitive revealing possible candidate lesion voxels while the second network is trained to reduce the number of misclassified voxels coming from the first network. This cascaded CNN architecture tends to learn well from a small (n≤35) set of labeled data of the same MRI contrast, which can be very interesting in practice, given the difficulty to obtain manual label annotations and the large amount of available unlabeled Magnetic Resonance Imaging (MRI) data. We evaluate the accuracy of the proposed method on the public MS lesion segmentation challenge MICCAI2008 dataset, comparing it with respect to other state-of-the-art MS lesion segmentation tools. Furthermore, the proposed method is also evaluated on two private MS clinical datasets, where the performance of our method is also compared with different recent public available state-of-the-art MS lesion segmentation methods. At the time of writing this paper, our method is the best ranked approach on the MICCAI2008 challenge, outperforming the rest of 60 participant methods when using all the available input modalities (T1-w, T2-w and FLAIR), while still in the top-rank (3rd position) when using only T1-w and FLAIR modalities. On clinical MS data, our approach exhibits a significant increase in the accuracy segmenting of WM lesions when compared with the rest of evaluated methods, highly correlating (r≥0.97) also with the expected lesion volume. Copyright © 2017 Elsevier Inc. All rights reserved.

Automated three-dimensional quantification of myocardial perfusion and brain SPECT.

PubMed

Slomka, P J; Radau, P; Hurwitz, G A; Dey, D

2001-01-01

To allow automated and objective reading of nuclear medicine tomography, we have developed a set of tools for clinical analysis of myocardial perfusion tomography (PERFIT) and Brain SPECT/PET (BRASS). We exploit algorithms for image registration and use three-dimensional (3D) "normal models" for individual patient comparisons to composite datasets on a "voxel-by-voxel basis" in order to automatically determine the statistically significant abnormalities. A multistage, 3D iterative inter-subject registration of patient images to normal templates is applied, including automated masking of the external activity before final fit. In separate projects, the software has been applied to the analysis of myocardial perfusion SPECT, as well as brain SPECT and PET data. Automatic reading was consistent with visual analysis; it can be applied to the whole spectrum of clinical images, and aid physicians in the daily interpretation of tomographic nuclear medicine images.

An automated voxelized dosimetry tool for radionuclide therapy based on serial quantitative SPECT/CT imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jackson, Price A.; Kron, Tomas; Beauregard, Jean-Mathieu

2013-11-15

Purpose: To create an accurate map of the distribution of radiation dose deposition in healthy and target tissues during radionuclide therapy.Methods: Serial quantitative SPECT/CT images were acquired at 4, 24, and 72 h for 28 {sup 177}Lu-octreotate peptide receptor radionuclide therapy (PRRT) administrations in 17 patients with advanced neuroendocrine tumors. Deformable image registration was combined with an in-house programming algorithm to interpolate pharmacokinetic uptake and clearance at a voxel level. The resultant cumulated activity image series are comprised of values representing the total number of decays within each voxel's volume. For PRRT, cumulated activity was translated to absorbed dose basedmore » on Monte Carlo-determined voxel S-values at a combination of long and short ranges. These dosimetric image sets were compared for mean radiation absorbed dose to at-risk organs using a conventional MIRD protocol (OLINDA 1.1).Results: Absorbed dose values to solid organs (liver, kidneys, and spleen) were within 10% using both techniques. Dose estimates to marrow were greater using the voxelized protocol, attributed to the software incorporating crossfire effect from nearby tumor volumes.Conclusions: The technique presented offers an efficient, automated tool for PRRT dosimetry based on serial post-therapy imaging. Following retrospective analysis, this method of high-resolution dosimetry may allow physicians to prescribe activity based on required dose to tumor volume or radiation limits to healthy tissue in individual patients.« less

A Voxel-Based Approach for Imaging Voids in Three-Dimensional Point Clouds

NASA Astrophysics Data System (ADS)

Salvaggio, Katie N.

Geographically accurate scene models have enormous potential beyond that of just simple visualizations in regard to automated scene generation. In recent years, thanks to ever increasing computational efficiencies, there has been significant growth in both the computer vision and photogrammetry communities pertaining to automatic scene reconstruction from multiple-view imagery. The result of these algorithms is a three-dimensional (3D) point cloud which can be used to derive a final model using surface reconstruction techniques. However, the fidelity of these point clouds has not been well studied, and voids often exist within the point cloud. Voids exist in texturally difficult areas, as well as areas where multiple views were not obtained during collection, constant occlusion existed due to collection angles or overlapping scene geometry, or in regions that failed to triangulate accurately. It may be possible to fill in small voids in the scene using surface reconstruction or hole-filling techniques, but this is not the case with larger more complex voids, and attempting to reconstruct them using only the knowledge of the incomplete point cloud is neither accurate nor aesthetically pleasing. A method is presented for identifying voids in point clouds by using a voxel-based approach to partition the 3D space. By using collection geometry and information derived from the point cloud, it is possible to detect unsampled voxels such that voids can be identified. This analysis takes into account the location of the camera and the 3D points themselves to capitalize on the idea of free space, such that voxels that lie on the ray between the camera and point are devoid of obstruction, as a clear line of sight is a necessary requirement for reconstruction. Using this approach, voxels are classified into three categories: occupied (contains points from the point cloud), free (rays from the camera to the point passed through the voxel), and unsampled (does not contain points

Single-voxel and multi-voxel spectroscopy yield comparable results in the normal juvenile canine brain when using 3 Tesla magnetic resonance imaging.

PubMed

Lee, Alison M; Beasley, Michaela J; Barrett, Emerald D; James, Judy R; Gambino, Jennifer M

2018-06-10

Conventional magnetic resonance imaging (MRI) characteristics of canine brain diseases are often nonspecific. Single- and multi-voxel spectroscopy techniques allow quantification of chemical biomarkers for tissues of interest and may help to improve diagnostic specificity. However, published information is currently lacking for the in vivo performance of these two techniques in dogs. The aim of this prospective, methods comparison study was to compare the performance of single- and multi-voxel spectroscopy in the brains of eight healthy, juvenile dogs using 3 Tesla MRI. Ipsilateral regions of single- and multi-voxel spectroscopy were performed in symmetric regions of interest of each brain in the parietal (n = 3), thalamic (n = 2), and piriform lobes (n = 3). In vivo single-voxel spectroscopy and multi-voxel spectroscopy metabolite ratios from the same size and multi-voxel spectroscopy ratios from different sized regions of interest were compared. No significant difference was seen between single-voxel spectroscopy and multi-voxel spectroscopy metabolite ratios for any lobe when regions of interest were similar in size and shape. Significant lobar single-voxel spectroscopy and multi-voxel spectroscopy differences were seen between the parietal lobe and thalamus (P = 0.047) for the choline to N-acetyl aspartase ratios when large multi-voxel spectroscopy regions of interest were compared to very small multi-voxel spectroscopy regions of interest within the same lobe; and for the N-acetyl aspartase to creatine ratios in all lobes when single-voxel spectroscopy was compared to combined (pooled) multi-voxel spectroscopy datasets. Findings from this preliminary study indicated that single- and multi-voxel spectroscopy techniques using 3T MRI yield comparable results for similar sized regions of interest in the normal canine brain. Findings also supported using the contralateral side as an internal control for dogs with brain lesions. © 2018 American College of

Volumetric 3D Display System with Static Screen

NASA Technical Reports Server (NTRS)

Geng, Jason

2011-01-01

Current display technology has relied on flat, 2D screens that cannot truly convey the third dimension of visual information: depth. In contrast to conventional visualization that is primarily based on 2D flat screens, the volumetric 3D display possesses a true 3D display volume, and places physically each 3D voxel in displayed 3D images at the true 3D (x,y,z) spatial position. Each voxel, analogous to a pixel in a 2D image, emits light from that position to form a real 3D image in the eyes of the viewers. Such true volumetric 3D display technology provides both physiological (accommodation, convergence, binocular disparity, and motion parallax) and psychological (image size, linear perspective, shading, brightness, etc.) depth cues to human visual systems to help in the perception of 3D objects. In a volumetric 3D display, viewers can watch the displayed 3D images from a completely 360 view without using any special eyewear. The volumetric 3D display techniques may lead to a quantum leap in information display technology and can dramatically change the ways humans interact with computers, which can lead to significant improvements in the efficiency of learning and knowledge management processes. Within a block of glass, a large amount of tiny dots of voxels are created by using a recently available machining technique called laser subsurface engraving (LSE). The LSE is able to produce tiny physical crack points (as small as 0.05 mm in diameter) at any (x,y,z) location within the cube of transparent material. The crack dots, when illuminated by a light source, scatter the light around and form visible voxels within the 3D volume. The locations of these tiny voxels are strategically determined such that each can be illuminated by a light ray from a high-resolution digital mirror device (DMD) light engine. The distribution of these voxels occupies the full display volume within the static 3D glass screen. This design eliminates any moving screen seen in previous

Multi-modality 3D breast imaging with X-Ray tomosynthesis and automated ultrasound.

PubMed

Sinha, Sumedha P; Roubidoux, Marilyn A; Helvie, Mark A; Nees, Alexis V; Goodsitt, Mitchell M; LeCarpentier, Gerald L; Fowlkes, J Brian; Chalek, Carl L; Carson, Paul L

2007-01-01

This study evaluated the utility of 3D automated ultrasound in conjunction with 3D digital X-Ray tomosynthesis for breast cancer detection and assessment, to better localize and characterize lesions in the breast. Tomosynthesis image volumes and automated ultrasound image volumes were acquired in the same geometry and in the same view for 27 patients. 3 MQSA certified radiologists independently reviewed the image volumes, visually correlating the images from the two modalities with in-house software. More sophisticated software was used on a smaller set of 10 cases, which enabled the radiologist to draw a 3D box around the suspicious lesion in one image set and isolate an anatomically correlated, similarly boxed region in the other modality image set. In the primary study, correlation was found to be moderately useful to the readers. In the additional study, using improved software, the median usefulness rating increased and confidence in localizing and identifying the suspicious mass increased in more than half the cases. As automated scanning and reading software techniques advance, superior results are expected.

Free and open-source automated 3-D microscope.

PubMed

Wijnen, Bas; Petersen, Emily E; Hunt, Emily J; Pearce, Joshua M

2016-11-01

Open-source technology not only has facilitated the expansion of the greater research community, but by lowering costs it has encouraged innovation and customizable design. The field of automated microscopy has continued to be a challenge in accessibility due the expense and inflexible, noninterchangeable stages. This paper presents a low-cost, open-source microscope 3-D stage. A RepRap 3-D printer was converted to an optical microscope equipped with a customized, 3-D printed holder for a USB microscope. Precision measurements were determined to have an average error of 10 μm at the maximum speed and 27 μm at the minimum recorded speed. Accuracy tests yielded an error of 0.15%. The machine is a true 3-D stage and thus able to operate with USB microscopes or conventional desktop microscopes. It is larger than all commercial alternatives, and is thus capable of high-depth images over unprecedented areas and complex geometries. The repeatability is below 2-D microscope stages, but testing shows that it is adequate for the majority of scientific applications. The open-source microscope stage costs less than 3-9% of the closest proprietary commercial stages. This extreme affordability vastly improves accessibility for 3-D microscopy throughout the world. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.

Multi-resolution Gabor wavelet feature extraction for needle detection in 3D ultrasound

NASA Astrophysics Data System (ADS)

Pourtaherian, Arash; Zinger, Svitlana; Mihajlovic, Nenad; de With, Peter H. N.; Huang, Jinfeng; Ng, Gary C.; Korsten, Hendrikus H. M.

2015-12-01

Ultrasound imaging is employed for needle guidance in various minimally invasive procedures such as biopsy guidance, regional anesthesia and brachytherapy. Unfortunately, a needle guidance using 2D ultrasound is very challenging, due to a poor needle visibility and a limited field of view. Nowadays, 3D ultrasound systems are available and more widely used. Consequently, with an appropriate 3D image-based needle detection technique, needle guidance and interventions may significantly be improved and simplified. In this paper, we present a multi-resolution Gabor transformation for an automated and reliable extraction of the needle-like structures in a 3D ultrasound volume. We study and identify the best combination of the Gabor wavelet frequencies. High precision in detecting the needle voxels leads to a robust and accurate localization of the needle for the intervention support. Evaluation in several ex-vivo cases shows that the multi-resolution analysis significantly improves the precision of the needle voxel detection from 0.23 to 0.32 at a high recall rate of 0.75 (gain 40%), where a better robustness and confidence were confirmed in the practical experiments.

Quantitative IR microscopy and spectromics open the way to 3D digital pathology.

PubMed

Bobroff, Vladimir; Chen, Hsiang-Hsin; Delugin, Maylis; Javerzat, Sophie; Petibois, Cyril

2017-04-01

Currently, only mass-spectrometry (MS) microscopy brings a quantitative analysis of chemical contents of tissue samples in 3D. Here, the reconstruction of a 3D quantitative chemical images of a biological tissue by FTIR spectro-microscopy is reported. An automated curve-fitting method is developed to extract all intense absorption bands constituting IR spectra. This innovation benefits from three critical features: (1) the correction of raw IR spectra to make them quantitatively comparable; (2) the automated and iterative data treatment allowing to transfer the IR-absorption spectrum into a IR-band spectrum; (3) the reconstruction of an 3D IR-band matrix (x, y, z for voxel position and a 4 th dimension with all IR-band parameters). Spectromics, which is a new method for exploiting spectral data for tissue metadata reconstruction, is proposed to further translate the related chemical information in 3D, as biochemical and anatomical tissue parameters. An example is given with oxidative stress distribution and the reconstruction of blood vessels in tissues. The requirements of IR microscopy instrumentation to propose 3D digital histology as a clinical routine technology is briefly discussed. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparison of low-contrast detectability between two CT reconstruction algorithms using voxel-based 3D printed textured phantoms.

PubMed

Solomon, Justin; Ba, Alexandre; Bochud, François; Samei, Ehsan

2016-12-01

To use novel voxel-based 3D printed textured phantoms in order to compare low-contrast detectability between two reconstruction algorithms, FBP (filtered-backprojection) and SAFIRE (sinogram affirmed iterative reconstruction) and determine what impact background texture (i.e., anatomical noise) has on estimating the dose reduction potential of SAFIRE. Liver volumes were segmented from 23 abdominal CT cases. The volumes were characterized in terms of texture features from gray-level co-occurrence and run-length matrices. Using a 3D clustered lumpy background (CLB) model, a fitting technique based on a genetic optimization algorithm was used to find CLB textures that were reflective of the liver textures, accounting for CT system factors of spatial blurring and noise. With the modeled background texture as a guide, four cylindrical phantoms (Textures A-C and uniform, 165 mm in diameter, and 30 mm height) were designed, each containing 20 low-contrast spherical signals (6 mm diameter at nominal contrast levels of ∼3.2, 5.2, 7.2, 10, and 14 HU with four repeats per signal). The phantoms were voxelized and input into a commercial multimaterial 3D printer (Object Connex 350), with custom software for voxel-based printing (using principles of digital dithering). Images of the textured phantoms and a corresponding uniform phantom were acquired at six radiation dose levels (SOMATOM Flash, Siemens Healthcare) and observer model detection performance (detectability index of a multislice channelized Hotelling observer) was estimated for each condition (5 contrasts × 6 doses × 2 reconstructions × 4 backgrounds = 240 total conditions). A multivariate generalized regression analysis was performed (linear terms, no interactions, random error term, log link function) to assess whether dose, reconstruction algorithm, signal contrast, and background type have statistically significant effects on detectability. Also, fitted curves of detectability (averaged across contrast levels

Combined registration of 3D tibia and femur implant models in 3D magnetic resonance images

NASA Astrophysics Data System (ADS)

Englmeier, Karl-Hans; Siebert, Markus; von Eisenhart-Rothe, Ruediger; Graichen, Heiko

2008-03-01

The most frequent reasons for revision of total knee arthroplasty are loosening and abnormal axial alignment leading to an unphysiological kinematic of the knee implant. To get an idea about the postoperative kinematic of the implant, it is essential to determine the position and orientation of the tibial and femoral prosthesis. Therefore we developed a registration method for fitting 3D CAD-models of knee joint prostheses into an 3D MR image. This rigid registration is the basis for a quantitative analysis of the kinematics of knee implants. Firstly the surface data of the prostheses models are converted into a voxel representation; a recursive algorithm determines all boundary voxels of the original triangular surface data. Secondly an initial preconfiguration of the implants by the user is still necessary for the following step: The user has to perform a rough preconfiguration of both remaining prostheses models, so that the fine matching process gets a reasonable starting point. After that an automated gradient-based fine matching process determines the best absolute position and orientation: This iterative process changes all 6 parameters (3 rotational- and 3 translational parameters) of a model by a minimal amount until a maximum value of the matching function is reached. To examine the spread of the final solutions of the registration, the interobserver variability was measured in a group of testers. This variability, calculated by the relative standard deviation, improved from about 50% (pure manual registration) to 0.5% (rough manual preconfiguration and subsequent fine registration with the automatic fine matching process).

Voxel Advanced Digital-Manufacturing for Earth and Regolith in Space Project

NASA Technical Reports Server (NTRS)

Zeitlin, Nancy; Mueller, Robert P.

2015-01-01

A voxel is a discrete three-dimensional (3D) element of material that is used to construct a larger 3D object. It is the 3D equivalent of a pixel. This project will conceptualize and study various approaches in order to develop a proof of concept 3D printing device that utilizes regolith as the material of the voxels. The goal is to develop a digital printer head capable of placing discrete self-aligning voxels in additive layers in order to fabricate small parts that can be given structural integrity through a post-printing sintering or other binding process. The quicker speeds possible with the voxel 3D printing approach along with the utilization of regolith material as the substrate will advance the use of this technology to applications for In-Situ Resource Utilization (ISRU), which is key to reducing logistics from Earth to Space, thus making long-duration human exploration missions to other celestial bodies more possible.

Automated 3D bioassembly of micro-tissues for biofabrication of hybrid tissue engineered constructs.

PubMed

Mekhileri, N V; Lim, K S; Brown, G C J; Mutreja, I; Schon, B S; Hooper, G J; Woodfield, T B F

2018-01-12

Bottom-up biofabrication approaches combining micro-tissue fabrication techniques with extrusion-based 3D printing of thermoplastic polymer scaffolds are emerging strategies in tissue engineering. These biofabrication strategies support native self-assembly mechanisms observed in developmental stages of tissue or organoid growth as well as promoting cell-cell interactions and cell differentiation capacity. Few technologies have been developed to automate the precise assembly of micro-tissues or tissue modules into structural scaffolds. We describe an automated 3D bioassembly platform capable of fabricating simple hybrid constructs via a two-step bottom-up bioassembly strategy, as well as complex hybrid hierarchical constructs via a multistep bottom-up bioassembly strategy. The bioassembly system consisted of a fluidic-based singularisation and injection module incorporated into a commercial 3D bioprinter. The singularisation module delivers individual micro-tissues to an injection module, for insertion into precise locations within a 3D plotted scaffold. To demonstrate applicability for cartilage tissue engineering, human chondrocytes were isolated and micro-tissues of 1 mm diameter were generated utilising a high throughput 96-well plate format. Micro-tissues were singularised with an efficiency of 96.0 ± 5.1%. There was no significant difference in size, shape or viability of micro-tissues before and after automated singularisation and injection. A layer-by-layer approach or aforementioned bottom-up bioassembly strategy was employed to fabricate a bilayered construct by alternatively 3D plotting a thermoplastic (PEGT/PBT) polymer scaffold and inserting pre-differentiated chondrogenic micro-tissues or cell-laden gelatin-based (GelMA) hydrogel micro-spheres, both formed via high-throughput fabrication techniques. No significant difference in viability between the construct assembled utilising the automated bioassembly system and manually assembled construct was

A discriminative model-constrained graph cuts approach to fully automated pediatric brain tumor segmentation in 3-D MRI.

PubMed

Wels, Michael; Carneiro, Gustavo; Aplas, Alexander; Huber, Martin; Hornegger, Joachim; Comaniciu, Dorin

2008-01-01

In this paper we present a fully automated approach to the segmentation of pediatric brain tumors in multi-spectral 3-D magnetic resonance images. It is a top-down segmentation approach based on a Markov random field (MRF) model that combines probabilistic boosting trees (PBT) and lower-level segmentation via graph cuts. The PBT algorithm provides a strong discriminative observation model that classifies tumor appearance while a spatial prior takes into account the pair-wise homogeneity in terms of classification labels and multi-spectral voxel intensities. The discriminative model relies not only on observed local intensities but also on surrounding context for detecting candidate regions for pathology. A mathematically sound formulation for integrating the two approaches into a unified statistical framework is given. The proposed method is applied to the challenging task of detection and delineation of pediatric brain tumors. This segmentation task is characterized by a high non-uniformity of both the pathology and the surrounding non-pathologic brain tissue. A quantitative evaluation illustrates the robustness of the proposed method. Despite dealing with more complicated cases of pediatric brain tumors the results obtained are mostly better than those reported for current state-of-the-art approaches to 3-D MR brain tumor segmentation in adult patients. The entire processing of one multi-spectral data set does not require any user interaction, and takes less time than previously proposed methods.

Voxel-Based LIDAR Analysis and Applications

NASA Astrophysics Data System (ADS)

Hagstrom, Shea T.

One of the greatest recent changes in the field of remote sensing is the addition of high-quality Light Detection and Ranging (LIDAR) instruments. In particular, the past few decades have been greatly beneficial to these systems because of increases in data collection speed and accuracy, as well as a reduction in the costs of components. These improvements allow modern airborne instruments to resolve sub-meter details, making them ideal for a wide variety of applications. Because LIDAR uses active illumination to capture 3D information, its output is fundamentally different from other modalities. Despite this difference, LIDAR datasets are often processed using methods appropriate for 2D images and that do not take advantage of its primary virtue of 3-dimensional data. It is this problem we explore by using volumetric voxel modeling. Voxel-based analysis has been used in many applications, especially medical imaging, but rarely in traditional remote sensing. In part this is because the memory requirements are substantial when handling large areas, but with modern computing and storage this is no longer a significant impediment. Our reason for using voxels to model scenes from LIDAR data is that there are several advantages over standard triangle-based models, including better handling of overlapping surfaces and complex shapes. We show how incorporating system position information from early in the LIDAR point cloud generation process allows radiometrically-correct transmission and other novel voxel properties to be recovered. This voxelization technique is validated on simulated data using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) software, a first-principles based ray-tracer developed at the Rochester Institute of Technology. Voxel-based modeling of LIDAR can be useful on its own, but we believe its primary advantage is when applied to problems where simpler surface-based 3D models conflict with the requirement of realistic geometry. To

WE-D-BRE-06: Quantification of Dose-Response for High Grade Esophagtis Patients Using a Novel Voxel-To-Voxel Method

DOE Office of Scientific and Technical Information (OSTI.GOV)

Niedzielski, J; Martel, M; Tucker, S

2014-06-15

Purpose: Radiation induces an inflammatory response in the esophagus, discernible on CT studies. This work objectively quantifies the voxel esophageal radiation-response for patients with acute esophagitis. This knowledge is an important first-step towards predicting the effect of complex dose distributions on patient esophagitis symptoms. Methods: A previously validated voxel-based methodology of quantifying radiation esophagitis severity was used to identify the voxel dose-response for 18 NSCLC patients with severe esophagitis (CTCAE grading criteria, grade2 or higher). The response is quantified as percent voxel volume change for a given dose. During treatment (6–8 weeks), patients had weekly 4DCT studies and esophagitis scoring.more » Planning CT esophageal contours were deformed to each weekly CT using a demons DIR algorithm. An algorithm using the Jacobian Map from the DIR of the planning CT to all weekly CTs was used to quantify voxel-volume change, along with corresponding delivered voxel dose, to the planning voxel. Dose for each voxel for each time-point was calculated on each previous weekly CT image, and accumulated using DIR. Thus, for each voxel, the volume-change and delivered dose was calculated for each time-point. The data was binned according to when the volume-change first increased by a threshold volume (10%–100%, in 10% increments), and the average delivered dose calculated for each bin. Results: The average dose resulting in a voxel volume increase of 10–100% was 21.6 to 45.9Gy, respectively. The mean population dose to give a 50% volume increase was 36.3±4.4Gy, (range:29.8 to 43.5Gy). The average week of 50% response was 4.1 (range:4.9 to 2.8 weeks). All 18 patients showed similar dose to first response curves, showing a common trend in the initial inflammatoryresponse. Conclusion: We extracted the dose-response curve of the esophagus on a voxel-to-voxel level. This may be useful for estimating the esophagus response (and patient

Design, fabrication, and implementation of voxel-based 3D printed textured phantoms for task-based image quality assessment in CT

NASA Astrophysics Data System (ADS)

Solomon, Justin; Ba, Alexandre; Diao, Andrew; Lo, Joseph; Bier, Elianna; Bochud, François; Gehm, Michael; Samei, Ehsan

2016-03-01

In x-ray computed tomography (CT), task-based image quality studies are typically performed using uniform background phantoms with low-contrast signals. Such studies may have limited clinical relevancy for modern non-linear CT systems due to possible influence of background texture on image quality. The purpose of this study was to design and implement anatomically informed textured phantoms for task-based assessment of low-contrast detection. Liver volumes were segmented from 23 abdominal CT cases. The volumes were characterized in terms of texture features from gray-level co-occurrence and run-length matrices. Using a 3D clustered lumpy background (CLB) model, a fitting technique based on a genetic optimization algorithm was used to find the CLB parameters that were most reflective of the liver textures, accounting for CT system factors of spatial blurring and noise. With the modeled background texture as a guide, a cylinder phantom (165 mm in diameter and 30 mm height) was designed, containing 20 low-contrast spherical signals (6 mm in diameter at targeted contrast levels of ~3.2, 5.2, 7.2, 10, and 14 HU, 4 repeats per signal). The phantom was voxelized and input into a commercial multi-material 3D printer (Object Connex 350), with custom software for voxel-based printing. Using principles of digital half-toning and dithering, the 3D printer was programmed to distribute two base materials (VeroWhite and TangoPlus, nominal voxel size of 42x84x30 microns) to achieve the targeted spatial distribution of x-ray attenuation properties. The phantom was used for task-based image quality assessment of a clinically available iterative reconstruction algorithm (Sinogram Affirmed Iterative Reconstruction, SAFIRE) using a channelized Hotelling observer paradigm. Images of the textured phantom and a corresponding uniform phantom were acquired at six dose levels and observer model performance was estimated for each condition (5 contrasts x 6 doses x 2 reconstructions x 2

Automated interpretation of 3D laserscanned point clouds for plant organ segmentation.

PubMed

Wahabzada, Mirwaes; Paulus, Stefan; Kersting, Kristian; Mahlein, Anne-Katrin

2015-08-08

Plant organ segmentation from 3D point clouds is a relevant task for plant phenotyping and plant growth observation. Automated solutions are required to increase the efficiency of recent high-throughput plant phenotyping pipelines. However, plant geometrical properties vary with time, among observation scales and different plant types. The main objective of the present research is to develop a fully automated, fast and reliable data driven approach for plant organ segmentation. The automated segmentation of plant organs using unsupervised, clustering methods is crucial in cases where the goal is to get fast insights into the data or no labeled data is available or costly to achieve. For this we propose and compare data driven approaches that are easy-to-realize and make the use of standard algorithms possible. Since normalized histograms, acquired from 3D point clouds, can be seen as samples from a probability simplex, we propose to map the data from the simplex space into Euclidean space using Aitchisons log ratio transformation, or into the positive quadrant of the unit sphere using square root transformation. This, in turn, paves the way to a wide range of commonly used analysis techniques that are based on measuring the similarities between data points using Euclidean distance. We investigate the performance of the resulting approaches in the practical context of grouping 3D point clouds and demonstrate empirically that they lead to clustering results with high accuracy for monocotyledonous and dicotyledonous plant species with diverse shoot architecture. An automated segmentation of 3D point clouds is demonstrated in the present work. Within seconds first insights into plant data can be deviated - even from non-labelled data. This approach is applicable to different plant species with high accuracy. The analysis cascade can be implemented in future high-throughput phenotyping scenarios and will support the evaluation of the performance of different plant

Second generation anthropomorphic physical phantom for mammography and DBT: Incorporating voxelized 3D printing and inkjet printing of iodinated lesion inserts

NASA Astrophysics Data System (ADS)

Sikaria, Dhiraj; Musinsky, Stephanie; Sturgeon, Gregory M.; Solomon, Justin; Diao, Andrew; Gehm, Michael E.; Samei, Ehsan; Glick, Stephen J.; Lo, Joseph Y.

2016-03-01

Physical phantoms are needed for the evaluation and optimization of new digital breast tomosynthesis (DBT) systems. Previously, we developed an anthropomorphic phantom based on human subject breast CT data and fabricated using commercial 3D printing. We now present three key advancements: voxelized 3D printing, photopolymer material doping, and 2D inkjet printing of lesion inserts. First, we bypassed the printer's control software in order to print in voxelized form instead of conventional STL surfaces, thus improving resolution and allowing dithering to mix the two photopolymer materials into arbitrary proportions. We demonstrated ability to print details as small as 150μm, and dithering to combine VeroWhitePlus and TangoPlus in 10% increments. Second, to address the limited attenuation difference among commercial photopolymers, we evaluated a beta sample from Stratasys with increased TiO2 doping concentration up to 2.5%, which corresponded to 98% breast density. By spanning 36% to 98% breast density, this doubles our previous contrast. Third, using inkjet printers modified to print with iopamidol, we created 2D lesion patterns on paper that can be sandwiched into the phantom. Inkjet printing has advantages of being inexpensive and easy, and more contrast can be delivered through overprinting. Printing resolution was maintained at 210 μm horizontally and 330 μm vertically even after 10 overprints. Contrast increased linearly with overprinting at 0.7% per overprint. Together, these three new features provide the basis for creating a new anthropomorphic physical breast phantom with improved resolution and contrast, as well as the ability to insert 2D lesions for task-based assessment of performance.

Geometry segmentation of voxelized representations of heterogeneous microstructures using betweenness centrality

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yuan, Rui; Singh, Sudhanshu S.; Chawla, Nikhilesh

2016-08-15

We present a robust method for automating removal of “segregation artifacts” in segmented tomographic images of three-dimensional heterogeneous microstructures. The objective of this method is to accurately identify and separate discrete features in composite materials where limitations in imaging resolution lead to spurious connections near close contacts. The method utilizes betweenness centrality, a measure of the importance of a node in the connectivity of a graph network, to identify voxels that create artificial bridges between otherwise distinct geometric features. To facilitate automation of the algorithm, we develop a relative centrality metric to allow for the selection of a threshold criterionmore » that is not sensitive to inclusion size or shape. As a demonstration of the effectiveness of the algorithm, we report on the segmentation of a 3D reconstruction of a SiC particle reinforced aluminum alloy, imaged by X-ray synchrotron tomography.« less

Automated Rapid Prototyping of 3D Ceramic Parts

NASA Technical Reports Server (NTRS)

McMillin, Scott G.; Griffin, Eugene A.; Griffin, Curtis W.; Coles, Peter W. H.; Engle, James D.

2005-01-01

An automated system of manufacturing equipment produces three-dimensional (3D) ceramic parts specified by computational models of the parts. The system implements an advanced, automated version of a generic rapid-prototyping process in which the fabrication of an object having a possibly complex 3D shape includes stacking of thin sheets, the outlines of which closely approximate the horizontal cross sections of the object at their respective heights. In this process, the thin sheets are made of a ceramic precursor material, and the stack is subsequently heated to transform it into a unitary ceramic object. In addition to the computer used to generate the computational model of the part to be fabricated, the equipment used in this process includes: 1) A commercially available laminated-object-manufacturing machine that was originally designed for building woodlike 3D objects from paper and was modified to accept sheets of ceramic precursor material, and 2) A machine designed specifically to feed single sheets of ceramic precursor material to the laminated-object-manufacturing machine. Like other rapid-prototyping processes that utilize stacking of thin sheets, this process begins with generation of the computational model of the part to be fabricated, followed by computational sectioning of the part into layers of predetermined thickness that collectively define the shape of the part. Information about each layer is transmitted to rapid-prototyping equipment, where the part is built layer by layer. What distinguishes this process from other rapid-prototyping processes that utilize stacking of thin sheets are the details of the machines and the actions that they perform. In this process, flexible sheets of ceramic precursor material (called "green" ceramic sheets) suitable for lamination are produced by tape casting. The binder used in the tape casting is specially formulated to enable lamination of layers with little or no applied heat or pressure. The tape is cut

Automated Quantification and Integrative Analysis of 2D and 3D Mitochondrial Shape and Network Properties

PubMed Central

Nikolaisen, Julie; Nilsson, Linn I. H.; Pettersen, Ina K. N.; Willems, Peter H. G. M.; Lorens, James B.; Koopman, Werner J. H.; Tronstad, Karl J.

2014-01-01

Mitochondrial morphology and function are coupled in healthy cells, during pathological conditions and (adaptation to) endogenous and exogenous stress. In this sense mitochondrial shape can range from small globular compartments to complex filamentous networks, even within the same cell. Understanding how mitochondrial morphological changes (i.e. “mitochondrial dynamics”) are linked to cellular (patho) physiology is currently the subject of intense study and requires detailed quantitative information. During the last decade, various computational approaches have been developed for automated 2-dimensional (2D) analysis of mitochondrial morphology and number in microscopy images. Although these strategies are well suited for analysis of adhering cells with a flat morphology they are not applicable for thicker cells, which require a three-dimensional (3D) image acquisition and analysis procedure. Here we developed and validated an automated image analysis algorithm allowing simultaneous 3D quantification of mitochondrial morphology and network properties in human endothelial cells (HUVECs). Cells expressing a mitochondria-targeted green fluorescence protein (mitoGFP) were visualized by 3D confocal microscopy and mitochondrial morphology was quantified using both the established 2D method and the new 3D strategy. We demonstrate that both analyses can be used to characterize and discriminate between various mitochondrial morphologies and network properties. However, the results from 2D and 3D analysis were not equivalent when filamentous mitochondria in normal HUVECs were compared with circular/spherical mitochondria in metabolically stressed HUVECs treated with rotenone (ROT). 2D quantification suggested that metabolic stress induced mitochondrial fragmentation and loss of biomass. In contrast, 3D analysis revealed that the mitochondrial network structure was dissolved without affecting the amount and size of the organelles. Thus, our results demonstrate that 3D

Voxel inversion of airborne electromagnetic data

NASA Astrophysics Data System (ADS)

Auken, E.; Fiandaca, G.; Kirkegaard, C.; Vest Christiansen, A.

2013-12-01

Inversion of electromagnetic data usually refers to a model space being linked to the actual observation points, and for airborne surveys the spatial discretization of the model space reflects the flight lines. On the contrary, geological and groundwater models most often refer to a regular voxel grid, not correlated to the geophysical model space. This means that incorporating the geophysical data into the geological and/or hydrological modelling grids involves a spatial relocation of the models, which in itself is a subtle process where valuable information is easily lost. Also the integration of prior information, e.g. from boreholes, is difficult when the observation points do not coincide with the position of the prior information, as well as the joint inversion of airborne and ground-based surveys. We developed a geophysical inversion algorithm working directly in a voxel grid disconnected from the actual measuring points, which then allows for informing directly geological/hydrogeological models, for easier incorporation of prior information and for straightforward integration of different data types in joint inversion. The new voxel model space defines the soil properties (like resistivity) on a set of nodes, and the distribution of the properties is computed everywhere by means of an interpolation function f (e.g. inverse distance or kriging). The position of the nodes is fixed during the inversion and is chosen to sample the soil taking into account topography and inversion resolution. Given this definition of the voxel model space, both 1D and 2D/3D forward responses can be computed. The 1D forward responses are computed as follows: A) a 1D model subdivision, in terms of model thicknesses and direction of the "virtual" horizontal stratification, is defined for each 1D data set. For EM soundings the "virtual" horizontal stratification is set up parallel to the topography at the sounding position. B) the "virtual" 1D models are constructed by interpolating

Calculation of Dose Deposition in 3D Voxels by Heavy Ions and Simulation of gamma-H2AX Experiments

NASA Technical Reports Server (NTRS)

Plante, I.; Ponomarev, A. L.; Wang, M.; Cucinotta, F. A.

2011-01-01

The biological response to high-LET radiation is different from low-LET radiation due to several factors, notably difference in energy deposition and formation of radiolytic species. Of particular importance in radiobiology is the formation of double-strand breaks (DSB), which can be detected by -H2AX foci experiments. These experiments has revealed important differences in the spatial distribution of DSB induced by low- and high-LET radiations [1,2]. To simulate -H2AX experiments, models based on amorphous track with radial dose are often combined with random walk chromosome models [3,4]. In this work, a new approach using the Monte-Carlo track structure code RITRACKS [5] and chromosome models have been used to simulate DSB formation. At first, RITRACKS have been used to simulate the irradiation of a cubic volume of 5 m by 1) 450 1H+ ions of 300 MeV (LET 0.3 keV/ m) and 2) by 1 56Fe26+ ion of 1 GeV/amu (LET 150 keV/ m). All energy deposition events are recorded to calculate dose in voxels of 20 m. The dose voxels are distributed randomly and scattered uniformly within the volume irradiated by low-LET radiation. Many differences are found in the spatial distribution of dose voxels for the 56Fe26+ ion. The track structure can be distinguished, and voxels with very high dose are found in the region corresponding to the track "core". These high-dose voxels are not found in the low-LET irradiation simulation and indicate clustered energy deposition, which may be responsible for complex DSB. In the second step, assuming that DSB will be found only in voxels where energy is deposited by the radiation, the intersection points between voxels with dose > 0 and simulated chromosomes were obtained. The spatial distribution of the intersection points is similar to -H2AX foci experiments. These preliminary results suggest that combining stochastic track structure and chromosome models could be a good approach to understand radiation-induced DSB and chromosome aberrations.

3D Actin Network Centerline Extraction with Multiple Active Contours

PubMed Central

Xu, Ting; Vavylonis, Dimitrios; Huang, Xiaolei

2013-01-01

Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and actin cables. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we propose a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open Active Contours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D Total Internal Reflection Fluorescence Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy. Quantitative evaluation of the method using synthetic images shows that for images with SNR above 5.0, the average vertex error measured by the distance between our result and ground truth is 1 voxel, and the average Hausdorff distance is below 10 voxels. PMID:24316442

Registration of 3D spectral OCT volumes using 3D SIFT feature point matching

NASA Astrophysics Data System (ADS)

Niemeijer, Meindert; Garvin, Mona K.; Lee, Kyungmoo; van Ginneken, Bram; Abràmoff, Michael D.; Sonka, Milan

2009-02-01

The recent introduction of next generation spectral OCT scanners has enabled routine acquisition of high resolution, 3D cross-sectional volumetric images of the retina. 3D OCT is used in the detection and management of serious eye diseases such as glaucoma and age-related macular degeneration. For follow-up studies, image registration is a vital tool to enable more precise, quantitative comparison of disease states. This work presents a registration method based on a recently introduced extension of the 2D Scale-Invariant Feature Transform (SIFT) framework1 to 3D.2 The SIFT feature extractor locates minima and maxima in the difference of Gaussian scale space to find salient feature points. It then uses histograms of the local gradient directions around each found extremum in 3D to characterize them in a 4096 element feature vector. Matching points are found by comparing the distance between feature vectors. We apply this method to the rigid registration of optic nerve head- (ONH) and macula-centered 3D OCT scans of the same patient that have only limited overlap. Three OCT data set pairs with known deformation were used for quantitative assessment of the method's robustness and accuracy when deformations of rotation and scaling were considered. Three-dimensional registration accuracy of 2.0+/-3.3 voxels was observed. The accuracy was assessed as average voxel distance error in N=1572 matched locations. The registration method was applied to 12 3D OCT scans (200 x 200 x 1024 voxels) of 6 normal eyes imaged in vivo to demonstrate the clinical utility and robustness of the method in a real-world environment.

Automated 3D structure composition for large RNAs

PubMed Central

Popenda, Mariusz; Szachniuk, Marta; Antczak, Maciej; Purzycka, Katarzyna J.; Lukasiak, Piotr; Bartol, Natalia; Blazewicz, Jacek; Adamiak, Ryszard W.

2012-01-01

Understanding the numerous functions that RNAs play in living cells depends critically on knowledge of their three-dimensional structure. Due to the difficulties in experimentally assessing structures of large RNAs, there is currently great demand for new high-resolution structure prediction methods. We present the novel method for the fully automated prediction of RNA 3D structures from a user-defined secondary structure. The concept is founded on the machine translation system. The translation engine operates on the RNA FRABASE database tailored to the dictionary relating the RNA secondary structure and tertiary structure elements. The translation algorithm is very fast. Initial 3D structure is composed in a range of seconds on a single processor. The method assures the prediction of large RNA 3D structures of high quality. Our approach needs neither structural templates nor RNA sequence alignment, required for comparative methods. This enables the building of unresolved yet native and artificial RNA structures. The method is implemented in a publicly available, user-friendly server RNAComposer. It works in an interactive mode and a batch mode. The batch mode is designed for large-scale modelling and accepts atomic distance restraints. Presently, the server is set to build RNA structures of up to 500 residues. PMID:22539264

Evaluation of an automated breast 3D-ultrasound system by comparing it with hand-held ultrasound (HHUS) and mammography.

PubMed

Golatta, Michael; Baggs, Christina; Schweitzer-Martin, Mirjam; Domschke, Christoph; Schott, Sarah; Harcos, Aba; Scharf, Alexander; Junkermann, Hans; Rauch, Geraldine; Rom, Joachim; Sohn, Christof; Heil, Joerg

2015-04-01

Automated three-dimensional (3D) breast ultrasound (US) systems are meant to overcome the shortcomings of hand-held ultrasound (HHUS). The aim of this study is to analyze and compare clinical performance of an automated 3D-US system by comparing it with HHUS, mammography and the clinical gold standard (defined as the combination of HHUS, mammography and-if indicated-histology). Nine hundred and eighty three patients (=1,966 breasts) were enrolled in this monocentric, explorative and prospective cohort study. All examinations were analyzed blinded to the patients´ history and to the results of the routine imaging. The agreement of automated 3D-US with HHUS, mammography and the gold standard was assessed with kappa statistics. Sensitivity, specificity and positive and negative predictive value were calculated to assess the test performance. Blinded to the results of the gold standard the agreement between automated 3D-US and HHUS or mammography was fair, given by a Kappa coefficient of 0.31 (95% CI [0.26;0.36], p < 0.0001) and 0.25 (95% CI [0.2;0.3], p < 0.0001), respectively. Our results showed a high negative predictive value (NPV) of 98%, a high specificity of 85% and a sensitivity of 74% based on the cases with US-guided biopsy. Including the cases where the lesion was seen in a second-look automated 3D-US the sensitivity improved to 84% (NPV = 99%, specificity = 85%). The results of this study let us suggest, that automated 3D-US might be a helpful new tool in breast imaging, especially in screening.

Voxel-based morphometry and automated lobar volumetry: The trade-off between spatial scale and statistical correction

PubMed Central

Voormolen, Eduard H.J.; Wei, Corie; Chow, Eva W.C.; Bassett, Anne S.; Mikulis, David J.; Crawley, Adrian P.

2011-01-01

Voxel-based morphometry (VBM) and automated lobar region of interest (ROI) volumetry are comprehensive and fast methods to detect differences in overall brain anatomy on magnetic resonance images. However, VBM and automated lobar ROI volumetry have detected dissimilar gray matter differences within identical image sets in our own experience and in previous reports. To gain more insight into how diverging results arise and to attempt to establish whether one method is superior to the other, we investigated how differences in spatial scale and in the need to statistically correct for multiple spatial comparisons influence the relative sensitivity of either technique to group differences in gray matter volumes. We assessed the performance of both techniques on a small dataset containing simulated gray matter deficits and additionally on a dataset of 22q11-deletion syndrome patients with schizophrenia (22q11DS-SZ) vs. matched controls. VBM was more sensitive to simulated focal deficits compared to automated ROI volumetry, and could detect global cortical deficits equally well. Moreover, theoretical calculations of VBM and ROI detection sensitivities to focal deficits showed that at increasing ROI size, ROI volumetry suffers more from loss in sensitivity than VBM. Furthermore, VBM and automated ROI found corresponding GM deficits in 22q11DS-SZ patients, except in the parietal lobe. Here, automated lobar ROI volumetry found a significant deficit only after a smaller subregion of interest was employed. Thus, sensitivity to focal differences is impaired relatively more by averaging over larger volumes in automated ROI methods than by the correction for multiple comparisons in VBM. These findings indicate that VBM is to be preferred over automated lobar-scale ROI volumetry for assessing gray matter volume differences between groups. PMID:19619660

Automated diagnosis of fetal alcohol syndrome using 3D facial image analysis

PubMed Central

Fang, Shiaofen; McLaughlin, Jason; Fang, Jiandong; Huang, Jeffrey; Autti-Rämö, Ilona; Fagerlund, Åse; Jacobson, Sandra W.; Robinson, Luther K.; Hoyme, H. Eugene; Mattson, Sarah N.; Riley, Edward; Zhou, Feng; Ward, Richard; Moore, Elizabeth S.; Foroud, Tatiana

2012-01-01

Objectives Use three-dimensional (3D) facial laser scanned images from children with fetal alcohol syndrome (FAS) and controls to develop an automated diagnosis technique that can reliably and accurately identify individuals prenatally exposed to alcohol. Methods A detailed dysmorphology evaluation, history of prenatal alcohol exposure, and 3D facial laser scans were obtained from 149 individuals (86 FAS; 63 Control) recruited from two study sites (Cape Town, South Africa and Helsinki, Finland). Computer graphics, machine learning, and pattern recognition techniques were used to automatically identify a set of facial features that best discriminated individuals with FAS from controls in each sample. Results An automated feature detection and analysis technique was developed and applied to the two study populations. A unique set of facial regions and features were identified for each population that accurately discriminated FAS and control faces without any human intervention. Conclusion Our results demonstrate that computer algorithms can be used to automatically detect facial features that can discriminate FAS and control faces. PMID:18713153

An automated 3D reconstruction method of UAV images

NASA Astrophysics Data System (ADS)

Liu, Jun; Wang, He; Liu, Xiaoyang; Li, Feng; Sun, Guangtong; Song, Ping

2015-10-01

In this paper a novel fully automated 3D reconstruction approach based on low-altitude unmanned aerial vehicle system (UAVs) images will be presented, which does not require previous camera calibration or any other external prior knowledge. Dense 3D point clouds are generated by integrating orderly feature extraction, image matching, structure from motion (SfM) and multi-view stereo (MVS) algorithms, overcoming many of the cost, time limitations of rigorous photogrammetry techniques. An image topology analysis strategy is introduced to speed up large scene reconstruction by taking advantage of the flight-control data acquired by UAV. Image topology map can significantly reduce the running time of feature matching by limiting the combination of images. A high-resolution digital surface model of the study area is produced base on UAV point clouds by constructing the triangular irregular network. Experimental results show that the proposed approach is robust and feasible for automatic 3D reconstruction of low-altitude UAV images, and has great potential for the acquisition of spatial information at large scales mapping, especially suitable for rapid response and precise modelling in disaster emergency.

a Voxel-Based Filtering Algorithm for Mobile LIDAR Data

NASA Astrophysics Data System (ADS)

Qin, H.; Guan, G.; Yu, Y.; Zhong, L.

2018-04-01

This paper presents a stepwise voxel-based filtering algorithm for mobile LiDAR data. In the first step, to improve computational efficiency, mobile LiDAR points, in xy-plane, are first partitioned into a set of two-dimensional (2-D) blocks with a given block size, in each of which all laser points are further organized into an octree partition structure with a set of three-dimensional (3-D) voxels. Then, a voxel-based upward growing processing is performed to roughly separate terrain from non-terrain points with global and local terrain thresholds. In the second step, the extracted terrain points are refined by computing voxel curvatures. This voxel-based filtering algorithm is comprehensively discussed in the analyses of parameter sensitivity and overall performance. An experimental study performed on multiple point cloud samples, collected by different commercial mobile LiDAR systems, showed that the proposed algorithm provides a promising solution to terrain point extraction from mobile point clouds.

Voxel-based dose prediction with multi-patient atlas selection for automated radiotherapy treatment planning

NASA Astrophysics Data System (ADS)

McIntosh, Chris; Purdie, Thomas G.

2017-01-01

Automating the radiotherapy treatment planning process is a technically challenging problem. The majority of automated approaches have focused on customizing and inferring dose volume objectives to be used in plan optimization. In this work we outline a multi-patient atlas-based dose prediction approach that learns to predict the dose-per-voxel for a novel patient directly from the computed tomography planning scan without the requirement of specifying any objectives. Our method learns to automatically select the most effective atlases for a novel patient, and then map the dose from those atlases onto the novel patient. We extend our previous work to include a conditional random field for the optimization of a joint distribution prior that matches the complementary goals of an accurately spatially distributed dose distribution while still adhering to the desired dose volume histograms. The resulting distribution can then be used for inverse-planning with a new spatial dose objective, or to create typical dose volume objectives for the canonical optimization pipeline. We investigated six treatment sites (633 patients for training and 113 patients for testing) and evaluated the mean absolute difference in all DVHs for the clinical and predicted dose distribution. The results on average are favorable in comparison to our previous approach (1.91 versus 2.57). Comparing our method with and without atlas-selection further validates that atlas-selection improved dose prediction on average in whole breast (0.64 versus 1.59), prostate (2.13 versus 4.07), and rectum (1.46 versus 3.29) while it is less important in breast cavity (0.79 versus 0.92) and lung (1.33 versus 1.27) for which there is high conformity and minimal dose shaping. In CNS brain, atlas-selection has the potential to be impactful (3.65 versus 5.09), but selecting the ideal atlas is the most challenging.

Automated 3D renal segmentation based on image partitioning

NASA Astrophysics Data System (ADS)

Yeghiazaryan, Varduhi; Voiculescu, Irina D.

2016-03-01

Despite several decades of research into segmentation techniques, automated medical image segmentation is barely usable in a clinical context, and still at vast user time expense. This paper illustrates unsupervised organ segmentation through the use of a novel automated labelling approximation algorithm followed by a hypersurface front propagation method. The approximation stage relies on a pre-computed image partition forest obtained directly from CT scan data. We have implemented all procedures to operate directly on 3D volumes, rather than slice-by-slice, because our algorithms are dimensionality-independent. The results picture segmentations which identify kidneys, but can easily be extrapolated to other body parts. Quantitative analysis of our automated segmentation compared against hand-segmented gold standards indicates an average Dice similarity coefficient of 90%. Results were obtained over volumes of CT data with 9 kidneys, computing both volume-based similarity measures (such as the Dice and Jaccard coefficients, true positive volume fraction) and size-based measures (such as the relative volume difference). The analysis considered both healthy and diseased kidneys, although extreme pathological cases were excluded from the overall count. Such cases are difficult to segment both manually and automatically due to the large amplitude of Hounsfield unit distribution in the scan, and the wide spread of the tumorous tissue inside the abdomen. In the case of kidneys that have maintained their shape, the similarity range lies around the values obtained for inter-operator variability. Whilst the procedure is fully automated, our tools also provide a light level of manual editing.

Automated abdominal plane and circumference estimation in 3D US for fetal screening

NASA Astrophysics Data System (ADS)

Lorenz, C.; Brosch, T.; Ciofolo-Veit, C.; Klinder, T.; Lefevre, T.; Cavallaro, A.; Salim, I.; Papageorghiou, A. T.; Raynaud, C.; Roundhill, D.; Rouet, L.; Schadewaldt, N.; Schmidt-Richberg, A.

2018-03-01

Ultrasound is increasingly becoming a 3D modality. Mechanical and matrix array transducers are able to deliver 3D images with good spatial and temporal resolution. The 3D imaging facilitates the application of automated image analysis to enhance workflows, which has the potential to make ultrasound a less operator dependent modality. However, the analysis of the more complex 3D images and definition of all examination standards on 2D images pose barriers to the use of 3D in daily clinical practice. In this paper, we address a part of the canonical fetal screening program, namely the localization of the abdominal cross-sectional plane with the corresponding measurement of the abdominal circumference in this plane. For this purpose, a fully automated pipeline has been designed starting with a random forest based anatomical landmark detection. A feature trained shape model of the fetal torso including inner organs with the abdominal cross-sectional plane encoded into the model is then transformed into the patient space using the landmark localizations. In a free-form deformation step, the model is individualized to the image, using a torso probability map generated by a convolutional neural network as an additional feature image. After adaptation, the abdominal plane and the abdominal torso contour in that plane are directly obtained. This allows the measurement of the abdominal circumference as well as the rendering of the plane for visual assessment. The method has been trained on 126 and evaluated on 42 abdominal 3D US datasets. An average plane offset error of 5.8 mm and an average relative circumference error of 4.9 % in the evaluation set could be achieved.

Two efficient label-equivalence-based connected-component labeling algorithms for 3-D binary images.

PubMed

He, Lifeng; Chao, Yuyan; Suzuki, Kenji

2011-08-01

Whenever one wants to distinguish, recognize, and/or measure objects (connected components) in binary images, labeling is required. This paper presents two efficient label-equivalence-based connected-component labeling algorithms for 3-D binary images. One is voxel based and the other is run based. For the voxel-based one, we present an efficient method of deciding the order for checking voxels in the mask. For the run-based one, instead of assigning each foreground voxel, we assign each run a provisional label. Moreover, we use run data to label foreground voxels without scanning any background voxel in the second scan. Experimental results have demonstrated that our voxel-based algorithm is efficient for 3-D binary images with complicated connected components, that our run-based one is efficient for those with simple connected components, and that both are much more efficient than conventional 3-D labeling algorithms.

A Corner-Point-Grid-Based Voxelization Method for Complex Geological Structure Model with Folds

NASA Astrophysics Data System (ADS)

Chen, Qiyu; Mariethoz, Gregoire; Liu, Gang

2017-04-01

3D voxelization is the foundation of geological property modeling, and is also an effective approach to realize the 3D visualization of the heterogeneous attributes in geological structures. The corner-point grid is a representative data model among all voxel models, and is a structured grid type that is widely applied at present. When carrying out subdivision for complex geological structure model with folds, we should fully consider its structural morphology and bedding features to make the generated voxels keep its original morphology. And on the basis of which, they can depict the detailed bedding features and the spatial heterogeneity of the internal attributes. In order to solve the shortage of the existing technologies, this work puts forward a corner-point-grid-based voxelization method for complex geological structure model with folds. We have realized the fast conversion from the 3D geological structure model to the fine voxel model according to the rule of isocline in Ramsay's fold classification. In addition, the voxel model conforms to the spatial features of folds, pinch-out and other complex geological structures, and the voxels of the laminas inside a fold accords with the result of geological sedimentation and tectonic movement. This will provide a carrier and model foundation for the subsequent attribute assignment as well as the quantitative analysis and evaluation based on the spatial voxels. Ultimately, we use examples and the contrastive analysis between the examples and the Ramsay's description of isoclines to discuss the effectiveness and advantages of the method proposed in this work when dealing with the voxelization of 3D geologic structural model with folds based on corner-point grids.

Dynamic CT myocardial perfusion imaging: performance of 3D semi-automated evaluation software.

PubMed

Ebersberger, Ullrich; Marcus, Roy P; Schoepf, U Joseph; Lo, Gladys G; Wang, Yining; Blanke, Philipp; Geyer, Lucas L; Gray, J Cranston; McQuiston, Andrew D; Cho, Young Jun; Scheuering, Michael; Canstein, Christian; Nikolaou, Konstantin; Hoffmann, Ellen; Bamberg, Fabian

2014-01-01

To evaluate the performance of three-dimensional semi-automated evaluation software for the assessment of myocardial blood flow (MBF) and blood volume (MBV) at dynamic myocardial perfusion computed tomography (CT). Volume-based software relying on marginal space learning and probabilistic boosting tree-based contour fitting was applied to CT myocardial perfusion imaging data of 37 subjects. In addition, all image data were analysed manually and both approaches were compared with SPECT findings. Study endpoints included time of analysis and conventional measures of diagnostic accuracy. Of 592 analysable segments, 42 showed perfusion defects on SPECT. Average analysis times for the manual and software-based approaches were 49.1 ± 11.2 and 16.5 ± 3.7 min respectively (P < 0.01). There was strong agreement between the two measures of interest (MBF, ICC = 0.91, and MBV, ICC = 0.88, both P < 0.01) and no significant difference in MBF/MBV with respect to diagnostic accuracy between the two approaches for both MBF and MBV for manual versus software-based approach; respectively; all comparisons P > 0.05. Three-dimensional semi-automated evaluation of dynamic myocardial perfusion CT data provides similar measures and diagnostic accuracy to manual evaluation, albeit with substantially reduced analysis times. This capability may aid the integration of this test into clinical workflows. • Myocardial perfusion CT is attractive for comprehensive coronary heart disease assessment. • Traditional image analysis methods are cumbersome and time-consuming. • Automated 3D perfusion software shortens analysis times. • Automated 3D perfusion software increases standardisation of myocardial perfusion CT. • Automated, standardised analysis fosters myocardial perfusion CT integration into clinical practice.

SU-F-J-93: Automated Segmentation of High-Resolution 3D WholeBrain Spectroscopic MRI for Glioblastoma Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schreibmann, E; Shu, H; Cordova, J

Purpose: We report on an automated segmentation algorithm for defining radiation therapy target volumes using spectroscopic MR images (sMRI) acquired at nominal voxel resolution of 100 microliters. Methods: Wholebrain sMRI combining 3D echo-planar spectroscopic imaging, generalized auto-calibrating partially-parallel acquisitions, and elliptical k-space encoding were conducted on 3T MRI scanner with 32-channel head coil array creating images. Metabolite maps generated include choline (Cho), creatine (Cr), and N-acetylaspartate (NAA), as well as Cho/NAA, Cho/Cr, and NAA/Cr ratio maps. Automated segmentation was achieved by concomitantly considering sMRI metabolite maps with standard contrast enhancing (CE) imaging in a pipeline that first uses the watermore » signal for skull stripping. Subsequently, an initial blob of tumor region is identified by searching for regions of FLAIR abnormalities that also display reduced NAA activity using a mean ratio correlation and morphological filters. These regions are used as starting point for a geodesic level-set refinement that adapts the initial blob to the fine details specific to each metabolite. Results: Accuracy of the segmentation model was tested on a cohort of 12 patients that had sMRI datasets acquired pre, mid and post-treatment, providing a broad range of enhancement patterns. Compared to classical imaging, where heterogeneity in the tumor appearance and shape across posed a greater challenge to the algorithm, sMRI’s regions of abnormal activity were easily detected in the sMRI metabolite maps when combining the detail available in the standard imaging with the local enhancement produced by the metabolites. Results can be imported in the treatment planning, leading in general increase in the target volumes (GTV60) when using sMRI+CE MRI compared to the standard CE MRI alone. Conclusion: Integration of automated segmentation of sMRI metabolite maps into planning is feasible and will likely streamline acceptance

3D model assisted fully automated scanning laser Doppler vibrometer measurements

NASA Astrophysics Data System (ADS)

Sels, Seppe; Ribbens, Bart; Bogaerts, Boris; Peeters, Jeroen; Vanlanduit, Steve

2017-12-01

In this paper, a new fully automated scanning laser Doppler vibrometer (LDV) measurement technique is presented. In contrast to existing scanning LDV techniques which use a 2D camera for the manual selection of sample points, we use a 3D Time-of-Flight camera in combination with a CAD file of the test object to automatically obtain measurements at pre-defined locations. The proposed procedure allows users to test prototypes in a shorter time because physical measurement locations are determined without user interaction. Another benefit from this methodology is that it incorporates automatic mapping between a CAD model and the vibration measurements. This mapping can be used to visualize measurements directly on a 3D CAD model. The proposed method is illustrated with vibration measurements of an unmanned aerial vehicle

Automated Computational Processing of 3-D MR Images of Mouse Brain for Phenotyping of Living Animals.

PubMed

Medina, Christopher S; Manifold-Wheeler, Brett; Gonzales, Aaron; Bearer, Elaine L

2017-07-05

Magnetic resonance (MR) imaging provides a method to obtain anatomical information from the brain in vivo that is not typically available by optical imaging because of this organ's opacity. MR is nondestructive and obtains deep tissue contrast with 100-µm 3 voxel resolution or better. Manganese-enhanced MRI (MEMRI) may be used to observe axonal transport and localized neural activity in the living rodent and avian brain. Such enhancement enables researchers to investigate differences in functional circuitry or neuronal activity in images of brains of different animals. Moreover, once MR images of a number of animals are aligned into a single matrix, statistical analysis can be done comparing MR intensities between different multi-animal cohorts comprising individuals from different mouse strains or different transgenic animals, or at different time points after an experimental manipulation. Although preprocessing steps for such comparisons (including skull stripping and alignment) are automated for human imaging, no such automated processing has previously been readily available for mouse or other widely used experimental animals, and most investigators use in-house custom processing. This protocol describes a stepwise method to perform such preprocessing for mouse. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Automated Assignment of MS/MS Cleavable Cross-Links in Protein 3D-Structure Analysis

NASA Astrophysics Data System (ADS)

Götze, Michael; Pettelkau, Jens; Fritzsche, Romy; Ihling, Christian H.; Schäfer, Mathias; Sinz, Andrea

2015-01-01

CID-MS/MS cleavable cross-linkers hold an enormous potential for an automated analysis of cross-linked products, which is essential for conducting structural proteomics studies. The created characteristic fragment ion patterns can easily be used for an automated assignment and discrimination of cross-linked products. To date, there are only a few software solutions available that make use of these properties, but none allows for an automated analysis of cleavable cross-linked products. The MeroX software fills this gap and presents a powerful tool for protein 3D-structure analysis in combination with MS/MS cleavable cross-linkers. We show that MeroX allows an automatic screening of characteristic fragment ions, considering static and variable peptide modifications, and effectively scores different types of cross-links. No manual input is required for a correct assignment of cross-links and false discovery rates are calculated. The self-explanatory graphical user interface of MeroX provides easy access for an automated cross-link search platform that is compatible with commonly used data file formats, enabling analysis of data originating from different instruments. The combination of an MS/MS cleavable cross-linker with a dedicated software tool for data analysis provides an automated workflow for 3D-structure analysis of proteins. MeroX is available at www.StavroX.com .

3D printed fluidics with embedded analytic functionality for automated reaction optimisation

PubMed Central

Capel, Andrew J; Wright, Andrew; Harding, Matthew J; Weaver, George W; Li, Yuqi; Harris, Russell A; Edmondson, Steve; Goodridge, Ruth D

2017-01-01

Additive manufacturing or ‘3D printing’ is being developed as a novel manufacturing process for the production of bespoke micro- and milliscale fluidic devices. When coupled with online monitoring and optimisation software, this offers an advanced, customised method for performing automated chemical synthesis. This paper reports the use of two additive manufacturing processes, stereolithography and selective laser melting, to create multifunctional fluidic devices with embedded reaction monitoring capability. The selectively laser melted parts are the first published examples of multifunctional 3D printed metal fluidic devices. These devices allow high temperature and pressure chemistry to be performed in solvent systems destructive to the majority of devices manufactured via stereolithography, polymer jetting and fused deposition modelling processes previously utilised for this application. These devices were integrated with commercially available flow chemistry, chromatographic and spectroscopic analysis equipment, allowing automated online and inline optimisation of the reaction medium. This set-up allowed the optimisation of two reactions, a ketone functional group interconversion and a fused polycyclic heterocycle formation, via spectroscopic and chromatographic analysis. PMID:28228852

Interactive voxel graphics in virtual reality

NASA Astrophysics Data System (ADS)

Brody, Bill; Chappell, Glenn G.; Hartman, Chris

2002-06-01

Interactive voxel graphics in virtual reality poses significant research challenges in terms of interface, file I/O, and real-time algorithms. Voxel graphics is not so new, as it is the focus of a good deal of scientific visualization. Interactive voxel creation and manipulation is a more innovative concept. Scientists are understandably reluctant to manipulate data. They collect or model data. A scientific analogy to interactive graphics is the generation of initial conditions for some model. It is used as a method to test those models. We, however, are in the business of creating new data in the form of graphical imagery. In our endeavor, science is a tool and not an end. Nevertheless, there is a whole class of interactions and associated data generation scenarios that are natural to our way of working and that are also appropriate to scientific inquiry. Annotation by sketching or painting to point to and distinguish interesting and important information is very significant for science as well as art. Annotation in 3D is difficult without a good 3D interface. Interactive graphics in virtual reality is an appropriate approach to this problem.

Laser-induced forward transfer (LIFT) of congruent voxels

NASA Astrophysics Data System (ADS)

Piqué, Alberto; Kim, Heungsoo; Auyeung, Raymond C. Y.; Beniam, Iyoel; Breckenfeld, Eric

2016-06-01

Laser-induced forward transfer (LIFT) of functional materials offers unique advantages and capabilities for the rapid prototyping of electronic, optical and sensor elements. The use of LIFT for printing high viscosity metallic nano-inks and nano-pastes can be optimized for the transfer of voxels congruent with the shape of the laser pulse, forming thin film-like structures non-lithographically. These processes are capable of printing patterns with excellent lateral resolution and thickness uniformity typically found in 3-dimensional stacked assemblies, MEMS-like structures and free-standing interconnects. However, in order to achieve congruent voxel transfer with LIFT, the particle size and viscosity of the ink or paste suspensions must be adjusted to minimize variations due to wetting and drying effects. When LIFT is carried out with high-viscosity nano-suspensions, the printed voxel size and shape become controllable parameters, allowing the printing of thin-film like structures whose shape is determined by the spatial distribution of the laser pulse. The result is a new level of parallelization beyond current serial direct-write processes whereby the geometry of each printed voxel can be optimized according to the pattern design. This work shows how LIFT of congruent voxels can be applied to the fabrication of 2D and 3D microstructures by adjusting the viscosity of the nano-suspension and laser transfer parameters.

FIJI Macro 3D ART VeSElecT: 3D Automated Reconstruction Tool for Vesicle Structures of Electron Tomograms

PubMed Central

Kaltdorf, Kristin Verena; Schulze, Katja; Helmprobst, Frederik; Kollmannsberger, Philip; Stigloher, Christian

2017-01-01

Automatic image reconstruction is critical to cope with steadily increasing data from advanced microscopy. We describe here the Fiji macro 3D ART VeSElecT which we developed to study synaptic vesicles in electron tomograms. We apply this tool to quantify vesicle properties (i) in embryonic Danio rerio 4 and 8 days past fertilization (dpf) and (ii) to compare Caenorhabditis elegans N2 neuromuscular junctions (NMJ) wild-type and its septin mutant (unc-59(e261)). We demonstrate development-specific and mutant-specific changes in synaptic vesicle pools in both models. We confirm the functionality of our macro by applying our 3D ART VeSElecT on zebrafish NMJ showing smaller vesicles in 8 dpf embryos then 4 dpf, which was validated by manual reconstruction of the vesicle pool. Furthermore, we analyze the impact of C. elegans septin mutant unc-59(e261) on vesicle pool formation and vesicle size. Automated vesicle registration and characterization was implemented in Fiji as two macros (registration and measurement). This flexible arrangement allows in particular reducing false positives by an optional manual revision step. Preprocessing and contrast enhancement work on image-stacks of 1nm/pixel in x and y direction. Semi-automated cell selection was integrated. 3D ART VeSElecT removes interfering components, detects vesicles by 3D segmentation and calculates vesicle volume and diameter (spherical approximation, inner/outer diameter). Results are collected in color using the RoiManager plugin including the possibility of manual removal of non-matching confounder vesicles. Detailed evaluation considered performance (detected vesicles) and specificity (true vesicles) as well as precision and recall. We furthermore show gain in segmentation and morphological filtering compared to learning based methods and a large time gain compared to manual segmentation. 3D ART VeSElecT shows small error rates and its speed gain can be up to 68 times faster in comparison to manual annotation

Automated voxel classification used with atlas-guided diffuse optical tomography for assessment of functional brain networks in young and older adults.

PubMed

Li, Lin; Cazzell, Mary; Babawale, Olajide; Liu, Hanli

2016-10-01

Atlas-guided diffuse optical tomography (atlas-DOT) is a computational means to image changes in cortical hemodynamic signals during human brain activities. Graph theory analysis (GTA) is a network analysis tool commonly used in functional neuroimaging to study brain networks. Atlas-DOT has not been analyzed with GTA to derive large-scale brain connectivity/networks based on near-infrared spectroscopy (NIRS) measurements. We introduced an automated voxel classification (AVC) method that facilitated the use of GTA with atlas-DOT images by grouping unequal-sized finite element voxels into anatomically meaningful regions of interest within the human brain. The overall approach included volume segmentation, AVC, and cross-correlation. To demonstrate the usefulness of AVC, we applied reproducibility analysis to resting-state functional connectivity measurements conducted from 15 young adults in a two-week period. We also quantified and compared changes in several brain network metrics between young and older adults, which were in agreement with those reported by a previous positron emission tomography study. Overall, this study demonstrated that AVC is a useful means for facilitating integration or combination of atlas-DOT with GTA and thus for quantifying NIRS-based, voxel-wise resting-state functional brain networks.

From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

PubMed Central

Tsai, Wen-Ting; Hassan, Ahmed; Sarkar, Purbasha; Correa, Joaquin; Metlagel, Zoltan; Jorgens, Danielle M.; Auer, Manfred

2014-01-01

Modern 3D electron microscopy approaches have recently allowed unprecedented insight into the 3D ultrastructural organization of cells and tissues, enabling the visualization of large macromolecular machines, such as adhesion complexes, as well as higher-order structures, such as the cytoskeleton and cellular organelles in their respective cell and tissue context. Given the inherent complexity of cellular volumes, it is essential to first extract the features of interest in order to allow visualization, quantification, and therefore comprehension of their 3D organization. Each data set is defined by distinct characteristics, e.g., signal-to-noise ratio, crispness (sharpness) of the data, heterogeneity of its features, crowdedness of features, presence or absence of characteristic shapes that allow for easy identification, and the percentage of the entire volume that a specific region of interest occupies. All these characteristics need to be considered when deciding on which approach to take for segmentation. The six different 3D ultrastructural data sets presented were obtained by three different imaging approaches: resin embedded stained electron tomography, focused ion beam- and serial block face- scanning electron microscopy (FIB-SEM, SBF-SEM) of mildly stained and heavily stained samples, respectively. For these data sets, four different segmentation approaches have been applied: (1) fully manual model building followed solely by visualization of the model, (2) manual tracing segmentation of the data followed by surface rendering, (3) semi-automated approaches followed by surface rendering, or (4) automated custom-designed segmentation algorithms followed by surface rendering and quantitative analysis. Depending on the combination of data set characteristics, it was found that typically one of these four categorical approaches outperforms the others, but depending on the exact sequence of criteria, more than one approach may be successful. Based on these data

Quality control of 3D Geological Models using an Attention Model based on Gaze

NASA Astrophysics Data System (ADS)

Busschers, Freek S.; van Maanen, Peter-Paul; Brouwer, Anne-Marie

2014-05-01

The Geological Survey of the Netherlands (GSN) produces 3D stochastic geological models of the upper 50 meters of the Dutch subsurface. The voxel models are regarded essential in answering subsurface questions on, for example, aggregate resources, groundwater flow, land subsidence studies and the planning of large-scale infrastructural works such as tunnels. GeoTOP is the most recent and detailed generation of 3D voxel models. This model describes 3D lithological variability up to a depth of 50 m using voxels of 100*100*0.5m. Due to the expected increase in data-flow, model output and user demands, the development of (semi-)automated quality control systems is getting more important in the near future. Besides numerical control systems, capturing model errors as seen from the expert geologist viewpoint is of increasing interest. We envision the use of eye gaze to support and speed up detection of errors in the geological voxel models. As a first step in this direction we explore gaze behavior of 12 geological experts from the GSN during quality control of part of the GeoTOP 3D geological model using an eye-tracker. Gaze is used as input of an attention model that results in 'attended areas' for each individual examined image of the GeoTOP model and each individual expert. We compared these attended areas to errors as marked by the experts using a mouse. Results show that: 1) attended areas as determined from experts' gaze data largely match with GeoTOP errors as indicated by the experts using a mouse, and 2) a substantial part of the match can be reached using only gaze data from the first few seconds of the time geologists spend to search for errors. These results open up the possibility of faster GeoTOP model control using gaze if geologists accept a small decrease of error detection accuracy. Attention data may also be used to make independent comparisons between different geologists varying in focus and expertise. This would facilitate a more effective use of

Automated detection, 3D segmentation and analysis of high resolution spine MR images using statistical shape models

NASA Astrophysics Data System (ADS)

Neubert, A.; Fripp, J.; Engstrom, C.; Schwarz, R.; Lauer, L.; Salvado, O.; Crozier, S.

2012-12-01

Recent advances in high resolution magnetic resonance (MR) imaging of the spine provide a basis for the automated assessment of intervertebral disc (IVD) and vertebral body (VB) anatomy. High resolution three-dimensional (3D) morphological information contained in these images may be useful for early detection and monitoring of common spine disorders, such as disc degeneration. This work proposes an automated approach to extract the 3D segmentations of lumbar and thoracic IVDs and VBs from MR images using statistical shape analysis and registration of grey level intensity profiles. The algorithm was validated on a dataset of volumetric scans of the thoracolumbar spine of asymptomatic volunteers obtained on a 3T scanner using the relatively new 3D T2-weighted SPACE pulse sequence. Manual segmentations and expert radiological findings of early signs of disc degeneration were used in the validation. There was good agreement between manual and automated segmentation of the IVD and VB volumes with the mean Dice scores of 0.89 ± 0.04 and 0.91 ± 0.02 and mean absolute surface distances of 0.55 ± 0.18 mm and 0.67 ± 0.17 mm respectively. The method compares favourably to existing 3D MR segmentation techniques for VBs. This is the first time IVDs have been automatically segmented from 3D volumetric scans and shape parameters obtained were used in preliminary analyses to accurately classify (100% sensitivity, 98.3% specificity) disc abnormalities associated with early degenerative changes.

Reproducibility of a novel echocardiographic 3D automated software for the assessment of mitral valve anatomy.

PubMed

Aquila, Iolanda; González, Ariana; Fernández-Golfín, Covadonga; Rincón, Luis Miguel; Casas, Eduardo; García, Ana; Hinojar, Rocio; Jiménez-Nacher, José Julio; Zamorano, José Luis

2016-05-17

3D transesophageal echocardiography (TEE) is superior to 2D TEE in quantitative anatomic evaluation of the mitral valve (MV) but it shows limitations regarding automatic quantification. Here, we tested the inter-/intra-observer reproducibility of a novel full-automated software in the evaluation of MV anatomy compared to manual 3D assessment. Thirty-six out of 61 screened patients referred to our Cardiac Imaging Unit for TEE were retrospectively included. 3D TEE analysis was performed both manually and with the automated software by two independent operators. Mitral annular area, intercommissural distance, anterior leaflet length and posterior leaflet length were assessed. A significant correlation between both methods was found for all variables: intercommissural diameter (r = 0.84, p < 0.01), mitral annular area (r = 0.94, p > 0, 01), anterior leaflet length (r = 0.83, p < 0.01) and posterior leaflet length (r = 0.67, p < 0.01). Interobserver variability assessed by the intraclass correlation coefficient was superior for the automatic software: intercommisural distance 0.997 vs. 0.76; mitral annular area 0.957 vs. 0.858; anterior leaflet length 0.963 vs. 0.734 and posterior leaflet length 0.936 vs. 0.838. Intraobserver variability was good for both methods with a better level of agreement with the automatic software. The novel 3D automated software is reproducible in MV anatomy assessment. The incorporation of this new tool in clinical MV assessment may improve patient selection and outcomes for MV interventions as well as patient diagnosis and prognosis stratification. Yet, high-quality 3D images are indispensable.

Effects of voxelization on dose volume histogram accuracy

NASA Astrophysics Data System (ADS)

Sunderland, Kyle; Pinter, Csaba; Lasso, Andras; Fichtinger, Gabor

2016-03-01

PURPOSE: In radiotherapy treatment planning systems, structures of interest such as targets and organs at risk are stored as 2D contours on evenly spaced planes. In order to be used in various algorithms, contours must be converted into binary labelmap volumes using voxelization. The voxelization process results in lost information, which has little effect on the volume of large structures, but has significant impact on small structures, which contain few voxels. Volume differences for segmented structures affects metrics such as dose volume histograms (DVH), which are used for treatment planning. Our goal is to evaluate the impact of voxelization on segmented structures, as well as how factors like voxel size affects metrics, such as DVH. METHODS: We create a series of implicit functions, which represent simulated structures. These structures are sampled at varying resolutions, and compared to labelmaps with high sub-millimeter resolutions. We generate DVH and evaluate voxelization error for the same structures at different resolutions by calculating the agreement acceptance percentage between the DVH. RESULTS: We implemented tools for analysis as modules in the SlicerRT toolkit based on the 3D Slicer platform. We found that there were large DVH variation from the baseline for small structures or for structures located in regions with a high dose gradient, potentially leading to the creation of suboptimal treatment plans. CONCLUSION: This work demonstrates that labelmap and dose volume voxel size is an important factor in DVH accuracy, which must be accounted for in order to ensure the development of accurate treatment plans.

Early detection of glaucoma by means of a novel 3D computer‐automated visual field test

PubMed Central

Nazemi, Paul P; Fink, Wolfgang; Sadun, Alfredo A; Francis, Brian; Minckler, Donald

2007-01-01

Purpose A recently devised 3D computer‐automated threshold Amsler grid test was used to identify early and distinctive defects in people with suspected glaucoma. Further, the location, shape and depth of these field defects were characterised. Finally, the visual fields were compared with those obtained by standard automated perimetry. Patients and methods Glaucoma suspects were defined as those having elevated intraocular pressure (>21 mm Hg) or cup‐to‐disc ratio of >0.5. 33 patients and 66 eyes with risk factors for glaucoma were examined. 15 patients and 23 eyes with no risk factors were tested as controls. The recently developed 3D computer‐automated threshold Amsler grid test was used. The test exhibits a grid on a computer screen at a preselected greyscale and angular resolution, and allows patients to trace those areas on the grid that are missing in their visual field using a touch screen. The 5‐minute test required that the patients repeatedly outline scotomas on a touch screen with varied displays of contrast while maintaining their gaze on a central fixation marker. A 3D depiction of the visual field defects was then obtained that was further characterised by the location, shape and depth of the scotomas. The exam was repeated three times per eye. The results were compared to Humphrey visual field tests (ie, achromatic standard or SITA standard 30‐2 or 24‐2). Results In this pilot study 79% of the eyes tested in the glaucoma‐suspect group repeatedly demonstrated visual field loss with the 3D perimetry. The 3D depictions of visual field loss associated with these risk factors were all characteristic of or compatible with glaucoma. 71% of the eyes demonstrated arcuate defects or a nasal step. Constricted visual fields were shown in 29% of the eyes. No visual field changes were detected in the control group. Conclusions The 3D computer‐automated threshold Amsler grid test may demonstrate visual field abnormalities characteristic of

A review of automated image understanding within 3D baggage computed tomography security screening.

PubMed

Mouton, Andre; Breckon, Toby P

2015-01-01

Baggage inspection is the principal safeguard against the transportation of prohibited and potentially dangerous materials at airport security checkpoints. Although traditionally performed by 2D X-ray based scanning, increasingly stringent security regulations have led to a growing demand for more advanced imaging technologies. The role of X-ray Computed Tomography is thus rapidly expanding beyond the traditional materials-based detection of explosives. The development of computer vision and image processing techniques for the automated understanding of 3D baggage-CT imagery is however, complicated by poor image resolutions, image clutter and high levels of noise and artefacts. We discuss the recent and most pertinent advancements and identify topics for future research within the challenging domain of automated image understanding for baggage security screening CT.

The digital code driven autonomous synthesis of ibuprofen automated in a 3D-printer-based robot.

PubMed

Kitson, Philip J; Glatzel, Stefan; Cronin, Leroy

2016-01-01

An automated synthesis robot was constructed by modifying an open source 3D printing platform. The resulting automated system was used to 3D print reaction vessels (reactionware) of differing internal volumes using polypropylene feedstock via a fused deposition modeling 3D printing approach and subsequently make use of these fabricated vessels to synthesize the nonsteroidal anti-inflammatory drug ibuprofen via a consecutive one-pot three-step approach. The synthesis of ibuprofen could be achieved on different scales simply by adjusting the parameters in the robot control software. The software for controlling the synthesis robot was written in the python programming language and hard-coded for the synthesis of ibuprofen by the method described, opening possibilities for the sharing of validated synthetic 'programs' which can run on similar low cost, user-constructed robotic platforms towards an 'open-source' regime in the area of chemical synthesis.

The digital code driven autonomous synthesis of ibuprofen automated in a 3D-printer-based robot

PubMed Central

Kitson, Philip J; Glatzel, Stefan

2016-01-01

An automated synthesis robot was constructed by modifying an open source 3D printing platform. The resulting automated system was used to 3D print reaction vessels (reactionware) of differing internal volumes using polypropylene feedstock via a fused deposition modeling 3D printing approach and subsequently make use of these fabricated vessels to synthesize the nonsteroidal anti-inflammatory drug ibuprofen via a consecutive one-pot three-step approach. The synthesis of ibuprofen could be achieved on different scales simply by adjusting the parameters in the robot control software. The software for controlling the synthesis robot was written in the python programming language and hard-coded for the synthesis of ibuprofen by the method described, opening possibilities for the sharing of validated synthetic ‘programs’ which can run on similar low cost, user-constructed robotic platforms towards an ‘open-source’ regime in the area of chemical synthesis. PMID:28144350

Sloped terrain segmentation for autonomous drive using sparse 3D point cloud.

PubMed

Cho, Seoungjae; Kim, Jonghyun; Ikram, Warda; Cho, Kyungeun; Jeong, Young-Sik; Um, Kyhyun; Sim, Sungdae

2014-01-01

A ubiquitous environment for road travel that uses wireless networks requires the minimization of data exchange between vehicles. An algorithm that can segment the ground in real time is necessary to obtain location data between vehicles simultaneously executing autonomous drive. This paper proposes a framework for segmenting the ground in real time using a sparse three-dimensional (3D) point cloud acquired from undulating terrain. A sparse 3D point cloud can be acquired by scanning the geography using light detection and ranging (LiDAR) sensors. For efficient ground segmentation, 3D point clouds are quantized in units of volume pixels (voxels) and overlapping data is eliminated. We reduce nonoverlapping voxels to two dimensions by implementing a lowermost heightmap. The ground area is determined on the basis of the number of voxels in each voxel group. We execute ground segmentation in real time by proposing an approach to minimize the comparison between neighboring voxels. Furthermore, we experimentally verify that ground segmentation can be executed at about 19.31 ms per frame.

Sloped Terrain Segmentation for Autonomous Drive Using Sparse 3D Point Cloud

PubMed Central

Cho, Seoungjae; Kim, Jonghyun; Ikram, Warda; Cho, Kyungeun; Sim, Sungdae

2014-01-01

A ubiquitous environment for road travel that uses wireless networks requires the minimization of data exchange between vehicles. An algorithm that can segment the ground in real time is necessary to obtain location data between vehicles simultaneously executing autonomous drive. This paper proposes a framework for segmenting the ground in real time using a sparse three-dimensional (3D) point cloud acquired from undulating terrain. A sparse 3D point cloud can be acquired by scanning the geography using light detection and ranging (LiDAR) sensors. For efficient ground segmentation, 3D point clouds are quantized in units of volume pixels (voxels) and overlapping data is eliminated. We reduce nonoverlapping voxels to two dimensions by implementing a lowermost heightmap. The ground area is determined on the basis of the number of voxels in each voxel group. We execute ground segmentation in real time by proposing an approach to minimize the comparison between neighboring voxels. Furthermore, we experimentally verify that ground segmentation can be executed at about 19.31 ms per frame. PMID:25093204

Automated 3D-Printed Unibody Immunoarray for Chemiluminescence Detection of Cancer Biomarker Proteins

PubMed Central

Tang, C. K.; Vaze, A.; Rusling, J. F.

2017-01-01

A low cost three-dimensional (3D) printed clear plastic microfluidic device was fabricated for fast, low cost automated protein detection. The unibody device features three reagent reservoirs, an efficient 3D network for passive mixing, and an optically transparent detection chamber housing a glass capture antibody array for measuring chemiluminescence output with a CCD camera. Sandwich type assays were built onto the glass arrays using a multi-labeled detection antibody-polyHRP (HRP = horseradish peroxidase). Total assay time was ~30 min in a complete automated assay employing a programmable syringe pump so that the protocol required minimal operator intervention. The device was used for multiplexed detection of prostate cancer biomarker proteins prostate specific antigen (PSA) and platelet factor 4 (PF-4). Detection limits of 0.5 pg mL−1 were achieved for these proteins in diluted serum with log dynamic ranges of four orders of magnitude. Good accuracy vs ELISA was validated by analyzing human serum samples. This prototype device holds good promise for further development as a point-of-care cancer diagnostics tool. PMID:28067370

Automated linking of suspicious findings between automated 3D breast ultrasound volumes

NASA Astrophysics Data System (ADS)

Gubern-Mérida, Albert; Tan, Tao; van Zelst, Jan; Mann, Ritse M.; Karssemeijer, Nico

2016-03-01

Automated breast ultrasound (ABUS) is a 3D imaging technique which is rapidly emerging as a safe and relatively inexpensive modality for screening of women with dense breasts. However, reading ABUS examinations is very time consuming task since radiologists need to manually identify suspicious findings in all the different ABUS volumes available for each patient. Image analysis techniques to automatically link findings across volumes are required to speed up clinical workflow and make ABUS screening more efficient. In this study, we propose an automated system to, given the location in the ABUS volume being inspected (source), find the corresponding location in a target volume. The target volume can be a different view of the same study or the same view from a prior examination. The algorithm was evaluated using 118 linkages between suspicious abnormalities annotated in a dataset of ABUS images of 27 patients participating in a high risk screening program. The distance between the predicted location and the center of the annotated lesion in the target volume was computed for evaluation. The mean ± stdev and median distance error achieved by the presented algorithm for linkages between volumes of the same study was 7.75±6.71 mm and 5.16 mm, respectively. The performance was 9.54±7.87 and 8.00 mm (mean ± stdev and median) for linkages between volumes from current and prior examinations. The proposed approach has the potential to minimize user interaction for finding correspondences among ABUS volumes.

Quantifying Standing Dead Tree Volume and Structural Loss with Voxelized Terrestrial Lidar Data

NASA Astrophysics Data System (ADS)

Popescu, S. C.; Putman, E.

2017-12-01

Standing dead trees (SDTs) are an important forest component and impact a variety of ecosystem processes, yet the carbon pool dynamics of SDTs are poorly constrained in terrestrial carbon cycling models. The ability to model wood decay and carbon cycling in relation to detectable changes in tree structure and volume over time would greatly improve such models. The overall objective of this study was to provide automated aboveground volume estimates of SDTs and automated procedures to detect, quantify, and characterize structural losses over time with terrestrial lidar data. The specific objectives of this study were: 1) develop an automated SDT volume estimation algorithm providing accurate volume estimates for trees scanned in dense forests; 2) develop an automated change detection methodology to accurately detect and quantify SDT structural loss between subsequent terrestrial lidar observations; and 3) characterize the structural loss rates of pine and oak SDTs in southeastern Texas. A voxel-based volume estimation algorithm, "TreeVolX", was developed and incorporates several methods designed to robustly process point clouds of varying quality levels. The algorithm operates on horizontal voxel slices by segmenting the slice into distinct branch or stem sections then applying an adaptive contour interpolation and interior filling process to create solid reconstructed tree models (RTMs). TreeVolX estimated large and small branch volume with an RMSE of 7.3% and 13.8%, respectively. A voxel-based change detection methodology was developed to accurately detect and quantify structural losses and incorporated several methods to mitigate the challenges presented by shifting tree and branch positions as SDT decay progresses. The volume and structural loss of 29 SDTs, composed of Pinus taeda and Quercus stellata, were successfully estimated using multitemporal terrestrial lidar observations over elapsed times ranging from 71 - 753 days. Pine and oak structural loss rates

A PENELOPE-based system for the automated Monte Carlo simulation of clinacs and voxelized geometries - application to far-from-axis fields

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sempau, Josep; Badal, Andreu; Brualla, Lorenzo

Purpose: Two new codes, PENEASY and PENEASYLINAC, which automate the Monte Carlo simulation of Varian Clinacs of the 600, 1800, 2100, and 2300 series, together with their electron applicators and multileaf collimators, are introduced. The challenging case of a relatively small and far-from-axis field has been studied with these tools. Methods: PENEASY is a modular, general-purpose main program for the PENELOPE Monte Carlo system that includes various source models, tallies and variance-reduction techniques (VRT). The code includes a new geometry model that allows the superposition of voxels and objects limited by quadric surfaces. A variant of the VRT known asmore » particle splitting, called fan splitting, is also introduced. PENEASYLINAC, in turn, automatically generates detailed geometry and configuration files to simulate linacs with PENEASY. These tools are applied to the generation of phase-space files, and of the corresponding absorbed dose distributions in water, for two 6 MV photon beams from a Varian Clinac 2100 C/D: a 40 x 40 cm{sup 2} centered field; and a 3 x 5 cm{sup 2} field centered at (4.5, -11.5) cm from the beam central axis. This latter configuration implies the largest possible over-traveling values of two of the jaws. Simulation results for the depth dose and lateral profiles at various depths are compared, by using the gamma index, with experimental values obtained with a PTW 31002 ionization chamber. The contribution of several VRTs to the computing speed of the more demanding off-axis case is analyzed. Results: For the 40 x 40 cm{sup 2} field, the percentages {gamma}{sub 1} and {gamma}{sub 1.2} of voxels with gamma indices (using 0.2 cm and 2% criteria) larger than unity and larger than 1.2 are 0.2% and 0%, respectively. For the 3 x 5 cm{sup 2} field, {gamma}{sub 1} = 0%. These figures indicate an excellent agreement between simulation and experiment. The dose distribution for the off-axis case with voxels of 2.5 x 2.5 x 2.5 mm{sup 3} and

Automated detection and segmentation of follicles in 3D ultrasound for assisted reproduction

NASA Astrophysics Data System (ADS)

Narayan, Nikhil S.; Sivanandan, Srinivasan; Kudavelly, Srinivas; Patwardhan, Kedar A.; Ramaraju, G. A.

2018-02-01

Follicle quantification refers to the computation of the number and size of follicles in 3D ultrasound volumes of the ovary. This is one of the key factors in determining hormonal dosage during female infertility treatments. In this paper, we propose an automated algorithm to detect and segment follicles in 3D ultrasound volumes of the ovary for quantification. In a first of its kind attempt, we employ noise-robust phase symmetry feature maps as likelihood function to perform mean-shift based follicle center detection. Max-flow algorithm is used for segmentation and gray weighted distance transform is employed for post-processing the results. We have obtained state-of-the-art results with a true positive detection rate of >90% on 26 3D volumes with 323 follicles.

Fully automated atlas-based method for prescribing 3D PRESS MR spectroscopic imaging: Toward robust and reproducible metabolite measurements in human brain.

PubMed

Bian, Wei; Li, Yan; Crane, Jason C; Nelson, Sarah J

2018-02-01

To implement a fully automated atlas-based method for prescribing 3D PRESS MR spectroscopic imaging (MRSI). The PRESS selected volume and outer-volume suppression bands were predefined on the MNI152 standard template image. The template image was aligned to the subject T 1 -weighted image during a scan, and the resulting transformation was then applied to the predefined prescription. To evaluate the method, H-1 MRSI data were obtained in repeat scan sessions from 20 healthy volunteers. In each session, datasets were acquired twice without repositioning. The overlap ratio of the prescribed volume in the two sessions was calculated and the reproducibility of inter- and intrasession metabolite peak height and area ratios was measured by the coefficient of variation (CoV). The CoVs from intra- and intersession were compared by a paired t-test. The average overlap ratio of the automatically prescribed selection volumes between two sessions was 97.8%. The average voxel-based intersession CoVs were less than 0.124 and 0.163 for peak height and area ratios, respectively. Paired t-test showed no significant difference between the intra- and intersession CoVs. The proposed method provides a time efficient method to prescribe 3D PRESS MRSI with reproducible imaging positioning and metabolite measurements. Magn Reson Med 79:636-642, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Adaptive kernel regression for freehand 3D ultrasound reconstruction

NASA Astrophysics Data System (ADS)

Alshalalfah, Abdel-Latif; Daoud, Mohammad I.; Al-Najar, Mahasen

2017-03-01

Freehand three-dimensional (3D) ultrasound imaging enables low-cost and flexible 3D scanning of arbitrary-shaped organs, where the operator can freely move a two-dimensional (2D) ultrasound probe to acquire a sequence of tracked cross-sectional images of the anatomy. Often, the acquired 2D ultrasound images are irregularly and sparsely distributed in the 3D space. Several 3D reconstruction algorithms have been proposed to synthesize 3D ultrasound volumes based on the acquired 2D images. A challenging task during the reconstruction process is to preserve the texture patterns in the synthesized volume and ensure that all gaps in the volume are correctly filled. This paper presents an adaptive kernel regression algorithm that can effectively reconstruct high-quality freehand 3D ultrasound volumes. The algorithm employs a kernel regression model that enables nonparametric interpolation of the voxel gray-level values. The kernel size of the regression model is adaptively adjusted based on the characteristics of the voxel that is being interpolated. In particular, when the algorithm is employed to interpolate a voxel located in a region with dense ultrasound data samples, the size of the kernel is reduced to preserve the texture patterns. On the other hand, the size of the kernel is increased in areas that include large gaps to enable effective gap filling. The performance of the proposed algorithm was compared with seven previous interpolation approaches by synthesizing freehand 3D ultrasound volumes of a benign breast tumor. The experimental results show that the proposed algorithm outperforms the other interpolation approaches.

Current automated 3D cell detection methods are not a suitable replacement for manual stereologic cell counting

PubMed Central

Schmitz, Christoph; Eastwood, Brian S.; Tappan, Susan J.; Glaser, Jack R.; Peterson, Daniel A.; Hof, Patrick R.

2014-01-01

Stereologic cell counting has had a major impact on the field of neuroscience. A major bottleneck in stereologic cell counting is that the user must manually decide whether or not each cell is counted according to three-dimensional (3D) stereologic counting rules by visual inspection within hundreds of microscopic fields-of-view per investigated brain or brain region. Reliance on visual inspection forces stereologic cell counting to be very labor-intensive and time-consuming, and is the main reason why biased, non-stereologic two-dimensional (2D) “cell counting” approaches have remained in widespread use. We present an evaluation of the performance of modern automated cell detection and segmentation algorithms as a potential alternative to the manual approach in stereologic cell counting. The image data used in this study were 3D microscopic images of thick brain tissue sections prepared with a variety of commonly used nuclear and cytoplasmic stains. The evaluation compared the numbers and locations of cells identified unambiguously and counted exhaustively by an expert observer with those found by three automated 3D cell detection algorithms: nuclei segmentation from the FARSIGHT toolkit, nuclei segmentation by 3D multiple level set methods, and the 3D object counter plug-in for ImageJ. Of these methods, FARSIGHT performed best, with true-positive detection rates between 38 and 99% and false-positive rates from 3.6 to 82%. The results demonstrate that the current automated methods suffer from lower detection rates and higher false-positive rates than are acceptable for obtaining valid estimates of cell numbers. Thus, at present, stereologic cell counting with manual decision for object inclusion according to unbiased stereologic counting rules remains the only adequate method for unbiased cell quantification in histologic tissue sections. PMID:24847213

PONDEROSA, an automated 3D-NOESY peak picking program, enables automated protein structure determination.

PubMed

Lee, Woonghee; Kim, Jin Hae; Westler, William M; Markley, John L

2011-06-15

PONDEROSA (Peak-picking Of Noe Data Enabled by Restriction of Shift Assignments) accepts input information consisting of a protein sequence, backbone and sidechain NMR resonance assignments, and 3D-NOESY ((13)C-edited and/or (15)N-edited) spectra, and returns assignments of NOESY crosspeaks, distance and angle constraints, and a reliable NMR structure represented by a family of conformers. PONDEROSA incorporates and integrates external software packages (TALOS+, STRIDE and CYANA) to carry out different steps in the structure determination. PONDEROSA implements internal functions that identify and validate NOESY peak assignments and assess the quality of the calculated three-dimensional structure of the protein. The robustness of the analysis results from PONDEROSA's hierarchical processing steps that involve iterative interaction among the internal and external modules. PONDEROSA supports a variety of input formats: SPARKY assignment table (.shifts) and spectrum file formats (.ucsf), XEASY proton file format (.prot), and NMR-STAR format (.star). To demonstrate the utility of PONDEROSA, we used the package to determine 3D structures of two proteins: human ubiquitin and Escherichia coli iron-sulfur scaffold protein variant IscU(D39A). The automatically generated structural constraints and ensembles of conformers were as good as or better than those determined previously by much less automated means. The program, in the form of binary code along with tutorials and reference manuals, is available at http://ponderosa.nmrfam.wisc.edu/.

Evaluation of negative results of BacT/Alert 3D automated blood culture system.

PubMed

Kocoglu, M Esra; Bayram, Aysen; Balci, Iclal

2005-06-01

Although automated continuous-monitoring blood culture systems are both rapid and sensitive, false-positive and false-negative results still occur. The objective of this study, then, was to evaluate negative results occurring with BacT/Alert 3D blood culture systems. A total of 1032 samples were cultured with the BacT/Alert 3D automated blood culture system, using both aerobic (FA) and anaerobic (FN) [corrected] media, and 128 of these samples yielded positive results. A total of 904 negative blood samples were then subcultured in 5% sheep blood agar, eosin methylene blue, chocolate agar, and sabouraud-dextrose agar. Organisms growing on these subcultures were subsequently identified using both Vitek32 (bioMerieux, Durham, NC) and conventional methods. Twenty four (2.6%) of the 904 subcultures grew on the subculture media. The majority (83.3%) of these were determined to be gram-positive microorganisms. Fourteen (58.3%) were coagulase-negative staphylococci, two (8.3%) were Bacillus spp., one (4.2%) was Staphylococcus aureus, and one (4.2%) was identified as Enterococcus faecium. Streptococcus pneumoniae and Neisseria spp. were isolated together in two (8.3%) vials. Gram-negative microorganisms comprised 12.5% of the subcultures, of which two (8.3%) were found to be Pseudomonas aeruginosa, and one (4.2%) was Pseudomonas fluorescens. The other isolate (4.2%) was identified as Candida albicans. We conclude that the subculture of negative results is valuable in the BacT/Alert 3D system, especially in situations in which only one set of blood cultures is taken.

A Voxel-by-Voxel Comparison of Deformable Vector Fields Obtained by Three Deformable Image Registration Algorithms Applied to 4DCT Lung Studies.

PubMed

Fatyga, Mirek; Dogan, Nesrin; Weiss, Elizabeth; Sleeman, William C; Zhang, Baoshe; Lehman, William J; Williamson, Jeffrey F; Wijesooriya, Krishni; Christensen, Gary E

2015-01-01

Commonly used methods of assessing the accuracy of deformable image registration (DIR) rely on image segmentation or landmark selection. These methods are very labor intensive and thus limited to relatively small number of image pairs. The direct voxel-by-voxel comparison can be automated to examine fluctuations in DIR quality on a long series of image pairs. A voxel-by-voxel comparison of three DIR algorithms applied to lung patients is presented. Registrations are compared by comparing volume histograms formed both with individual DIR maps and with a voxel-by-voxel subtraction of the two maps. When two DIR maps agree one concludes that both maps are interchangeable in treatment planning applications, though one cannot conclude that either one agrees with the ground truth. If two DIR maps significantly disagree one concludes that at least one of the maps deviates from the ground truth. We use the method to compare 3 DIR algorithms applied to peak inhale-peak exhale registrations of 4DFBCT data obtained from 13 patients. All three algorithms appear to be nearly equivalent when compared using DICE similarity coefficients. A comparison based on Jacobian volume histograms shows that all three algorithms measure changes in total volume of the lungs with reasonable accuracy, but show large differences in the variance of Jacobian distribution on contoured structures. Analysis of voxel-by-voxel subtraction of DIR maps shows differences between algorithms that exceed a centimeter for some registrations. Deformation maps produced by DIR algorithms must be treated as mathematical approximations of physical tissue deformation that are not self-consistent and may thus be useful only in applications for which they have been specifically validated. The three algorithms tested in this work perform fairly robustly for the task of contour propagation, but produce potentially unreliable results for the task of DVH accumulation or measurement of local volume change. Performance of

Quantification of Dynamic Morphological Drug Responses in 3D Organotypic Cell Cultures by Automated Image Analysis

PubMed Central

Härmä, Ville; Schukov, Hannu-Pekka; Happonen, Antti; Ahonen, Ilmari; Virtanen, Johannes; Siitari, Harri; Åkerfelt, Malin; Lötjönen, Jyrki; Nees, Matthias

2014-01-01

Glandular epithelial cells differentiate into complex multicellular or acinar structures, when embedded in three-dimensional (3D) extracellular matrix. The spectrum of different multicellular morphologies formed in 3D is a sensitive indicator for the differentiation potential of normal, non-transformed cells compared to different stages of malignant progression. In addition, single cells or cell aggregates may actively invade the matrix, utilizing epithelial, mesenchymal or mixed modes of motility. Dynamic phenotypic changes involved in 3D tumor cell invasion are sensitive to specific small-molecule inhibitors that target the actin cytoskeleton. We have used a panel of inhibitors to demonstrate the power of automated image analysis as a phenotypic or morphometric readout in cell-based assays. We introduce a streamlined stand-alone software solution that supports large-scale high-content screens, based on complex and organotypic cultures. AMIDA (Automated Morphometric Image Data Analysis) allows quantitative measurements of large numbers of images and structures, with a multitude of different spheroid shapes, sizes, and textures. AMIDA supports an automated workflow, and can be combined with quality control and statistical tools for data interpretation and visualization. We have used a representative panel of 12 prostate and breast cancer lines that display a broad spectrum of different spheroid morphologies and modes of invasion, challenged by a library of 19 direct or indirect modulators of the actin cytoskeleton which induce systematic changes in spheroid morphology and differentiation versus invasion. These results were independently validated by 2D proliferation, apoptosis and cell motility assays. We identified three drugs that primarily attenuated the invasion and formation of invasive processes in 3D, without affecting proliferation or apoptosis. Two of these compounds block Rac signalling, one affects cellular cAMP/cGMP accumulation. Our approach supports

Voxel inversion of airborne electromagnetic data for improved model integration

NASA Astrophysics Data System (ADS)

Fiandaca, Gianluca; Auken, Esben; Kirkegaard, Casper; Vest Christiansen, Anders

2014-05-01

Inversion of electromagnetic data has migrated from single site interpretations to inversions including entire surveys using spatial constraints to obtain geologically reasonable results. Though, the model space is usually linked to the actual observation points. For airborne electromagnetic (AEM) surveys the spatial discretization of the model space reflects the flight lines. On the contrary, geological and groundwater models most often refer to a regular voxel grid, not correlated to the geophysical model space, and the geophysical information has to be relocated for integration in (hydro)geological models. We have developed a new geophysical inversion algorithm working directly in a voxel grid disconnected from the actual measuring points, which then allows for informing directly geological/hydrogeological models. The new voxel model space defines the soil properties (like resistivity) on a set of nodes, and the distribution of the soil properties is computed everywhere by means of an interpolation function (e.g. inverse distance or kriging). Given this definition of the voxel model space, the 1D forward responses of the AEM data are computed as follows: 1) a 1D model subdivision, in terms of model thicknesses, is defined for each 1D data set, creating "virtual" layers. 2) the "virtual" 1D models at the sounding positions are finalized by interpolating the soil properties (the resistivity) in the center of the "virtual" layers. 3) the forward response is computed in 1D for each "virtual" model. We tested the new inversion scheme on an AEM survey carried out with the SkyTEM system close to Odder, in Denmark. The survey comprises 106054 dual mode AEM soundings, and covers an area of approximately 13 km X 16 km. The voxel inversion was carried out on a structured grid of 260 X 325 X 29 xyz nodes (50 m xy spacing), for a total of 2450500 inversion parameters. A classical spatially constrained inversion (SCI) was carried out on the same data set, using 106054

Automatic nipple detection on 3D images of an automated breast ultrasound system (ABUS)

NASA Astrophysics Data System (ADS)

Javanshir Moghaddam, Mandana; Tan, Tao; Karssemeijer, Nico; Platel, Bram

2014-03-01

Recent studies have demonstrated that applying Automated Breast Ultrasound in addition to mammography in women with dense breasts can lead to additional detection of small, early stage breast cancers which are occult in corresponding mammograms. In this paper, we proposed a fully automatic method for detecting the nipple location in 3D ultrasound breast images acquired from Automated Breast Ultrasound Systems. The nipple location is a valuable landmark to report the position of possible abnormalities in a breast or to guide image registration. To detect the nipple location, all images were normalized. Subsequently, features have been extracted in a multi scale approach and classification experiments were performed using a gentle boost classifier to identify the nipple location. The method was applied on a dataset of 100 patients with 294 different 3D ultrasound views from Siemens and U-systems acquisition systems. Our database is a representative sample of cases obtained in clinical practice by four medical centers. The automatic method could accurately locate the nipple in 90% of AP (Anterior-Posterior) views and in 79% of the other views.

Automation and Preclinical Evaluation of a Dedicated Emission Mammotomography System for Fully 3-D Molecular Breast Imaging

DTIC Science & Technology

2009-10-01

molecular breast imaging, with the ability to dynamically contour any sized breast, will improve detection and potentially in vivo characterization of...Having flexible 3D positioning about the breast yielded minimal RMSD differences, which is important for high resolution molecular emission imaging. This...TITLE: Automation and Preclinical Evaluation of a Dedicated Emission Mammotomography System for Fully 3-D Molecular Breast Imaging PRINCIPAL

3D Deep Learning Angiography (3D-DLA) from C-arm Conebeam CT.

PubMed

Montoya, J C; Li, Y; Strother, C; Chen, G-H

2018-05-01

Deep learning is a branch of artificial intelligence that has demonstrated unprecedented performance in many medical imaging applications. Our purpose was to develop a deep learning angiography method to generate 3D cerebral angiograms from a single contrast-enhanced C-arm conebeam CT acquisition in order to reduce image artifacts and radiation dose. A set of 105 3D rotational angiography examinations were randomly selected from an internal data base. All were acquired using a clinical system in conjunction with a standard injection protocol. More than 150 million labeled voxels from 35 subjects were used for training. A deep convolutional neural network was trained to classify each image voxel into 3 tissue types (vasculature, bone, and soft tissue). The trained deep learning angiography model was then applied for tissue classification into a validation cohort of 8 subjects and a final testing cohort of the remaining 62 subjects. The final vasculature tissue class was used to generate the 3D deep learning angiography images. To quantify the generalization error of the trained model, we calculated the accuracy, sensitivity, precision, and Dice similarity coefficients for vasculature classification in relevant anatomy. The 3D deep learning angiography and clinical 3D rotational angiography images were subjected to a qualitative assessment for the presence of intersweep motion artifacts. Vasculature classification accuracy and 95% CI in the testing dataset were 98.7% (98.3%-99.1%). No residual signal from osseous structures was observed for any 3D deep learning angiography testing cases except for small regions in the otic capsule and nasal cavity compared with 37% (23/62) of the 3D rotational angiographies. Deep learning angiography accurately recreated the vascular anatomy of the 3D rotational angiography reconstructions without a mask. Deep learning angiography reduced misregistration artifacts induced by intersweep motion, and it reduced radiation exposure

Reconstruction of 3d Models from Point Clouds with Hybrid Representation

NASA Astrophysics Data System (ADS)

Hu, P.; Dong, Z.; Yuan, P.; Liang, F.; Yang, B.

2018-05-01

The three-dimensional (3D) reconstruction of urban buildings from point clouds has long been an active topic in applications related to human activities. However, due to the structures significantly differ in terms of complexity, the task of 3D reconstruction remains a challenging issue especially for the freeform surfaces. In this paper, we present a new reconstruction algorithm which allows the 3D-models of building as a combination of regular structures and irregular surfaces, where the regular structures are parameterized plane primitives and the irregular surfaces are expressed as meshes. The extraction of irregular surfaces starts with an over-segmented method for the unstructured point data, a region growing approach based the adjacent graph of super-voxels is then applied to collapse these super-voxels, and the freeform surfaces can be clustered from the voxels filtered by a thickness threshold. To achieve these regular planar primitives, the remaining voxels with a larger flatness will be further divided into multiscale super-voxels as basic units, and the final segmented planes are enriched and refined in a mutually reinforcing manner under the framework of a global energy optimization. We have implemented the proposed algorithms and mainly tested on two point clouds that differ in point density and urban characteristic, and experimental results on complex building structures illustrated the efficacy of the proposed framework.

Automated Recognition of 3D Features in GPIR Images

NASA Technical Reports Server (NTRS)

Park, Han; Stough, Timothy; Fijany, Amir

2007-01-01

A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a

Segmentation of 3D ultrasound computer tomography reflection images using edge detection and surface fitting

NASA Astrophysics Data System (ADS)

Hopp, T.; Zapf, M.; Ruiter, N. V.

2014-03-01

An essential processing step for comparison of Ultrasound Computer Tomography images to other modalities, as well as for the use in further image processing, is to segment the breast from the background. In this work we present a (semi-) automated 3D segmentation method which is based on the detection of the breast boundary in coronal slice images and a subsequent surface fitting. The method was evaluated using a software phantom and in-vivo data. The fully automatically processed phantom results showed that a segmentation of approx. 10% of the slices of a dataset is sufficient to recover the overall breast shape. Application to 16 in-vivo datasets was performed successfully using semi-automated processing, i.e. using a graphical user interface for manual corrections of the automated breast boundary detection. The processing time for the segmentation of an in-vivo dataset could be significantly reduced by a factor of four compared to a fully manual segmentation. Comparison to manually segmented images identified a smoother surface for the semi-automated segmentation with an average of 11% of differing voxels and an average surface deviation of 2mm. Limitations of the edge detection may be overcome by future updates of the KIT USCT system, allowing a fully-automated usage of our segmentation approach.

a Semi-Automated Point Cloud Processing Methodology for 3d Cultural Heritage Documentation

NASA Astrophysics Data System (ADS)

Kıvılcım, C. Ö.; Duran, Z.

2016-06-01

The preliminary phase in any architectural heritage project is to obtain metric measurements and documentation of the building and its individual elements. On the other hand, conventional measurement techniques require tremendous resources and lengthy project completion times for architectural surveys and 3D model production. Over the past two decades, the widespread use of laser scanning and digital photogrammetry have significantly altered the heritage documentation process. Furthermore, advances in these technologies have enabled robust data collection and reduced user workload for generating various levels of products, from single buildings to expansive cityscapes. More recently, the use of procedural modelling methods and BIM relevant applications for historic building documentation purposes has become an active area of research, however fully automated systems in cultural heritage documentation still remains open. In this paper, we present a semi-automated methodology, for 3D façade modelling of cultural heritage assets based on parametric and procedural modelling techniques and using airborne and terrestrial laser scanning data. We present the contribution of our methodology, which we implemented in an open source software environment using the example project of a 16th century early classical era Ottoman structure, Sinan the Architect's Şehzade Mosque in Istanbul, Turkey.

Low-Cost 3D Printers Enable High-Quality and Automated Sample Preparation and Molecular Detection

PubMed Central

Chan, Kamfai; Coen, Mauricio; Hardick, Justin; Gaydos, Charlotte A.; Wong, Kah-Yat; Smith, Clayton; Wilson, Scott A.; Vayugundla, Siva Praneeth; Wong, Season

2016-01-01

Most molecular diagnostic assays require upfront sample preparation steps to isolate the target’s nucleic acids, followed by its amplification and detection using various nucleic acid amplification techniques. Because molecular diagnostic methods are generally rather difficult to perform manually without highly trained users, automated and integrated systems are highly desirable but too costly for use at point-of-care or low-resource settings. Here, we showcase the development of a low-cost and rapid nucleic acid isolation and amplification platform by modifying entry-level 3D printers that cost between $400 and $750. Our modifications consisted of replacing the extruder with a tip-comb attachment that houses magnets to conduct magnetic particle-based nucleic acid extraction. We then programmed the 3D printer to conduct motions that can perform high-quality extraction protocols. Up to 12 samples can be processed simultaneously in under 13 minutes and the efficiency of nucleic acid isolation matches well against gold-standard spin-column-based extraction technology. Additionally, we used the 3D printer’s heated bed to supply heat to perform water bath-based polymerase chain reactions (PCRs). Using another attachment to hold PCR tubes, the 3D printer was programmed to automate the process of shuttling PCR tubes between water baths. By eliminating the temperature ramping needed in most commercial thermal cyclers, the run time of a 35-cycle PCR protocol was shortened by 33%. This article demonstrates that for applications in resource-limited settings, expensive nucleic acid extraction devices and thermal cyclers that are used in many central laboratories can be potentially replaced by a device modified from inexpensive entry-level 3D printers. PMID:27362424

Comparative 3D micro-CT and 2D histomorphometry analysis of dental implant osseointegration in the maxilla of minipigs.

PubMed

Bissinger, Oliver; Probst, Florian Andreas; Wolff, Klaus-Dietrich; Jeschke, Anke; Weitz, Jochen; Deppe, Herbert; Kolk, Andreas

2017-04-01

The bone implant contact (BIC) has traditionally been evaluated with histological methods. Thereupon, strong correlations of two-dimensional (2D) BIC have been detected between μCT and destructive histology. However, due to the high intra-sample variability in BIC values, one histological slice is not sufficient to represent 3D BIC. Therefore, our aim has been to correlate the averaged values of 3-4 histological sections to 3D μCT. Fifty-four implants inserted into the maxilla of 14 minipigs were evaluated. Two different time points were selected to assess the 3D BIC (distance to implant: 2-5 voxels), an inner ring (6-30 voxels) and an outer ring (55-100 voxels) using μCT (voxel size: 10 μm) and to correlate the values to histomorphometry. Strong correlations (p < 0.0001; 28 days, 56 days, total) were seen between μCT and histomorphometry concerning BIC (r = 0.84, r = 0.85, r = 0.83), the inner ring (r = 0.87, r = 0.87, r = 0.88) and the outer ring (r = 0.85, r = 0.85, r = 0.88). Closer to the implant, μCT values were higher compared with histomorphometry. Although 3-4 histological slices per implant seem to predict the 3D BIC, μCT might be advantageous because of its non-destructive 3D character. The healing time may not impact on the comparability. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Towards a voxel-based geographic automata for the simulation of geospatial processes

NASA Astrophysics Data System (ADS)

Jjumba, Anthony; Dragićević, Suzana

2016-07-01

Many geographic processes evolve in a three dimensional space and time continuum. However, when they are represented with the aid of geographic information systems (GIS) or geosimulation models they are modelled in a framework of two-dimensional space with an added temporal component. The objective of this study is to propose the design and implementation of voxel-based automata as a methodological approach for representing spatial processes evolving in the four-dimensional (4D) space-time domain. Similar to geographic automata models which are developed to capture and forecast geospatial processes that change in a two-dimensional spatial framework using cells (raster geospatial data), voxel automata rely on the automata theory and use three-dimensional volumetric units (voxels). Transition rules have been developed to represent various spatial processes which range from the movement of an object in 3D to the diffusion of airborne particles and landslide simulation. In addition, the proposed 4D models demonstrate that complex processes can be readily reproduced from simple transition functions without complex methodological approaches. The voxel-based automata approach provides a unique basis to model geospatial processes in 4D for the purpose of improving representation, analysis and understanding their spatiotemporal dynamics. This study contributes to the advancement of the concepts and framework of 4D GIS.

Automated segmentation of 3D anatomical structures on CT images by using a deep convolutional network based on end-to-end learning approach

NASA Astrophysics Data System (ADS)

Zhou, Xiangrong; Takayama, Ryosuke; Wang, Song; Zhou, Xinxin; Hara, Takeshi; Fujita, Hiroshi

2017-02-01

We have proposed an end-to-end learning approach that trained a deep convolutional neural network (CNN) for automatic CT image segmentation, which accomplished a voxel-wised multiple classification to directly map each voxel on 3D CT images to an anatomical label automatically. The novelties of our proposed method were (1) transforming the anatomical structures segmentation on 3D CT images into a majority voting of the results of 2D semantic image segmentation on a number of 2D-slices from different image orientations, and (2) using "convolution" and "deconvolution" networks to achieve the conventional "coarse recognition" and "fine extraction" functions which were integrated into a compact all-in-one deep CNN for CT image segmentation. The advantage comparing to previous works was its capability to accomplish real-time image segmentations on 2D slices of arbitrary CT-scan-range (e.g. body, chest, abdomen) and produced correspondingly-sized output. In this paper, we propose an improvement of our proposed approach by adding an organ localization module to limit CT image range for training and testing deep CNNs. A database consisting of 240 3D CT scans and a human annotated ground truth was used for training (228 cases) and testing (the remaining 12 cases). We applied the improved method to segment pancreas and left kidney regions, respectively. The preliminary results showed that the accuracies of the segmentation results were improved significantly (pancreas was 34% and kidney was 8% increased in Jaccard index from our previous results). The effectiveness and usefulness of proposed improvement for CT image segmentations were confirmed.

PONDEROSA, an automated 3D-NOESY peak picking program, enables automated protein structure determination

PubMed Central

Lee, Woonghee; Kim, Jin Hae; Westler, William M.; Markley, John L.

2011-01-01

Summary: PONDEROSA (Peak-picking Of Noe Data Enabled by Restriction of Shift Assignments) accepts input information consisting of a protein sequence, backbone and sidechain NMR resonance assignments, and 3D-NOESY (13C-edited and/or 15N-edited) spectra, and returns assignments of NOESY crosspeaks, distance and angle constraints, and a reliable NMR structure represented by a family of conformers. PONDEROSA incorporates and integrates external software packages (TALOS+, STRIDE and CYANA) to carry out different steps in the structure determination. PONDEROSA implements internal functions that identify and validate NOESY peak assignments and assess the quality of the calculated three-dimensional structure of the protein. The robustness of the analysis results from PONDEROSA's hierarchical processing steps that involve iterative interaction among the internal and external modules. PONDEROSA supports a variety of input formats: SPARKY assignment table (.shifts) and spectrum file formats (.ucsf), XEASY proton file format (.prot), and NMR-STAR format (.star). To demonstrate the utility of PONDEROSA, we used the package to determine 3D structures of two proteins: human ubiquitin and Escherichia coli iron-sulfur scaffold protein variant IscU(D39A). The automatically generated structural constraints and ensembles of conformers were as good as or better than those determined previously by much less automated means. Availability: The program, in the form of binary code along with tutorials and reference manuals, is available at http://ponderosa.nmrfam.wisc.edu/. Contact: whlee@nmrfam.wisc.edu; markley@nmrfam.wisc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21511715

Silhouette-based approach of 3D image reconstruction for automated image acquisition using robotic arm

NASA Astrophysics Data System (ADS)

Azhar, N.; Saad, W. H. M.; Manap, N. A.; Saad, N. M.; Syafeeza, A. R.

2017-06-01

This study presents the approach of 3D image reconstruction using an autonomous robotic arm for the image acquisition process. A low cost of the automated imaging platform is created using a pair of G15 servo motor connected in series to an Arduino UNO as a main microcontroller. Two sets of sequential images were obtained using different projection angle of the camera. The silhouette-based approach is used in this study for 3D reconstruction from the sequential images captured from several different angles of the object. Other than that, an analysis based on the effect of different number of sequential images on the accuracy of 3D model reconstruction was also carried out with a fixed projection angle of the camera. The effecting elements in the 3D reconstruction are discussed and the overall result of the analysis is concluded according to the prototype of imaging platform.

An accurate segmentation method for volumetry of brain tumor in 3D MRI

NASA Astrophysics Data System (ADS)

Wang, Jiahui; Li, Qiang; Hirai, Toshinori; Katsuragawa, Shigehiko; Li, Feng; Doi, Kunio

2008-03-01

Accurate volumetry of brain tumors in magnetic resonance imaging (MRI) is important for evaluating the interval changes in tumor volumes during and after treatment, and also for planning of radiation therapy. In this study, an automated volumetry method for brain tumors in MRI was developed by use of a new three-dimensional (3-D) image segmentation technique. First, the central location of a tumor was identified by a radiologist, and then a volume of interest (VOI) was determined automatically. To substantially simplify tumor segmentation, we transformed the 3-D image of the tumor into a two-dimensional (2-D) image by use of a "spiral-scanning" technique, in which a radial line originating from the center of the tumor scanned the 3-D image spirally from the "north pole" to the "south pole". The voxels scanned by the radial line provided a transformed 2-D image. We employed dynamic programming to delineate an "optimal" outline of the tumor in the transformed 2-D image. We then transformed the optimal outline back into 3-D image space to determine the volume of the tumor. The volumetry method was trained and evaluated by use of 16 cases with 35 brain tumors. The agreement between tumor volumes provided by computer and a radiologist was employed as a performance metric. Our method provided relatively accurate results with a mean agreement value of 88%.

Generation of Ground Truth Datasets for the Analysis of 3d Point Clouds in Urban Scenes Acquired via Different Sensors

NASA Astrophysics Data System (ADS)

Xu, Y.; Sun, Z.; Boerner, R.; Koch, T.; Hoegner, L.; Stilla, U.

2018-04-01

In this work, we report a novel way of generating ground truth dataset for analyzing point cloud from different sensors and the validation of algorithms. Instead of directly labeling large amount of 3D points requiring time consuming manual work, a multi-resolution 3D voxel grid for the testing site is generated. Then, with the help of a set of basic labeled points from the reference dataset, we can generate a 3D labeled space of the entire testing site with different resolutions. Specifically, an octree-based voxel structure is applied to voxelize the annotated reference point cloud, by which all the points are organized by 3D grids of multi-resolutions. When automatically annotating the new testing point clouds, a voting based approach is adopted to the labeled points within multiple resolution voxels, in order to assign a semantic label to the 3D space represented by the voxel. Lastly, robust line- and plane-based fast registration methods are developed for aligning point clouds obtained via various sensors. Benefiting from the labeled 3D spatial information, we can easily create new annotated 3D point clouds of different sensors of the same scene directly by considering the corresponding labels of 3D space the points located, which would be convenient for the validation and evaluation of algorithms related to point cloud interpretation and semantic segmentation.

Dose fractionation theorem in 3-D reconstruction (tomography)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Glaeser, R.M.

It is commonly assumed that the large number of projections for single-axis tomography precludes its application to most beam-labile specimens. However, Hegerl and Hoppe have pointed out that the total dose required to achieve statistical significance for each voxel of a computed 3-D reconstruction is the same as that required to obtain a single 2-D image of that isolated voxel, at the same level of statistical significance. Thus a statistically significant 3-D image can be computed from statistically insignificant projections, as along as the total dosage that is distributed among these projections is high enough that it would have resultedmore » in a statistically significant projection, if applied to only one image. We have tested this critical theorem by simulating the tomographic reconstruction of a realistic 3-D model created from an electron micrograph. The simulations verify the basic conclusions of high absorption, signal-dependent noise, varying specimen contrast and missing angular range. Furthermore, the simulations demonstrate that individual projections in the series of fractionated-dose images can be aligned by cross-correlation because they contain significant information derived from the summation of features from different depths in the structure. This latter information is generally not useful for structural interpretation prior to 3-D reconstruction, owing to the complexity of most specimens investigated by single-axis tomography. These results, in combination with dose estimates for imaging single voxels and measurements of radiation damage in the electron microscope, demonstrate that it is feasible to use single-axis tomography with soft X-ray microscopy of frozen-hydrated specimens.« less

High-Precision Phenotyping of Grape Bunch Architecture Using Fast 3D Sensor and Automation.

PubMed

Rist, Florian; Herzog, Katja; Mack, Jenny; Richter, Robert; Steinhage, Volker; Töpfer, Reinhard

2018-03-02

Wine growers prefer cultivars with looser bunch architecture because of the decreased risk for bunch rot. As a consequence, grapevine breeders have to select seedlings and new cultivars with regard to appropriate bunch traits. Bunch architecture is a mosaic of different single traits which makes phenotyping labor-intensive and time-consuming. In the present study, a fast and high-precision phenotyping pipeline was developed. The optical sensor Artec Spider 3D scanner (Artec 3D, L-1466, Luxembourg) was used to generate dense 3D point clouds of grapevine bunches under lab conditions and an automated analysis software called 3D-Bunch-Tool was developed to extract different single 3D bunch traits, i.e., the number of berries, berry diameter, single berry volume, total volume of berries, convex hull volume of grapes, bunch width and bunch length. The method was validated on whole bunches of different grapevine cultivars and phenotypic variable breeding material. Reliable phenotypic data were obtained which show high significant correlations (up to r² = 0.95 for berry number) compared to ground truth data. Moreover, it was shown that the Artec Spider can be used directly in the field where achieved data show comparable precision with regard to the lab application. This non-invasive and non-contact field application facilitates the first high-precision phenotyping pipeline based on 3D bunch traits in large plant sets.

MVO Automation Platform: Addressing Unmet Needs in Clinical Laboratories with Microcontrollers, 3D Printing, and Open-Source Hardware/Software.

PubMed

Iglehart, Brian

2018-05-01

Laboratory automation improves test reproducibility, which is vital to patient care in clinical laboratories. Many small and specialty laboratories are excluded from the benefits of automation due to low sample number, cost, space, and/or lack of automation expertise. The Minimum Viable Option (MVO) automation platform was developed to address these hurdles and fulfill an unmet need. Consumer 3D printing enabled rapid iterative prototyping to allow for a variety of instrumentation and assay setups and procedures. Three MVO versions have been produced. MVOv1.1 successfully performed part of a clinical assay, and results were comparable to those of commercial automation. Raspberry Pi 3 Model B (RPI3) single-board computers with Sense Hardware Attached on Top (HAT) and Raspberry Pi Camera Module V2 hardware were remotely accessed and evaluated for their suitability to qualify the latest MVOv1.2 platform. Sense HAT temperature, barometric pressure, and relative humidity sensors were stable in climate-controlled environments and are useful in identifying appropriate laboratory spaces for automation placement. The RPI3 with camera plus digital dial indicator logged axis travel experiments. RPI3 with camera and Sense HAT as a light source showed promise when used for photometric dispensing tests. Individual well standard curves were necessary for well-to-well light and path length compensations.

Smooth 2D manifold extraction from 3D image stack

PubMed Central

Shihavuddin, Asm; Basu, Sreetama; Rexhepaj, Elton; Delestro, Felipe; Menezes, Nikita; Sigoillot, Séverine M; Del Nery, Elaine; Selimi, Fekrije; Spassky, Nathalie; Genovesio, Auguste

2017-01-01

Three-dimensional fluorescence microscopy followed by image processing is routinely used to study biological objects at various scales such as cells and tissue. However, maximum intensity projection, the most broadly used rendering tool, extracts a discontinuous layer of voxels, obliviously creating important artifacts and possibly misleading interpretation. Here we propose smooth manifold extraction, an algorithm that produces a continuous focused 2D extraction from a 3D volume, hence preserving local spatial relationships. We demonstrate the usefulness of our approach by applying it to various biological applications using confocal and wide-field microscopy 3D image stacks. We provide a parameter-free ImageJ/Fiji plugin that allows 2D visualization and interpretation of 3D image stacks with maximum accuracy. PMID:28561033

A study on automated anatomical labeling to arteries concerning with colon from 3D abdominal CT images

NASA Astrophysics Data System (ADS)

Hoang, Bui Huy; Oda, Masahiro; Jiang, Zhengang; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Mori, Kensaku

2011-03-01

This paper presents an automated anatomical labeling method of arteries extracted from contrasted 3D CT images based on multi-class AdaBoost. In abdominal surgery, understanding of vasculature related to a target organ such as the colon is very important. Therefore, the anatomical structure of blood vessels needs to be understood by computers in a system supporting abdominal surgery. There are several researches on automated anatomical labeling, but there is no research on automated anatomical labeling to arteries concerning with the colon. The proposed method obtains a tree structure of arteries from the artery region and calculates features values of each branch. These feature values are thickness, curvature, direction, and running vectors of branch. Then, candidate arterial names are computed by classifiers that are trained to output artery names. Finally, a global optimization process is applied to the candidate arterial names to determine final names. Target arteries of this paper are nine lower abdominal arteries (AO, LCIA, RCIA, LEIA, REIA, SMA, IMA, LIIA, RIIA). We applied the proposed method to 14 cases of 3D abdominal contrasted CT images, and evaluated the results by leave-one-out scheme. The average precision and recall rates of the proposed method were 87.9% and 93.3%, respectively. The results of this method are applicable for anatomical name display of surgical simulation and computer aided surgery.

Completely automated estimation of prostate volume for 3-D side-fire transrectal ultrasound using shape prior approach

NASA Astrophysics Data System (ADS)

Li, Lu; Narayanan, Ramakrishnan; Miller, Steve; Shen, Feimo; Barqawi, Al B.; Crawford, E. David; Suri, Jasjit S.

2008-02-01

Real-time knowledge of capsule volume of an organ provides a valuable clinical tool for 3D biopsy applications. It is challenging to estimate this capsule volume in real-time due to the presence of speckles, shadow artifacts, partial volume effect and patient motion during image scans, which are all inherent in medical ultrasound imaging. The volumetric ultrasound prostate images are sliced in a rotational manner every three degrees. The automated segmentation method employs a shape model, which is obtained from training data, to delineate the middle slices of volumetric prostate images. Then a "DDC" algorithm is applied to the rest of the images with the initial contour obtained. The volume of prostate is estimated with the segmentation results. Our database consists of 36 prostate volumes which are acquired using a Philips ultrasound machine using a Side-fire transrectal ultrasound (TRUS) probe. We compare our automated method with the semi-automated approach. The mean volumes using the semi-automated and complete automated techniques were 35.16 cc and 34.86 cc, with the error of 7.3% and 7.6% compared to the volume obtained by the human estimated boundary (ideal boundary), respectively. The overall system, which was developed using Microsoft Visual C++, is real-time and accurate.

Multimodality 3D Superposition and Automated Whole Brain Tractography: Comprehensive Printing of the Functional Brain

PubMed Central

Brimley, Cameron J; Sublett, Jesna Mathew; Stefanowicz, Edward; Flora, Sarah; Mongelluzzo, Gino; Schirmer, Clemens M

2017-01-01

Whole brain tractography using diffusion tensor imaging (DTI) sequences can be used to map cerebral connectivity; however, this can be time-consuming due to the manual component of image manipulation required, calling for the need for a standardized, automated, and accurate fiber tracking protocol with automatic whole brain tractography (AWBT). Interpreting conventional two-dimensional (2D) images, such as computed tomography (CT) and magnetic resonance imaging (MRI), as an intraoperative three-dimensional (3D) environment is a difficult task with recognized inter-operator variability. Three-dimensional printing in neurosurgery has gained significant traction in the past decade, and as software, equipment, and practices become more refined, trainee education, surgical skills, research endeavors, innovation, patient education, and outcomes via valued care is projected to improve. We describe a novel multimodality 3D superposition (MMTS) technique, which fuses multiple imaging sequences alongside cerebral tractography into one patient-specific 3D printed model. Inferences on cost and improved outcomes fueled by encouraging patient engagement are explored. PMID:29201580

Multimodality 3D Superposition and Automated Whole Brain Tractography: Comprehensive Printing of the Functional Brain.

PubMed

Konakondla, Sanjay; Brimley, Cameron J; Sublett, Jesna Mathew; Stefanowicz, Edward; Flora, Sarah; Mongelluzzo, Gino; Schirmer, Clemens M

2017-09-29

Whole brain tractography using diffusion tensor imaging (DTI) sequences can be used to map cerebral connectivity; however, this can be time-consuming due to the manual component of image manipulation required, calling for the need for a standardized, automated, and accurate fiber tracking protocol with automatic whole brain tractography (AWBT). Interpreting conventional two-dimensional (2D) images, such as computed tomography (CT) and magnetic resonance imaging (MRI), as an intraoperative three-dimensional (3D) environment is a difficult task with recognized inter-operator variability. Three-dimensional printing in neurosurgery has gained significant traction in the past decade, and as software, equipment, and practices become more refined, trainee education, surgical skills, research endeavors, innovation, patient education, and outcomes via valued care is projected to improve. We describe a novel multimodality 3D superposition (MMTS) technique, which fuses multiple imaging sequences alongside cerebral tractography into one patient-specific 3D printed model. Inferences on cost and improved outcomes fueled by encouraging patient engagement are explored.

A complete system for 3D reconstruction of roots for phenotypic analysis.

PubMed

Kumar, Pankaj; Cai, Jinhai; Miklavcic, Stanley J

2015-01-01

Here we present a complete system for 3D reconstruction of roots grown in a transparent gel medium or washed and suspended in water. The system is capable of being fully automated as it is self calibrating. The system starts with detection of root tips in root images from an image sequence generated by a turntable motion. Root tips are detected using the statistics of Zernike moments on image patches centred on high curvature points on root boundary and Bayes classification rule. The detected root tips are tracked in the image sequence using a multi-target tracking algorithm. Conics are fitted to the root tip trajectories using a novel ellipse fitting algorithm which weighs the data points by its eccentricity. The conics projected from the circular trajectory have a complex conjugate intersection which are image of the circular points. Circular points constraint the image of the absolute conics which are directly related to the internal parameters of the camera. The pose of the camera is computed from the image of the rotation axis and the horizon. The silhouettes of the roots and camera parameters are used to reconstruction the 3D voxel model of the roots. We show the results of real 3D reconstruction of roots which are detailed and realistic for phenotypic analysis.

Multistep Lattice-Voxel method utilizing lattice function for Monte-Carlo treatment planning with pixel based voxel model.

PubMed

Kumada, H; Saito, K; Nakamura, T; Sakae, T; Sakurai, H; Matsumura, A; Ono, K

2011-12-01

Treatment planning for boron neutron capture therapy generally utilizes Monte-Carlo methods for calculation of the dose distribution. The new treatment planning system JCDS-FX employs the multi-purpose Monte-Carlo code PHITS to calculate the dose distribution. JCDS-FX allows to build a precise voxel model consisting of pixel based voxel cells in the scale of 0.4×0.4×2.0 mm(3) voxel in order to perform high-accuracy dose estimation, e.g. for the purpose of calculating the dose distribution in a human body. However, the miniaturization of the voxel size increases calculation time considerably. The aim of this study is to investigate sophisticated modeling methods which can perform Monte-Carlo calculations for human geometry efficiently. Thus, we devised a new voxel modeling method "Multistep Lattice-Voxel method," which can configure a voxel model that combines different voxel sizes by utilizing the lattice function over and over. To verify the performance of the calculation with the modeling method, several calculations for human geometry were carried out. The results demonstrated that the Multistep Lattice-Voxel method enabled the precise voxel model to reduce calculation time substantially while keeping the high-accuracy of dose estimation. Copyright © 2011 Elsevier Ltd. All rights reserved.

Automated Voxel-Based Analysis of Volumetric Dynamic Contrast-Enhanced CT Data Improves Measurement of Serial Changes in Tumor Vascular Biomarkers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Coolens, Catherine, E-mail: catherine.coolens@rmp.uhn.on.ca; Department of Radiation Oncology, University of Toronto, Toronto, Ontario; Institute of Biomaterials and Biomedical Engineering, University of Toronto, Toronto, Ontario

2015-01-01

Objectives: Development of perfusion imaging as a biomarker requires more robust methodologies for quantification of tumor physiology that allow assessment of volumetric tumor heterogeneity over time. This study proposes a parametric method for automatically analyzing perfused tissue from volumetric dynamic contrast-enhanced (DCE) computed tomography (CT) scans and assesses whether this 4-dimensional (4D) DCE approach is more robust and accurate than conventional, region-of-interest (ROI)-based CT methods in quantifying tumor perfusion with preliminary evaluation in metastatic brain cancer. Methods and Materials: Functional parameter reproducibility and analysis of sensitivity to imaging resolution and arterial input function were evaluated in image sets acquired from amore » 320-slice CT with a controlled flow phantom and patients with brain metastases, whose treatments were planned for stereotactic radiation surgery and who consented to a research ethics board-approved prospective imaging biomarker study. A voxel-based temporal dynamic analysis (TDA) methodology was used at baseline, at day 7, and at day 20 after treatment. The ability to detect changes in kinetic parameter maps in clinical data sets was investigated for both 4D TDA and conventional 2D ROI-based analysis methods. Results: A total of 7 brain metastases in 3 patients were evaluated over the 3 time points. The 4D TDA method showed improved spatial efficacy and accuracy of perfusion parameters compared to ROI-based DCE analysis (P<.005), with a reproducibility error of less than 2% when tested with DCE phantom data. Clinically, changes in transfer constant from the blood plasma into the extracellular extravascular space (K{sub trans}) were seen when using TDA, with substantially smaller errors than the 2D method on both day 7 post radiation surgery (±13%; P<.05) and by day 20 (±12%; P<.04). Standard methods showed a decrease in K{sub trans} but with large uncertainty (111.6 ± 150

Automated identification of RNA 3D modules with discriminative power in RNA structural alignments.

PubMed

Theis, Corinna; Höner Zu Siederdissen, Christian; Hofacker, Ivo L; Gorodkin, Jan

2013-12-01

Recent progress in predicting RNA structure is moving towards filling the 'gap' in 2D RNA structure prediction where, for example, predicted internal loops often form non-canonical base pairs. This is increasingly recognized with the steady increase of known RNA 3D modules. There is a general interest in matching structural modules known from one molecule to other molecules for which the 3D structure is not known yet. We have created a pipeline, metaRNAmodules, which completely automates extracting putative modules from the FR3D database and mapping of such modules to Rfam alignments to obtain comparative evidence. Subsequently, the modules, initially represented by a graph, are turned into models for the RMDetect program, which allows to test their discriminative power using real and randomized Rfam alignments. An initial extraction of 22 495 3D modules in all PDB files results in 977 internal loop and 17 hairpin modules with clear discriminatory power. Many of these modules describe only minor variants of each other. Indeed, mapping of the modules onto Rfam families results in 35 unique locations in 11 different families. The metaRNAmodules pipeline source for the internal loop modules is available at http://rth.dk/resources/mrm.

Modular high power diode lasers with flexible 3D multiplexing arrangement optimized for automated manufacturing

NASA Astrophysics Data System (ADS)

Könning, Tobias; Bayer, Andreas; Plappert, Nora; Faßbender, Wilhelm; Dürsch, Sascha; Küster, Matthias; Hubrich, Ralf; Wolf, Paul; Köhler, Bernd; Biesenbach, Jens

2018-02-01

A novel 3-dimensional arrangement of mirrors is used to re-arrange beams from 1-D and 2-D high power diode laser arrays. The approach allows for a variety of stacking geometries, depending on individual requirements. While basic building blocks, including collimating optics, always remain the same, most adaptations can be realized by simple rearrangement of a few optical components. Due to fully automated alignment processes, the required changes can be realized in software by changing coordinates, rather than requiring customized mechanical components. This approach minimizes development costs due to its flexibility, while reducing overall product cost by using similar building blocks for a variety of products and utilizing a high grade of automation. The modules can be operated with industrial grade water, lowering overall system and maintenance cost. Stackable macro coolers are used as the smallest building block of the system. Each cooler can hold up to five diode laser bars. Micro optical components, collimating the beam, are mounted directly to the cooler. All optical assembly steps are fully automated. Initially, the beams from all laser bars propagate in the same direction. Key to the concept is an arrangement of deflectors, which re-arrange the beams into a 2-D array of the desired shape and high fill factor. Standard multiplexing techniques like polarization- or wavelengths-multiplexing have been implemented as well. A variety of fiber coupled modules ranging from a few hundred watts of optical output power to multiple kilowatts of power, as well as customized laser spot geometries like uniform line sources, have been realized.

Statistical Segmentation of Surgical Instruments in 3D Ultrasound Images

PubMed Central

Linguraru, Marius George; Vasilyev, Nikolay V.; Del Nido, Pedro J.; Howe, Robert D.

2008-01-01

The recent development of real-time 3D ultrasound enables intracardiac beating heart procedures, but the distorted appearance of surgical instruments is a major challenge to surgeons. In addition, tissue and instruments have similar gray levels in US images and the interface between instruments and tissue is poorly defined. We present an algorithm that automatically estimates instrument location in intracardiac procedures. Expert-segmented images are used to initialize the statistical distributions of blood, tissue and instruments. Voxels are labeled through an iterative expectation-maximization algorithm using information from the neighboring voxels through a smoothing kernel. Once the three classes of voxels are separated, additional neighboring information is combined with the known shape characteristics of instruments in order to correct for misclassifications. We analyze the major axis of segmented data through their principal components and refine the results by a watershed transform, which corrects the results at the contact between instrument and tissue. We present results on 3D in-vitro data from a tank trial, and 3D in-vivo data from cardiac interventions on porcine beating hearts, using instruments of four types of materials. The comparison of algorithm results to expert-annotated images shows the correct segmentation and position of the instrument shaft. PMID:17521802

Fully automated, real-time 3D ultrasound segmentation to estimate first trimester placental volume using deep learning.

PubMed

Looney, Pádraig; Stevenson, Gordon N; Nicolaides, Kypros H; Plasencia, Walter; Molloholli, Malid; Natsis, Stavros; Collins, Sally L

2018-06-07

We present a new technique to fully automate the segmentation of an organ from 3D ultrasound (3D-US) volumes, using the placenta as the target organ. Image analysis tools to estimate organ volume do exist but are too time consuming and operator dependant. Fully automating the segmentation process would potentially allow the use of placental volume to screen for increased risk of pregnancy complications. The placenta was segmented from 2,393 first trimester 3D-US volumes using a semiautomated technique. This was quality controlled by three operators to produce the "ground-truth" data set. A fully convolutional neural network (OxNNet) was trained using this ground-truth data set to automatically segment the placenta. OxNNet delivered state-of-the-art automatic segmentation. The effect of training set size on the performance of OxNNet demonstrated the need for large data sets. The clinical utility of placental volume was tested by looking at predictions of small-for-gestational-age babies at term. The receiver-operating characteristics curves demonstrated almost identical results between OxNNet and the ground-truth). Our results demonstrated good similarity to the ground-truth and almost identical clinical results for the prediction of SGA.

Iterative Reconstruction of Volumetric Particle Distribution for 3D Velocimetry

NASA Astrophysics Data System (ADS)

Wieneke, Bernhard; Neal, Douglas

2011-11-01

A number of different volumetric flow measurement techniques exist for following the motion of illuminated particles. For experiments that have lower seeding densities, 3D-PTV uses recorded images from typically 3-4 cameras and then tracks the individual particles in space and time. This technique is effective in flows that have lower seeding densities. For flows that have a higher seeding density, tomographic PIV uses a tomographic reconstruction algorithm (e.g. MART) to reconstruct voxel intensities of the recorded volume followed by the cross-correlation of subvolumes to provide the instantaneous 3D vector fields on a regular grid. A new hybrid algorithm is presented which iteratively reconstructs the 3D-particle distribution directly using particles with certain imaging properties instead of voxels as base functions. It is shown with synthetic data that this method is capable of reconstructing densely seeded flows up to 0.05 particles per pixel (ppp) with the same or higher accuracy than 3D-PTV and tomographic PIV. Finally, this new method is validated using experimental data on a turbulent jet.

Comparison of the accuracy of 3-dimensional cone-beam computed tomography and micro-computed tomography reconstructions by using different voxel sizes.

PubMed

Maret, Delphine; Peters, Ove A; Galibourg, Antoine; Dumoncel, Jean; Esclassan, Rémi; Kahn, Jean-Luc; Sixou, Michel; Telmon, Norbert

2014-09-01

Cone-beam computed tomography (CBCT) data are, in principle, metrically exact. However, clinicians need to consider the precision of measurements of dental morphology as well as other hard tissue structures. CBCT spatial resolution, and thus image reconstruction quality, is restricted by the acquisition voxel size. The aim of this study was to assess geometric discrepancies among 3-dimensional CBCT reconstructions relative to the micro-CT reference. A total of 37 permanent teeth from 9 mandibles were scanned with CBCT 9500 and 9000 3D and micro-CT. After semiautomatic segmentation, reconstructions were obtained from CBCT acquisitions (voxel sizes 76, 200, and 300 μm) and from micro-CT (voxel size 41 μm). All reconstructions were positioned in the same plane by image registration. The topography of the geometric discrepancies was displayed by using a color map allowing the maximum differences to be located. The maximum differences were mainly found at the cervical margins and on the cusp tips or incisal edges. Geometric reconstruction discrepancies were significant at 300-μm resolution (P = .01, Wilcoxon test). To study hard tissue morphology, CBCT acquisitions require voxel sizes smaller than 300 μm. This experimental study will have to be complemented by studies in vivo that consider the conditions of clinical practice. Copyright © 2014 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Postprocessing of Voxel-Based Topologies for Additive Manufacturing Using the Computational Geometry Algorithms Library (CGAL)

DTIC Science & Technology

2015-06-01

10-2014 to 00-11-2014 4. TITLE AND SUBTITLE Postprocessing of Voxel-Based Topologies for Additive Manufacturing Using the Computational Geometry...ABSTRACT Postprocessing of 3-dimensional (3-D) topologies that are defined as a set of voxels using the Computational Geometry Algorithms Library (CGAL... computational geometry algorithms, several of which are suited to the task. The work flow described in this report involves first defining a set of

Automated segmentation and geometrical modeling of the tricuspid aortic valve in 3D echocardiographic images.

PubMed

Pouch, Alison M; Wang, Hongzhi; Takabe, Manabu; Jackson, Benjamin M; Sehgal, Chandra M; Gorman, Joseph H; Gorman, Robert C; Yushkevich, Paul A

2013-01-01

The aortic valve has been described with variable anatomical definitions, and the consistency of 2D manual measurement of valve dimensions in medical image data has been questionable. Given the importance of image-based morphological assessment in the diagnosis and surgical treatment of aortic valve disease, there is considerable need to develop a standardized framework for 3D valve segmentation and shape representation. Towards this goal, this work integrates template-based medial modeling and multi-atlas label fusion techniques to automatically delineate and quantitatively describe aortic leaflet geometry in 3D echocardiographic (3DE) images, a challenging task that has been explored only to a limited extent. The method makes use of expert knowledge of aortic leaflet image appearance, generates segmentations with consistent topology, and establishes a shape-based coordinate system on the aortic leaflets that enables standardized automated measurements. In this study, the algorithm is evaluated on 11 3DE images of normal human aortic leaflets acquired at mid systole. The clinical relevance of the method is its ability to capture leaflet geometry in 3DE image data with minimal user interaction while producing consistent measurements of 3D aortic leaflet geometry.

Associative image analysis: a method for automated quantification of 3D multi-parameter images of brain tissue

PubMed Central

Bjornsson, Christopher S; Lin, Gang; Al-Kofahi, Yousef; Narayanaswamy, Arunachalam; Smith, Karen L; Shain, William; Roysam, Badrinath

2009-01-01

Brain structural complexity has confounded prior efforts to extract quantitative image-based measurements. We present a systematic ‘divide and conquer’ methodology for analyzing three-dimensional (3D) multi-parameter images of brain tissue to delineate and classify key structures, and compute quantitative associations among them. To demonstrate the method, thick (~100 μm) slices of rat brain tissue were labeled using 3 – 5 fluorescent signals, and imaged using spectral confocal microscopy and unmixing algorithms. Automated 3D segmentation and tracing algorithms were used to delineate cell nuclei, vasculature, and cell processes. From these segmentations, a set of 23 intrinsic and 8 associative image-based measurements was computed for each cell. These features were used to classify astrocytes, microglia, neurons, and endothelial cells. Associations among cells and between cells and vasculature were computed and represented as graphical networks to enable further analysis. The automated results were validated using a graphical interface that permits investigator inspection and corrective editing of each cell in 3D. Nuclear counting accuracy was >89%, and cell classification accuracy ranged from 81–92% depending on cell type. We present a software system named FARSIGHT implementing our methodology. Its output is a detailed XML file containing measurements that may be used for diverse quantitative hypothesis-driven and exploratory studies of the central nervous system. PMID:18294697

The design of 3D scaffold for tissue engineering using automated scaffold design algorithm.

PubMed

Mahmoud, Shahenda; Eldeib, Ayman; Samy, Sherif

2015-06-01

Several progresses have been introduced in the field of bone regenerative medicine. A new term tissue engineering (TE) was created. In TE, a highly porous artificial extracellular matrix or scaffold is required to accommodate cells and guide their growth in three dimensions. The design of scaffolds with desirable internal and external structure represents a challenge for TE. In this paper, we introduce a new method known as automated scaffold design (ASD) for designing a 3D scaffold with a minimum mismatches for its geometrical parameters. The method makes use of k-means clustering algorithm to separate the different tissues and hence decodes the defected bone portions. The segmented portions of different slices are registered to construct the 3D volume for the data. It also uses an isosurface rendering technique for 3D visualization of the scaffold and bones. It provides the ability to visualize the transplanted as well as the normal bone portions. The proposed system proves good performance in both the segmentation results and visualizations aspects.

Automated 3D quantitative assessment and measurement of alpha angles from the femoral head-neck junction using MR imaging

NASA Astrophysics Data System (ADS)

Xia, Ying; Fripp, Jurgen; Chandra, Shekhar S.; Walker, Duncan; Crozier, Stuart; Engstrom, Craig

2015-10-01

To develop an automated approach for 3D quantitative assessment and measurement of alpha angles from the femoral head-neck (FHN) junction using bone models derived from magnetic resonance (MR) images of the hip joint. Bilateral MR images of the hip joints were acquired from 30 male volunteers (healthy active individuals and high-performance athletes, aged 18-49 years) using a water-excited 3D dual echo steady state (DESS) sequence. In a subset of these subjects (18 water-polo players), additional True Fast Imaging with Steady-state Precession (TrueFISP) images were acquired from the right hip joint. For both MR image sets, an active shape model based algorithm was used to generate automated 3D bone reconstructions of the proximal femur. Subsequently, a local coordinate system of the femur was constructed to compute a 2D shape map to project femoral head sphericity for calculation of alpha angles around the FHN junction. To evaluate automated alpha angle measures, manual analyses were performed on anterosuperior and anterior radial MR slices from the FHN junction that were automatically reformatted using the constructed coordinate system. High intra- and inter-rater reliability (intra-class correlation coefficients  >  0.95) was found for manual alpha angle measurements from the auto-extracted anterosuperior and anterior radial slices. Strong correlations were observed between manual and automatic measures of alpha angles for anterosuperior (r  =  0.84) and anterior (r  =  0.92) FHN positions. For matched DESS and TrueFISP images, there were no significant differences between automated alpha angle measures obtained from the upper anterior quadrant of the FHN junction (two-way repeated measures ANOVA, F  <  0.01, p  =  0.98). Our automatic 3D method analysed MR images of the hip joints to generate alpha angle measures around the FHN junction circumference with very good reliability and reproducibility. This work has the

Step-by-step guide to building an inexpensive 3D printed motorized positioning stage for automated high-content screening microscopy.

PubMed

Schneidereit, Dominik; Kraus, Larissa; Meier, Jochen C; Friedrich, Oliver; Gilbert, Daniel F

2017-06-15

High-content screening microscopy relies on automation infrastructure that is typically proprietary, non-customizable, costly and requires a high level of skill to use and maintain. The increasing availability of rapid prototyping technology makes it possible to quickly engineer alternatives to conventional automation infrastructure that are low-cost and user-friendly. Here, we describe a 3D printed inexpensive open source and scalable motorized positioning stage for automated high-content screening microscopy and provide detailed step-by-step instructions to re-building the device, including a comprehensive parts list, 3D design files in STEP (Standard for the Exchange of Product model data) and STL (Standard Tessellation Language) format, electronic circuits and wiring diagrams as well as software code. System assembly including 3D printing requires approx. 30h. The fully assembled device is light-weight (1.1kg), small (33×20×8cm) and extremely low-cost (approx. EUR 250). We describe positioning characteristics of the stage, including spatial resolution, accuracy and repeatability, compare imaging data generated with our device to data obtained using a commercially available microplate reader, demonstrate its suitability to high-content microscopy in 96-well high-throughput screening format and validate its applicability to automated functional Cl - - and Ca 2+ -imaging with recombinant HEK293 cells as a model system. A time-lapse video of the stage during operation and as part of a custom assembled screening robot can be found at https://vimeo.com/158813199. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Towards Automated Large-Scale 3D Phenotyping of Vineyards under Field Conditions.

PubMed

Rose, Johann Christian; Kicherer, Anna; Wieland, Markus; Klingbeil, Lasse; Töpfer, Reinhard; Kuhlmann, Heiner

2016-12-15

In viticulture, phenotypic data are traditionally collected directly in the field via visual and manual means by an experienced person. This approach is time consuming, subjective and prone to human errors. In recent years, research therefore has focused strongly on developing automated and non-invasive sensor-based methods to increase data acquisition speed, enhance measurement accuracy and objectivity and to reduce labor costs. While many 2D methods based on image processing have been proposed for field phenotyping, only a few 3D solutions are found in the literature. A track-driven vehicle consisting of a camera system, a real-time-kinematic GPS system for positioning, as well as hardware for vehicle control, image storage and acquisition is used to visually capture a whole vine row canopy with georeferenced RGB images. In the first post-processing step, these images were used within a multi-view-stereo software to reconstruct a textured 3D point cloud of the whole grapevine row. A classification algorithm is then used in the second step to automatically classify the raw point cloud data into the semantic plant components, grape bunches and canopy. In the third step, phenotypic data for the semantic objects is gathered using the classification results obtaining the quantity of grape bunches, berries and the berry diameter.

Validation of automated white matter hyperintensity segmentation.

PubMed

Smart, Sean D; Firbank, Michael J; O'Brien, John T

2011-01-01

Introduction. White matter hyperintensities (WMHs) are a common finding on MRI scans of older people and are associated with vascular disease. We compared 3 methods for automatically segmenting WMHs from MRI scans. Method. An operator manually segmented WMHs on MRI images from a 3T scanner. The scans were also segmented in a fully automated fashion by three different programmes. The voxel overlap between manual and automated segmentation was compared. Results. Between observer overlap ratio was 63%. Using our previously described in-house software, we had overlap of 62.2%. We investigated the use of a modified version of SPM segmentation; however, this was not successful, with only 14% overlap. Discussion. Using our previously reported software, we demonstrated good segmentation of WMHs in a fully automated fashion.

Accuracy and reproducibility of aortic annular measurements obtained from echocardiographic 3D manual and semi-automated software analyses in patients referred for transcatheter aortic valve implantation: implication for prosthesis size selection.

PubMed

Stella, Stefano; Italia, Leonardo; Geremia, Giulia; Rosa, Isabella; Ancona, Francesco; Marini, Claudia; Capogrosso, Cristina; Giglio, Manuela; Montorfano, Matteo; Latib, Azeem; Margonato, Alberto; Colombo, Antonio; Agricola, Eustachio

2018-02-06

A 3D transoesophageal echocardiography (3D-TOE) reconstruction tool has recently been introduced. The system automatically configures a geometric model of the aortic root and performs quantitative analysis of these structures. We compared the measurements of the aortic annulus (AA) obtained by semi-automated 3D-TOE quantitative software and manual analysis vs. multislice computed tomography (MSCT) ones. One hundred and seventy-five patients (mean age 81.3 ± 6.3 years, 77 men) who underwent both MSCT and 3D-TOE for annulus assessment before transcatheter aortic valve implantation were analysed. Hypothetical prosthetic valve sizing was evaluated using the 3D manual, semi-automated measurements using manufacturer-recommended CT-based sizing algorithm as gold standard. Good correlation between 3D-TOE methods vs. MSCT measurements was found, but the semi-automated analysis demonstrated slightly better correlations for AA major diameter (r = 0.89), perimeter (r = 0.89), and area (r = 0.85) (all P < 0.0001) than manual one. Both 3D methods underestimated the MSCT measurements, but semi-automated measurements showed narrower limits of agreement and lesser bias than manual measurements for most of AA parameters. On average, 3D-TOE semi-automated major diameter, area, and perimeter underestimated the respective MSCT measurements by 7.4%, 3.5%, and 4.4%, respectively, whereas minor diameter was overestimated by 0.3%. Moderate agreement for valve sizing for both 3D-TOE techniques was found: Kappa agreement 0.5 for both semi-automated and manual analysis. Interobserver and intraobserver agreements for the AA measurements were excellent for both techniques (intraclass correlation coefficients for all parameters >0.80). The 3D-TOE semi-automated analysis of AA is feasible and reliable and can be used in clinical practice as an alternative to MSCT for AA assessment. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author

A Comprehensive Automated 3D Approach for Building Extraction, Reconstruction, and Regularization from Airborne Laser Scanning Point Clouds

PubMed Central

Dorninger, Peter; Pfeifer, Norbert

2008-01-01

Three dimensional city models are necessary for supporting numerous management applications. For the determination of city models for visualization purposes, several standardized workflows do exist. They are either based on photogrammetry or on LiDAR or on a combination of both data acquisition techniques. However, the automated determination of reliable and highly accurate city models is still a challenging task, requiring a workflow comprising several processing steps. The most relevant are building detection, building outline generation, building modeling, and finally, building quality analysis. Commercial software tools for building modeling require, generally, a high degree of human interaction and most automated approaches described in literature stress the steps of such a workflow individually. In this article, we propose a comprehensive approach for automated determination of 3D city models from airborne acquired point cloud data. It is based on the assumption that individual buildings can be modeled properly by a composition of a set of planar faces. Hence, it is based on a reliable 3D segmentation algorithm, detecting planar faces in a point cloud. This segmentation is of crucial importance for the outline detection and for the modeling approach. We describe the theoretical background, the segmentation algorithm, the outline detection, and the modeling approach, and we present and discuss several actual projects. PMID:27873931

Automated torso organ segmentation from 3D CT images using structured perceptron and dual decomposition

NASA Astrophysics Data System (ADS)

Nimura, Yukitaka; Hayashi, Yuichiro; Kitasaka, Takayuki; Mori, Kensaku

2015-03-01

This paper presents a method for torso organ segmentation from abdominal CT images using structured perceptron and dual decomposition. A lot of methods have been proposed to enable automated extraction of organ regions from volumetric medical images. However, it is necessary to adjust empirical parameters of them to obtain precise organ regions. This paper proposes an organ segmentation method using structured output learning. Our method utilizes a graphical model and binary features which represent the relationship between voxel intensities and organ labels. Also we optimize the weights of the graphical model by structured perceptron and estimate the best organ label for a given image by dynamic programming and dual decomposition. The experimental result revealed that the proposed method can extract organ regions automatically using structured output learning. The error of organ label estimation was 4.4%. The DICE coefficients of left lung, right lung, heart, liver, spleen, pancreas, left kidney, right kidney, and gallbladder were 0.91, 0.95, 0.77, 0.81, 0.74, 0.08, 0.83, 0.84, and 0.03, respectively.

Reproducibility study of whole-brain 1H spectroscopic imaging with automated quantification.

PubMed

Gu, Meng; Kim, Dong-Hyun; Mayer, Dirk; Sullivan, Edith V; Pfefferbaum, Adolf; Spielman, Daniel M

2008-09-01

A reproducibility study of proton MR spectroscopic imaging ((1)H-MRSI) of the human brain was conducted to evaluate the reliability of an automated 3D in vivo spectroscopic imaging acquisition and associated quantification algorithm. A PRESS-based pulse sequence was implemented using dualband spectral-spatial RF pulses designed to fully excite the singlet resonances of choline (Cho), creatine (Cre), and N-acetyl aspartate (NAA) while simultaneously suppressing water and lipids; 1% of the water signal was left to be used as a reference signal for robust data processing, and additional lipid suppression was obtained using adiabatic inversion recovery. Spiral k-space trajectories were used for fast spectral and spatial encoding yielding high-quality spectra from 1 cc voxels throughout the brain with a 13-min acquisition time. Data were acquired with an 8-channel phased-array coil and optimal signal-to-noise ratio (SNR) for the combined signals was achieved using a weighting based on the residual water signal. Automated quantification of the spectrum of each voxel was performed using LCModel. The complete study consisted of eight healthy adult subjects to assess intersubject variations and two subjects scanned six times each to assess intrasubject variations. The results demonstrate that reproducible whole-brain (1)H-MRSI data can be robustly obtained with the proposed methods.

Standardized method to quantify the variation in voxel value distribution in patient-simulated CBCT data sets.

PubMed

Spin-Neto, R; Gotfredsen, E; Wenzel, A

2015-01-01

To suggest a standardized method to assess the variation in voxel value distribution in patient-simulated CBCT data sets and the effect of time between exposures (TBE). Additionally, a measurement of reproducibility, Aarhus measurement of reproducibility (AMORe), is introduced, which could be used for quality assurance purposes. Six CBCT units were tested [Cranex(®) 3D/CRAN (Soredex Oy, Tuusula, Finland); Scanora(®) 3D/SCAN (Soredex Oy); NewTom™ 5G/NEW5 (QR srl, Verona, Italy); i-CAT/ICAT (Imaging Sciences International, Hatfield, PA); 3D Accuitomo FPD80/ACCU (Morita, Kyoto, Japan); and NewTom VG/NEWV (QR srl)]. Two sets of volumetric data of a wax-imbedded dry human skull (containing a titanium implant) were acquired by each CBCT unit at two sessions on separate days. Each session consisted 21 exposures: 1 "initial" followed by a 30-min interval (initial data set), 10 acquired with 30-min TBE (data sets 1-10) and 10 acquired with 15-min TBE (data sets 11-20). CBCT data were exported as digital imaging and communications in medicine files and converted to text files containing x, y and z positions and grey shade for each voxel. Subtractions were performed voxel-by-voxel in two set-ups: (1) between two consecutive data sets and (2) between any subsequent data set and data set 1. The mean grey shade variation for each voxel was calculated for each unit/session. The largest mean grey shade variation was found in the subtraction set-up 2 (27-447 shades of grey, depending on the unit). Considering subtraction set-up 1, the highest variation was seen for NEW5, between data sets 1 and the initial. Discrepancies in voxel value distribution were found by comparing the initial examination of the day with the subsequent examinations. TBE had no predictable effect on the variation of CBCT-derived voxel values. AMORe ranged between 0 and 64.

Automated 3D Damaged Cavity Model Builder for Lower Surface Acreage Tile on Orbiter

NASA Technical Reports Server (NTRS)

Belknap, Shannon; Zhang, Michael

2013-01-01

The 3D Automated Thermal Tool for Damaged Acreage Tile Math Model builder was developed to perform quickly and accurately 3D thermal analyses on damaged lower surface acreage tiles and structures beneath the damaged locations on a Space Shuttle Orbiter. The 3D model builder created both TRASYS geometric math models (GMMs) and SINDA thermal math models (TMMs) to simulate an idealized damaged cavity in the damaged tile(s). The GMMs are processed in TRASYS to generate radiation conductors between the surfaces in the cavity. The radiation conductors are inserted into the TMMs, which are processed in SINDA to generate temperature histories for all of the nodes on each layer of the TMM. The invention allows a thermal analyst to create quickly and accurately a 3D model of a damaged lower surface tile on the orbiter. The 3D model builder can generate a GMM and the correspond ing TMM in one or two minutes, with the damaged cavity included in the tile material. A separate program creates a configuration file, which would take a couple of minutes to edit. This configuration file is read by the model builder program to determine the location of the damage, the correct tile type, tile thickness, structure thickness, and SIP thickness of the damage, so that the model builder program can build an accurate model at the specified location. Once the models are built, they are processed by the TRASYS and SINDA.

Phase correction for three-dimensional (3D) diffusion-weighted interleaved EPI using 3D multiplexed sensitivity encoding and reconstruction (3D-MUSER).

PubMed

Chang, Hing-Chiu; Hui, Edward S; Chiu, Pui-Wai; Liu, Xiaoxi; Chen, Nan-Kuei

2018-05-01

Three-dimensional (3D) multiplexed sensitivity encoding and reconstruction (3D-MUSER) algorithm is proposed to reduce aliasing artifacts and signal corruption caused by inter-shot 3D phase variations in 3D diffusion-weighted echo planar imaging (DW-EPI). 3D-MUSER extends the original framework of multiplexed sensitivity encoding (MUSE) to a hybrid k-space-based reconstruction, thereby enabling the correction of inter-shot 3D phase variations. A 3D single-shot EPI navigator echo was used to measure inter-shot 3D phase variations. The performance of 3D-MUSER was evaluated by analyses of point-spread function (PSF), signal-to-noise ratio (SNR), and artifact levels. The efficacy of phase correction using 3D-MUSER for different slab thicknesses and b-values were investigated. Simulations showed that 3D-MUSER could eliminate artifacts because of through-slab phase variation and reduce noise amplification because of SENSE reconstruction. All aliasing artifacts and signal corruption in 3D interleaved DW-EPI acquired with different slab thicknesses and b-values were reduced by our new algorithm. A near-whole brain single-slab 3D DTI with 1.3-mm isotropic voxel acquired at 1.5T was successfully demonstrated. 3D phase correction for 3D interleaved DW-EPI data is made possible by 3D-MUSER, thereby improving feasible slab thickness and maximum feasible b-value. Magn Reson Med 79:2702-2712, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Label free cell tracking in 3D tissue engineering constructs with high resolution imaging

NASA Astrophysics Data System (ADS)

Smith, W. A.; Lam, K.-P.; Dempsey, K. P.; Mazzocchi-Jones, D.; Richardson, J. B.; Yang, Y.

2014-02-01

Within the field of tissue engineering there is an emphasis on studying 3-D live tissue structures. Consequently, to investigate and identify cellular activities and phenotypes in a 3-D environment for all in vitro experiments, including shape, migration/proliferation and axon projection, it is necessary to adopt an optical imaging system that enables monitoring 3-D cellular activities and morphology through the thickness of the construct for an extended culture period without cell labeling. This paper describes a new 3-D tracking algorithm developed for Cell-IQ®, an automated cell imaging platform, which has been equipped with an environmental chamber optimized to enable capturing time-lapse sequences of live cell images over a long-term period without cell labeling. As an integral part of the algorithm, a novel auto-focusing procedure was developed for phase contrast microscopy equipped with 20x and 40x objectives, to provide a more accurate estimation of cell growth/trajectories by allowing 3-D voxels to be computed at high spatiotemporal resolution and cell density. A pilot study was carried out in a phantom system consisting of horizontally aligned nanofiber layers (with precise spacing between them), to mimic features well exemplified in cellular activities of neuronal growth in a 3-D environment. This was followed by detailed investigations concerning axonal projections and dendritic circuitry formation in a 3-D tissue engineering construct. Preliminary work on primary animal neuronal cells in response to chemoattractant and topographic cue within the scaffolds has produced encouraging results.

Voxel modelling of sands and gravels of Pleistocene Rhine and Meuse deposits in Flanders (Belgium)

NASA Astrophysics Data System (ADS)

van Haren, Tom; Dirix, Katrijn; De Koninck, Roel

2017-04-01

Voxel modelling or 3D volume modelling of Quaternary raw materials is VITO's next step in the geological layer modelling of the Flanders and Brussels Capital Region in Belgium (G3D - Matthijs et al., 2013). The aim is to schematise deposits as voxels ('volumetric pixels') that represent lithological information on a grid in three-dimensional space (25 x 25 x 0.5 m). A new voxel model on Pleistocene Meuse and Rhine sands and gravels will be illustrated succeeding a voxel model on loess resources (van Haren et al., 2016). The model methodology is based on a geological 'skeleton' extracted from the regional geological layer model of Flanders. This framework holds the 3D interpolated lithological information of 5.000 boreholes. First a check on quality and spatial location filtered out significant and usable lithological information. Subsequently a manual geological interpretation was performed to analyse stratigraphical arrangement and identify the raw materials of interest. Finally, a workflow was developed that automatically encodes and classifies the borehole descriptions in a standardized manner. This workflow was implemented by combining Microsoft Access® and ArcMap® and is able to convert borehole descriptions into specific geological parameters. An analysis of the conversed lithological data prior to interpolation improves the understanding of the spatial distribution, to fine tune the modelling process and to know the limitations of the data. The converted lithological data were 3D interpolated in Voxler using IDW and resulted in a model containing 52 million voxels. It gives an overview on the regional distribution and thickness variation of interesting Pleistocene aggregates of Meuse and Rhine. Much effort has been put in setting up a database structure in Microsoft Access® and Microsoft SQL Server® in order to arrange and analyse the lithological information, link the voxel model with the geological layer model and handle and analyse the resulting

Towards Automated Large-Scale 3D Phenotyping of Vineyards under Field Conditions

PubMed Central

Rose, Johann Christian; Kicherer, Anna; Wieland, Markus; Klingbeil, Lasse; Töpfer, Reinhard; Kuhlmann, Heiner

2016-01-01

In viticulture, phenotypic data are traditionally collected directly in the field via visual and manual means by an experienced person. This approach is time consuming, subjective and prone to human errors. In recent years, research therefore has focused strongly on developing automated and non-invasive sensor-based methods to increase data acquisition speed, enhance measurement accuracy and objectivity and to reduce labor costs. While many 2D methods based on image processing have been proposed for field phenotyping, only a few 3D solutions are found in the literature. A track-driven vehicle consisting of a camera system, a real-time-kinematic GPS system for positioning, as well as hardware for vehicle control, image storage and acquisition is used to visually capture a whole vine row canopy with georeferenced RGB images. In the first post-processing step, these images were used within a multi-view-stereo software to reconstruct a textured 3D point cloud of the whole grapevine row. A classification algorithm is then used in the second step to automatically classify the raw point cloud data into the semantic plant components, grape bunches and canopy. In the third step, phenotypic data for the semantic objects is gathered using the classification results obtaining the quantity of grape bunches, berries and the berry diameter. PMID:27983669

The 3D Euler solutions using automated Cartesian grid generation

NASA Technical Reports Server (NTRS)

Melton, John E.; Enomoto, Francis Y.; Berger, Marsha J.

1993-01-01

Viewgraphs on 3-dimensional Euler solutions using automated Cartesian grid generation are presented. Topics covered include: computational fluid dynamics (CFD) and the design cycle; Cartesian grid strategy; structured body fit; grid generation; prolate spheroid; and ONERA M6 wing.

Validation of Automated White Matter Hyperintensity Segmentation

PubMed Central

Smart, Sean D.; Firbank, Michael J.; O'Brien, John T.

2011-01-01

Introduction. White matter hyperintensities (WMHs) are a common finding on MRI scans of older people and are associated with vascular disease. We compared 3 methods for automatically segmenting WMHs from MRI scans. Method. An operator manually segmented WMHs on MRI images from a 3T scanner. The scans were also segmented in a fully automated fashion by three different programmes. The voxel overlap between manual and automated segmentation was compared. Results. Between observer overlap ratio was 63%. Using our previously described in-house software, we had overlap of 62.2%. We investigated the use of a modified version of SPM segmentation; however, this was not successful, with only 14% overlap. Discussion. Using our previously reported software, we demonstrated good segmentation of WMHs in a fully automated fashion. PMID:21904678

Automated bone segmentation from large field of view 3D MR images of the hip joint

NASA Astrophysics Data System (ADS)

Xia, Ying; Fripp, Jurgen; Chandra, Shekhar S.; Schwarz, Raphael; Engstrom, Craig; Crozier, Stuart

2013-10-01

Accurate bone segmentation in the hip joint region from magnetic resonance (MR) images can provide quantitative data for examining pathoanatomical conditions such as femoroacetabular impingement through to varying stages of osteoarthritis to monitor bone and associated cartilage morphometry. We evaluate two state-of-the-art methods (multi-atlas and active shape model (ASM) approaches) on bilateral MR images for automatic 3D bone segmentation in the hip region (proximal femur and innominate bone). Bilateral MR images of the hip joints were acquired at 3T from 30 volunteers. Image sequences included water-excitation dual echo stead state (FOV 38.6 × 24.1 cm, matrix 576 × 360, thickness 0.61 mm) in all subjects and multi-echo data image combination (FOV 37.6 × 23.5 cm, matrix 576 × 360, thickness 0.70 mm) for a subset of eight subjects. Following manual segmentation of femoral (head-neck, proximal-shaft) and innominate (ilium+ischium+pubis) bone, automated bone segmentation proceeded via two approaches: (1) multi-atlas segmentation incorporating non-rigid registration and (2) an advanced ASM-based scheme. Mean inter- and intra-rater reliability Dice's similarity coefficients (DSC) for manual segmentation of femoral and innominate bone were (0.970, 0.963) and (0.971, 0.965). Compared with manual data, mean DSC values for femoral and innominate bone volumes using automated multi-atlas and ASM-based methods were (0.950, 0.922) and (0.946, 0.917), respectively. Both approaches delivered accurate (high DSC values) segmentation results; notably, ASM data were generated in substantially less computational time (12 min versus 10 h). Both automated algorithms provided accurate 3D bone volumetric descriptions for MR-based measures in the hip region. The highly computational efficient ASM-based approach is more likely suitable for future clinical applications such as extracting bone-cartilage interfaces for potential cartilage segmentation.

VoxelStats: A MATLAB Package for Multi-Modal Voxel-Wise Brain Image Analysis.

PubMed

Mathotaarachchi, Sulantha; Wang, Seqian; Shin, Monica; Pascoal, Tharick A; Benedet, Andrea L; Kang, Min Su; Beaudry, Thomas; Fonov, Vladimir S; Gauthier, Serge; Labbe, Aurélie; Rosa-Neto, Pedro

2016-01-01

In healthy individuals, behavioral outcomes are highly associated with the variability on brain regional structure or neurochemical phenotypes. Similarly, in the context of neurodegenerative conditions, neuroimaging reveals that cognitive decline is linked to the magnitude of atrophy, neurochemical declines, or concentrations of abnormal protein aggregates across brain regions. However, modeling the effects of multiple regional abnormalities as determinants of cognitive decline at the voxel level remains largely unexplored by multimodal imaging research, given the high computational cost of estimating regression models for every single voxel from various imaging modalities. VoxelStats is a voxel-wise computational framework to overcome these computational limitations and to perform statistical operations on multiple scalar variables and imaging modalities at the voxel level. VoxelStats package has been developed in Matlab(®) and supports imaging formats such as Nifti-1, ANALYZE, and MINC v2. Prebuilt functions in VoxelStats enable the user to perform voxel-wise general and generalized linear models and mixed effect models with multiple volumetric covariates. Importantly, VoxelStats can recognize scalar values or image volumes as response variables and can accommodate volumetric statistical covariates as well as their interaction effects with other variables. Furthermore, this package includes built-in functionality to perform voxel-wise receiver operating characteristic analysis and paired and unpaired group contrast analysis. Validation of VoxelStats was conducted by comparing the linear regression functionality with existing toolboxes such as glim_image and RMINC. The validation results were identical to existing methods and the additional functionality was demonstrated by generating feature case assessments (t-statistics, odds ratio, and true positive rate maps). In summary, VoxelStats expands the current methods for multimodal imaging analysis by allowing the

Automated modification and fusion of voxel models to construct body phantoms with heterogeneous breast tissue: Application to MRI simulations.

PubMed

Rispoli, Joseph V; Wright, Steven M; Malloy, Craig R; McDougall, Mary P

2017-01-01

Human voxel models incorporating detailed anatomical features are vital tools for the computational evaluation of electromagnetic (EM) fields within the body. Besides whole-body human voxel models, phantoms representing smaller heterogeneous anatomical features are often employed; for example, localized breast voxel models incorporating fatty and fibroglandular tissues have been developed for a variety of EM applications including mammography simulation and dosimetry, magnetic resonance imaging (MRI), and ultra-wideband microwave imaging. However, considering wavelength effects, electromagnetic modeling of the breast at sub-microwave frequencies necessitates detailed breast phantoms in conjunction with whole-body voxel models. Heterogeneous breast phantoms are sized to fit within radiofrequency coil hardware, modified by voxel-wise extrusion, and fused to whole-body models using voxel-wise, tissue-dependent logical operators. To illustrate the utility of this method, finite-difference time-domain simulations are performed using a whole-body model integrated with a variety of available breast phantoms spanning the standard four tissue density classifications representing the majority of the population. The software library uses a combination of voxel operations to seamlessly size, modify, and fuse eleven breast phantoms to whole-body voxel models. The software is publicly available on GitHub and is linked to the file exchange at MATLAB ® Central. Simulations confirm the proportions of fatty and fibroglandular tissues in breast phantoms have significant yet predictable implications on projected power deposition in tissue. Breast phantoms may be modified and fused to whole-body voxel models using the software presented in this work; user considerations for the open-source software and resultant phantoms are discussed. Furthermore, results indicate simulating breast models as predominantly fatty tissue can considerably underestimate the potential for tissue heating in

Automated modification and fusion of voxel models to construct body phantoms with heterogeneous breast tissue: Application to MRI simulations

PubMed Central

Rispoli, Joseph V.; Wright, Steven M.; Malloy, Craig R.; McDougall, Mary P.

2017-01-01

Background Human voxel models incorporating detailed anatomical features are vital tools for the computational evaluation of electromagnetic (EM) fields within the body. Besides whole-body human voxel models, phantoms representing smaller heterogeneous anatomical features are often employed; for example, localized breast voxel models incorporating fatty and fibroglandular tissues have been developed for a variety of EM applications including mammography simulation and dosimetry, magnetic resonance imaging (MRI), and ultra-wideband microwave imaging. However, considering wavelength effects, electromagnetic modeling of the breast at sub-microwave frequencies necessitates detailed breast phantoms in conjunction with whole-body voxel models. Methods Heterogeneous breast phantoms are sized to fit within radiofrequency coil hardware, modified by voxel-wise extrusion, and fused to whole-body models using voxel-wise, tissue-dependent logical operators. To illustrate the utility of this method, finite-difference time-domain simulations are performed using a whole-body model integrated with a variety of available breast phantoms spanning the standard four tissue density classifications representing the majority of the population. Results The software library uses a combination of voxel operations to seamlessly size, modify, and fuse eleven breast phantoms to whole-body voxel models. The software is publicly available on GitHub and is linked to the file exchange at MATLAB® Central. Simulations confirm the proportions of fatty and fibroglandular tissues in breast phantoms have significant yet predictable implications on projected power deposition in tissue. Conclusions Breast phantoms may be modified and fused to whole-body voxel models using the software presented in this work; user considerations for the open-source software and resultant phantoms are discussed. Furthermore, results indicate simulating breast models as predominantly fatty tissue can considerably

Automated 3D ultrasound elastography of the breast: a phantom validation study

NASA Astrophysics Data System (ADS)

Hendriks, Gijs A. G. M.; Holländer, Branislav; Menssen, Jan; Milkowski, Andy; Hansen, Hendrik H. G.; de Korte, Chris L.

2016-04-01

In breast cancer screening, the automated breast volume scanner (ABVS) was introduced as an alternative for mammography since the latter technique is less suitable for women with dense breasts. Although clinical studies show promising results, clinicians report two disadvantages: long acquisition times (>90 s) introducing breathing artefacts, and high recall rates due to detection of many small lesions of uncertain malignant potential. Technical improvements for faster image acquisition and better discrimination between benign and malignant lesions are thus required. Therefore, the aim of this study was to investigate if 3D ultrasound elastography using plane-wave imaging is feasible. Strain images of a breast elastography phantom were acquired by an ABVS-mimicking device that allowed axial and elevational movement of the attached transducer. Pre- and post-deformation volumes were acquired with different constant speeds (between 1.25 and 40.0 mm s-1) and by three protocols: Go-Go (pre- and post-volumes with identical start and end positions), Go-Return (similar to Go-Go with opposite scanning directions) and Control (pre- and post-volumes acquired per position, this protocol can be seen as reference). Afterwards, 2D and 3D cross-correlation and strain algorithms were applied to the acquired volumes and the results were compared. The Go-Go protocol was shown to be superior with better strain image quality (CNRe and SNRe) than Go-Return and to be similar as Control. This can be attributed to applying opposite mechanical forces to the phantom during the Go-Return protocol, leading to out-of-plane motion. This motion was partly compensated by using 3D cross-correlation. However, the quality was still inferior to Go-Go. Since these results were obtained in a phantom study with controlled deformations, the effect of possible uncontrolled in vivo tissue motion artefacts has to be addressed in future studies. In conclusion, it seems feasible to implement 3D ultrasound

Direct single-layered fabrication of 3D concavo convex patterns in nano-stereolithography

NASA Astrophysics Data System (ADS)

Lim, T. W.; Park, S. H.; Yang, D. Y.; Kong, H. J.; Lee, K. S.

2006-09-01

A nano-surfacing process (NSP) is proposed to directly fabricate three-dimensional (3D) concavo convex-shaped microstructures such as micro-lens arrays using two-photon polymerization (TPP), a promising technique for fabricating arbitrary 3D highly functional micro-devices. In TPP, commonly utilized methods for fabricating complex 3D microstructures to date are based on a layer-by-layer accumulating technique employing two-dimensional sliced data derived from 3D computer-aided design data. As such, this approach requires much time and effort for precise fabrication. In this work, a novel single-layer exposure method is proposed in order to improve the fabricating efficiency for 3D concavo convex-shaped microstructures. In the NSP, 3D microstructures are divided into 13 sub-regions horizontally with consideration of the heights. Those sub-regions are then expressed as 13 characteristic colors, after which a multi-voxel matrix (MVM) is composed with the characteristic colors. Voxels with various heights and diameters are generated to construct 3D structures using a MVM scanning method. Some 3D concavo convex-shaped microstructures were fabricated to estimate the usefulness of the NSP, and the results show that it readily enables the fabrication of single-layered 3D microstructures.

Using flow information to support 3D vessel reconstruction from rotational angiography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Waechter, Irina; Bredno, Joerg; Weese, Juergen

2008-07-15

For the assessment of cerebrovascular diseases, it is beneficial to obtain three-dimensional (3D) morphologic and hemodynamic information about the vessel system. Rotational angiography is routinely used to image the 3D vascular geometry and we have shown previously that rotational subtraction angiography has the potential to also give quantitative information about blood flow. Flow information can be determined when the angiographic sequence shows inflow and possibly outflow of contrast agent. However, a standard volume reconstruction assumes that the vessel tree is uniformly filled with contrast agent during the whole acquisition. If this is not the case, the reconstruction exhibits artifacts. Here,more » we show how flow information can be used to support the reconstruction of the 3D vessel centerline and radii in this case. Our method uses the fast marching algorithm to determine the order in which voxels are analyzed. For every voxel, the rotational time intensity curve (R-TIC) is determined from the image intensities at the projection points of the current voxel. Next, the bolus arrival time of the contrast agent at the voxel is estimated from the R-TIC. Then, a measure of the intensity and duration of the enhancement is determined, from which a speed value is calculated that steers the propagation of the fast marching algorithm. The results of the fast marching algorithm are used to determine the 3D centerline by backtracking. The 3D radius is reconstructed from 2D radius estimates on the projection images. The proposed method was tested on computer simulated rotational angiography sequences with systematically varied x-ray acquisition, blood flow, and contrast agent injection parameters and on datasets from an experimental setup using an anthropomorphic cerebrovascular phantom. For the computer simulation, the mean absolute error of the 3D centerline and 3D radius estimation was 0.42 and 0.25 mm, respectively. For the experimental datasets, the mean

New portable FELIX 3D display

NASA Astrophysics Data System (ADS)

Langhans, Knut; Bezecny, Daniel; Homann, Dennis; Bahr, Detlef; Vogt, Carsten; Blohm, Christian; Scharschmidt, Karl-Heinz

1998-04-01

An improved generation of our 'FELIX 3D Display' is presented. This system is compact, light, modular and easy to transport. The created volumetric images consist of many voxels, which are generated in a half-sphere display volume. In that way a spatial object can be displayed occupying a physical space with height, width and depth. The new FELIX generation uses a screen rotating with 20 revolutions per second. This target screen is mounted by an easy to change mechanism making it possible to use appropriate screens for the specific purpose of the display. An acousto-optic deflection unit with an integrated small diode pumped laser draws the images on the spinning screen. Images can consist of up to 10,000 voxels at a refresh rate of 20 Hz. Currently two different hardware systems are investigated. The first one is based on a standard PCMCIA digital/analog converter card as an interface and is controlled by a notebook. The developed software is provided with a graphical user interface enabling several animation features. The second, new prototype is designed to display images created by standard CAD applications. It includes the development of a new high speed hardware interface suitable for state-of-the- art fast and high resolution scanning devices, which require high data rates. A true 3D volume display as described will complement the broad range of 3D visualization tools, such as volume rendering packages, stereoscopic and virtual reality techniques, which have become widely available in recent years. Potential applications for the FELIX 3D display include imaging in the field so fair traffic control, medical imaging, computer aided design, science as well as entertainment.

Developing Mobile BIM/2D Barcode-Based Automated Facility Management System

PubMed Central

Chen, Yen-Pei

2014-01-01

Facility management (FM) has become an important topic in research on the operation and maintenance phase. Managing the work of FM effectively is extremely difficult owing to the variety of environments. One of the difficulties is the performance of two-dimensional (2D) graphics when depicting facilities. Building information modeling (BIM) uses precise geometry and relevant data to support the facilities depicted in three-dimensional (3D) object-oriented computer-aided design (CAD). This paper proposes a new and practical methodology with application to FM that uses an integrated 2D barcode and the BIM approach. Using 2D barcode and BIM technologies, this study proposes a mobile automated BIM-based facility management (BIMFM) system for FM staff in the operation and maintenance phase. The mobile automated BIMFM system is then applied in a selected case study of a commercial building project in Taiwan to verify the proposed methodology and demonstrate its effectiveness in FM practice. The combined results demonstrate that a BIMFM-like system can be an effective mobile automated FM tool. The advantage of the mobile automated BIMFM system lies not only in improving FM work efficiency for the FM staff but also in facilitating FM updates and transfers in the BIM environment. PMID:25250373

Developing mobile BIM/2D barcode-based automated facility management system.

PubMed

Lin, Yu-Cheng; Su, Yu-Chih; Chen, Yen-Pei

2014-01-01

Facility management (FM) has become an important topic in research on the operation and maintenance phase. Managing the work of FM effectively is extremely difficult owing to the variety of environments. One of the difficulties is the performance of two-dimensional (2D) graphics when depicting facilities. Building information modeling (BIM) uses precise geometry and relevant data to support the facilities depicted in three-dimensional (3D) object-oriented computer-aided design (CAD). This paper proposes a new and practical methodology with application to FM that uses an integrated 2D barcode and the BIM approach. Using 2D barcode and BIM technologies, this study proposes a mobile automated BIM-based facility management (BIMFM) system for FM staff in the operation and maintenance phase. The mobile automated BIMFM system is then applied in a selected case study of a commercial building project in Taiwan to verify the proposed methodology and demonstrate its effectiveness in FM practice. The combined results demonstrate that a BIMFM-like system can be an effective mobile automated FM tool. The advantage of the mobile automated BIMFM system lies not only in improving FM work efficiency for the FM staff but also in facilitating FM updates and transfers in the BIM environment.

3-D Voxel FEM Simulation of Seismic Wave Propagation in a Land-Sea Structure with Topography

NASA Astrophysics Data System (ADS)

Ikegami, Y.; Koketsu, K.

2003-12-01

We have already developed the voxel FEM (finite element method) code to simulate seismic wave propagation in a land structure with surface topography (Koketsu, Fujiwara and Ikegami, 2003). Although the conventional FEM often requires much larger memory, longer computation time and farther complicated mesh generation than the Finite Difference Method (FDM), this code consumes a similar amount of memory to FDM and spends only 1.4 times longer computation time thanks to the simplicity of voxels (hexahedron elements). The voxel FEM was successfully applied to inland earthquakes, but most earthquakes in a subduction zone occur beneath a sea, so that a simulation in a land-sea structure should be essential for waveform modeling and strong motion prediction there. We now introduce a domain of fluid elements into the model and formulate displacements in the elements using the Lagrange method. Sea-bottom motions are simulated for the simple land-sea models of Okamoto and Takenaka (1999). The simulation results agree well with their reflectivity and FDM seismograms. In order to enhance numerical stability, not only a variable mesh but also an adaptive time step is introduced. We can now choose the optimal time steps everywhere in the model based the Courant condition. This doubly variable formulation may result in inefficient parallel computing. The wave velocity in a shallow part is lower than that in a deeper part. Therefore, if the model is divided into horizontal slices and they are assigned to CPUs, a shallow slice will consist of only small elements. This can cause unbalanced loads on the CPUs. Accordingly, the model is divided into vertical slices in this study. They also reduce inter-processor communication, because a vertical cross section is usually smaller than a horizontal one. In addition, we will consider higher-order FEM formulation compatible to the fourth-order FDM. We will also present numerical examples to demonstrate the effects of a sea and surface

Automated full-3D digitization system for documentation of paintings

NASA Astrophysics Data System (ADS)

Karaszewski, Maciej; Adamczyk, Marcin; Sitnik, Robert; Michoński, Jakub; Załuski, Wojciech; Bunsch, Eryk; Bolewicki, Paweł

2013-05-01

In this paper, a fully automated 3D digitization system for documentation of paintings is presented. It consists of a specially designed frame system for secure fixing of painting, a custom designed, structured light-based, high-resolution measurement head with no IR and UV emission. This device is automatically positioned in two axes (parallel to the surface of digitized painting) with additional manual positioning in third, perpendicular axis. Manual change of observation angle is also possible around two axes to re-measure even partially shadowed areas. The whole system is built in a way which provides full protection of digitized object (moving elements cannot reach its vicinity) and is driven by computer-controlled, highly precise servomechanisms. It can be used for automatic (without any user attention) and fast measurement of the paintings with some limitation to their properties: maximum size of the picture is 2000mm x 2000mm (with deviation of flatness smaller than 20mm) Measurement head is automatically calibrated by the system and its possible working volume starts from 50mm x 50mm x 20mm (10000 points per square mm) and ends at 120mm x 80mm x 60mm (2500 points per square mm). The directional measurements obtained with this system are automatically initially aligned due to the measurement head's position coordinates known from servomechanisms. After the whole painting is digitized, the measurements are fine-aligned with color-based ICP algorithm to remove any influence of possible inaccuracy of positioning devices. We present exemplary digitization results along with the discussion about the opportunities of analysis which appear for such high-resolution, 3D computer models of paintings.

3D analysis of semiconductor devices: A combination of 3D imaging and 3D elemental analysis

NASA Astrophysics Data System (ADS)

Fu, Bianzhu; Gribelyuk, Michael A.

2018-04-01

3D analysis of semiconductor devices using a combination of scanning transmission electron microscopy (STEM) Z-contrast tomography and energy dispersive spectroscopy (EDS) elemental tomography is presented. 3D STEM Z-contrast tomography is useful in revealing the depth information of the sample. However, it suffers from contrast problems between materials with similar atomic numbers. Examples of EDS elemental tomography are presented using an automated EDS tomography system with batch data processing, which greatly reduces the data collection and processing time. 3D EDS elemental tomography reveals more in-depth information about the defect origin in semiconductor failure analysis. The influence of detector shadowing and X-rays absorption on the EDS tomography's result is also discussed.

Finding lesion correspondences in different views of automated 3D breast ultrasound

NASA Astrophysics Data System (ADS)

Tan, Tao; Platel, Bram; Hicks, Michael; Mann, Ritse M.; Karssemeijer, Nico

2013-02-01

Screening with automated 3D breast ultrasound (ABUS) is gaining popularity. However, the acquisition of multiple views required to cover an entire breast makes radiologic reading time-consuming. Linking lesions across views can facilitate the reading process. In this paper, we propose a method to automatically predict the position of a lesion in the target ABUS views, given the location of the lesion in a source ABUS view. We combine features describing the lesion location with respect to the nipple, the transducer and the chestwall, with features describing lesion properties such as intensity, spiculation, blobness, contrast and lesion likelihood. By using a grid search strategy, the location of the lesion was predicted in the target view. Our method achieved an error of 15.64 mm+/-16.13 mm. The error is small enough to help locate the lesion with minor additional interaction.

An automated design and fabrication pipeline for improving the strength of 3D printed artifacts under tensile loading

NASA Astrophysics Data System (ADS)

Al, Can Mert; Yaman, Ulas

2018-05-01

In the scope of this study, an alternative automated method to the conventional design and fabrication pipeline of 3D printers is developed by using an integrated CAD/CAE/CAM approach. It increases the load carrying capacity of the parts by constructing heterogeneous infill structures. Traditional CAM software of Additive Manufacturing machinery starts with a design model in STL file format which only includes data about the outer boundary in the triangular mesh form. Depending on the given infill percentage, the algorithm running behind constructs the interior of the artifact by using homogeneous infill structures. As opposed to the current CAM software, the proposed method provides a way to construct heterogeneous infill structures with respect to the Von Misses stress field results obtained from a finite element analysis. Throughout the work, Rhinoceros3D is used for the design of the parts along with Grasshopper3D, an algorithmic design tool for Rhinoceros3D. In addition, finite element analyses are performed using Karamba3D, a plug-in for Grasshopper3D. According to the results of the tensile tests, the method offers an improvement of load carrying capacity about 50% compared to traditional slicing algorithms of 3D printing.

Automated bone segmentation from large field of view 3D MR images of the hip joint.

PubMed

Xia, Ying; Fripp, Jurgen; Chandra, Shekhar S; Schwarz, Raphael; Engstrom, Craig; Crozier, Stuart

2013-10-21

Accurate bone segmentation in the hip joint region from magnetic resonance (MR) images can provide quantitative data for examining pathoanatomical conditions such as femoroacetabular impingement through to varying stages of osteoarthritis to monitor bone and associated cartilage morphometry. We evaluate two state-of-the-art methods (multi-atlas and active shape model (ASM) approaches) on bilateral MR images for automatic 3D bone segmentation in the hip region (proximal femur and innominate bone). Bilateral MR images of the hip joints were acquired at 3T from 30 volunteers. Image sequences included water-excitation dual echo stead state (FOV 38.6 × 24.1 cm, matrix 576 × 360, thickness 0.61 mm) in all subjects and multi-echo data image combination (FOV 37.6 × 23.5 cm, matrix 576 × 360, thickness 0.70 mm) for a subset of eight subjects. Following manual segmentation of femoral (head-neck, proximal-shaft) and innominate (ilium+ischium+pubis) bone, automated bone segmentation proceeded via two approaches: (1) multi-atlas segmentation incorporating non-rigid registration and (2) an advanced ASM-based scheme. Mean inter- and intra-rater reliability Dice's similarity coefficients (DSC) for manual segmentation of femoral and innominate bone were (0.970, 0.963) and (0.971, 0.965). Compared with manual data, mean DSC values for femoral and innominate bone volumes using automated multi-atlas and ASM-based methods were (0.950, 0.922) and (0.946, 0.917), respectively. Both approaches delivered accurate (high DSC values) segmentation results; notably, ASM data were generated in substantially less computational time (12 min versus 10 h). Both automated algorithms provided accurate 3D bone volumetric descriptions for MR-based measures in the hip region. The highly computational efficient ASM-based approach is more likely suitable for future clinical applications such as extracting bone-cartilage interfaces for potential cartilage segmentation.

Comparing the Effect of Different Voxel Resolutions for Assessment of Vertical Root Fracture of Permanent Teeth

PubMed Central

Uzun, Ismail; Gunduz, Kaan; Celenk, Peruze; Avsever, Hakan; Orhan, Kaan; Canitezer, Gozde; Ozmen, Bilal; Cicek, Ersan; Egrioglu, Erol

2015-01-01

Background: The teeth with undiagnosed vertical root fractures (VRFs) are likely to receive endodontic treatment or retreatment, leading to frustration and inappropriate endodontic therapies. Moreover, many cases of VRFs cannot be diagnosed definitively until the extraction of tooth. Objectives: This study aimed to assess the use of different voxel resolutions of two different cone beam computerized tomography (CBCT) units in the detection VRFs in vitro. Materials and Methods: The study material comprised 74 extracted human mandibular single rooted premolar teeth without root fractures that had not undergone any root-canal treatment. Images were obtained by two different CBCT units. Four image sets were obtained as follows: 1) 3D Accuitomo 170, 4 × 4 cm field of view (FOV) (0.080 mm3); 2) 3D Accuitomo 170. 6 × 6 cm FOV (0.125 mm3); 3) NewTom 3G, 6˝ (0.16 mm3) and 4) NewTom 3G, 9˝ FOV (0.25 mm3). Kappa coefficients were calculated to assess both intra- and inter-observer agreements for each image set. Results: No significant differences were found among observers or voxel sizes, with high average Z (Az) results being reported for all groups. Both intra- and inter-observer agreement values were relatively better for 3D Accuitomo 170 images than the images from NewTom 3G. The highest Az and kappa values were obtained with 3D Accuitomo 170, 4 × 4 cm FOV (0.080 mm3) images. Conclusion: No significant differences were found among observers or voxel sizes, with high Az results reported for all groups. PMID:26557279

An efficient and accurate 3D displacements tracking strategy for digital volume correlation

NASA Astrophysics Data System (ADS)

Pan, Bing; Wang, Bo; Wu, Dafang; Lubineau, Gilles

2014-07-01

Owing to its inherent computational complexity, practical implementation of digital volume correlation (DVC) for internal displacement and strain mapping faces important challenges in improving its computational efficiency. In this work, an efficient and accurate 3D displacement tracking strategy is proposed for fast DVC calculation. The efficiency advantage is achieved by using three improvements. First, to eliminate the need of updating Hessian matrix in each iteration, an efficient 3D inverse compositional Gauss-Newton (3D IC-GN) algorithm is introduced to replace existing forward additive algorithms for accurate sub-voxel displacement registration. Second, to ensure the 3D IC-GN algorithm that converges accurately and rapidly and avoid time-consuming integer-voxel displacement searching, a generalized reliability-guided displacement tracking strategy is designed to transfer accurate and complete initial guess of deformation for each calculation point from its computed neighbors. Third, to avoid the repeated computation of sub-voxel intensity interpolation coefficients, an interpolation coefficient lookup table is established for tricubic interpolation. The computational complexity of the proposed fast DVC and the existing typical DVC algorithms are first analyzed quantitatively according to necessary arithmetic operations. Then, numerical tests are performed to verify the performance of the fast DVC algorithm in terms of measurement accuracy and computational efficiency. The experimental results indicate that, compared with the existing DVC algorithm, the presented fast DVC algorithm produces similar precision and slightly higher accuracy at a substantially reduced computational cost.

Automation of Hessian-Based Tubularity Measure Response Function in 3D Biomedical Images.

PubMed

Dzyubak, Oleksandr P; Ritman, Erik L

2011-01-01

The blood vessels and nerve trees consist of tubular objects interconnected into a complex tree- or web-like structure that has a range of structural scale 5 μm diameter capillaries to 3 cm aorta. This large-scale range presents two major problems; one is just making the measurements, and the other is the exponential increase of component numbers with decreasing scale. With the remarkable increase in the volume imaged by, and resolution of, modern day 3D imagers, it is almost impossible to make manual tracking of the complex multiscale parameters from those large image data sets. In addition, the manual tracking is quite subjective and unreliable. We propose a solution for automation of an adaptive nonsupervised system for tracking tubular objects based on multiscale framework and use of Hessian-based object shape detector incorporating National Library of Medicine Insight Segmentation and Registration Toolkit (ITK) image processing libraries.

From SFM to 3d Print: Automated Workflow Addressed to Practitioner Aimed at the Conservation and Restauration

NASA Astrophysics Data System (ADS)

Inzerillo, L.; Di Paola, F.

2017-08-01

In In the last years there has been an increasing use of digital techniques for conservation and restoration purposes. Among these, a very dominant rule is played by the use of digital photogrammetry packages (Agisoft Photoscan, 3D Zephir) which allow to obtain in few steps 3D textured models of real objects. Combined with digital documentation technologies digital fabrication technologies can be employed in a variety of ways to assist in heritage documentation, conservation and dissemination. This paper will give to practitioners an overview on the state of the art available technologies and a feasible workflow for optimizing point cloud and polygon mesh datasets for the purpose of fabrication using 3D printing. The goal is to give an important contribute to confer an automation aspect at the whole processing. We tried to individuate a workflow that should be applicable to several types of cases apart from small precautions. In our experimentation we used a DELTA WASP 2040 printer with PLA easyfil.

A 3D contact analysis approach for the visualization of the electrical contact asperities

DOE Office of Scientific and Technical Information (OSTI.GOV)

Roussos, Constantinos C.; Swingler, Jonathan

The electrical contact is an important phenomenon that should be given into consideration to achieve better performance and long term reliability for the design of devices. Based upon this importance, the electrical contact interface has been visualized as a “3D Contact Map” and used in order to investigate the contact asperities. The contact asperities describe the structures above and below the contact spots (the contact spots define the 3D contact map) to the two conductors which make the contact system. The contact asperities require the discretization of the 3D microstructures of the contact system into voxels. A contact analysis approachmore » has been developed and introduced in this paper which shows the way to the 3D visualization of the contact asperities of a given contact system. For the discretization of 3D microstructure of contact system into voxels, X-ray Computed Tomography (CT) method is used in order to collect the data of a 250 V, 16 A rated AC single pole rocker switch which is used as a contact system for investigation.« less

A 3D contact analysis approach for the visualization of the electrical contact asperities

PubMed Central

Swingler, Jonathan

2017-01-01

The electrical contact is an important phenomenon that should be given into consideration to achieve better performance and long term reliability for the design of devices. Based upon this importance, the electrical contact interface has been visualized as a ‘‘3D Contact Map’’ and used in order to investigate the contact asperities. The contact asperities describe the structures above and below the contact spots (the contact spots define the 3D contact map) to the two conductors which make the contact system. The contact asperities require the discretization of the 3D microstructures of the contact system into voxels. A contact analysis approach has been developed and introduced in this paper which shows the way to the 3D visualization of the contact asperities of a given contact system. For the discretization of 3D microstructure of contact system into voxels, X-ray Computed Tomography (CT) method is used in order to collect the data of a 250 V, 16 A rated AC single pole rocker switch which is used as a contact system for investigation. PMID:28105383

A 3D contact analysis approach for the visualization of the electrical contact asperities

DOE PAGES

Roussos, Constantinos C.; Swingler, Jonathan

2017-01-11

The electrical contact is an important phenomenon that should be given into consideration to achieve better performance and long term reliability for the design of devices. Based upon this importance, the electrical contact interface has been visualized as a “3D Contact Map” and used in order to investigate the contact asperities. The contact asperities describe the structures above and below the contact spots (the contact spots define the 3D contact map) to the two conductors which make the contact system. The contact asperities require the discretization of the 3D microstructures of the contact system into voxels. A contact analysis approachmore » has been developed and introduced in this paper which shows the way to the 3D visualization of the contact asperities of a given contact system. For the discretization of 3D microstructure of contact system into voxels, X-ray Computed Tomography (CT) method is used in order to collect the data of a 250 V, 16 A rated AC single pole rocker switch which is used as a contact system for investigation.« less

A semi-automated algorithm for hypothalamus volumetry in 3 Tesla magnetic resonance images.

PubMed

Wolff, Julia; Schindler, Stephanie; Lucas, Christian; Binninger, Anne-Sophie; Weinrich, Luise; Schreiber, Jan; Hegerl, Ulrich; Möller, Harald E; Leitzke, Marco; Geyer, Stefan; Schönknecht, Peter

2018-07-30

The hypothalamus, a small diencephalic gray matter structure, is part of the limbic system. Volumetric changes of this structure occur in psychiatric diseases, therefore there is increasing interest in precise volumetry. Based on our detailed volumetry algorithm for 7 Tesla magnetic resonance imaging (MRI), we developed a method for 3 Tesla MRI, adopting anatomical landmarks and work in triplanar view. We overlaid T1-weighted MR images with gray matter-tissue probability maps to combine anatomical information with tissue class segmentation. Then, we outlined regions of interest (ROIs) that covered potential hypothalamus voxels. Within these ROIs, seed growing technique helped define the hypothalamic volume using gray matter probabilities from the tissue probability maps. This yielded a semi-automated method with short processing times of 20-40 min per hypothalamus. In the MRIs of ten subjects, reliabilities were determined as intraclass correlations (ICC) and volume overlaps in percent. Three raters achieved very good intra-rater reliabilities (ICC 0.82-0.97) and good inter-rater reliabilities (ICC 0.78 and 0.82). Overlaps of intra- and inter-rater runs were very good (≥ 89.7%). We present a fast, semi-automated method for in vivo hypothalamus volumetry in 3 Tesla MRI. Copyright © 2018 Elsevier B.V. All rights reserved.

Two-Voxel Localization Sequence for in Vivo Two-Dimensional Homonuclear Correlation Spectroscopy

NASA Astrophysics Data System (ADS)

Delmas, Florence; Beloeil, Jean-Claude; van der Sanden, Boudewijn P. J.; Nicolay, Klaas; Gillet, Brigitte

2001-03-01

The combination of localized 2D 1H MR correlation spectroscopy and Hadamard encoding allows the simultaneous acquisition of multiple volumes of interest without an increase in the experimental duration, compared to single-voxel acquisition. In the present study, 2D correlation spectra were acquired simultaneously within 20 to 40 min in two voxels located in each hemisphere of the rat brain. An intervoxel distance of 20% of the voxel size was sufficient to limit spatial contamination. The following cerebral metabolites gave detectable crosspeaks: N-acetylaspartate, the glutamate/glutamine pool, aspartate, phosphoethanolamine, glucose, glutathione, taurine, myo-inositols, lactate, threonine, γ-aminobutyric acid, and alanine. Most of the metabolites were measured without contamination of other resonances.

Segmentation of malignant lesions in 3D breast ultrasound using a depth-dependent model.

PubMed

Tan, Tao; Gubern-Mérida, Albert; Borelli, Cristina; Manniesing, Rashindra; van Zelst, Jan; Wang, Lei; Zhang, Wei; Platel, Bram; Mann, Ritse M; Karssemeijer, Nico

2016-07-01

Automated 3D breast ultrasound (ABUS) has been proposed as a complementary screening modality to mammography for early detection of breast cancers. To facilitate the interpretation of ABUS images, automated diagnosis and detection techniques are being developed, in which malignant lesion segmentation plays an important role. However, automated segmentation of cancer in ABUS is challenging since lesion edges might not be well defined. In this study, the authors aim at developing an automated segmentation method for malignant lesions in ABUS that is robust to ill-defined cancer edges and posterior shadowing. A segmentation method using depth-guided dynamic programming based on spiral scanning is proposed. The method automatically adjusts aggressiveness of the segmentation according to the position of the voxels relative to the lesion center. Segmentation is more aggressive in the upper part of the lesion (close to the transducer) than at the bottom (far away from the transducer), where posterior shadowing is usually visible. The authors used Dice similarity coefficient (Dice) for evaluation. The proposed method is compared to existing state of the art approaches such as graph cut, level set, and smart opening and an existing dynamic programming method without depth dependence. In a dataset of 78 cancers, our proposed segmentation method achieved a mean Dice of 0.73 ± 0.14. The method outperforms an existing dynamic programming method (0.70 ± 0.16) on this task (p = 0.03) and it is also significantly (p < 0.001) better than graph cut (0.66 ± 0.18), level set based approach (0.63 ± 0.20) and smart opening (0.65 ± 0.12). The proposed depth-guided dynamic programming method achieves accurate breast malignant lesion segmentation results in automated breast ultrasound.

Detection of infarct lesions from single MRI modality using inconsistency between voxel intensity and spatial location--a 3-D automatic approach.

PubMed

Shen, Shan; Szameitat, André J; Sterr, Annette

2008-07-01

Detection of infarct lesions using traditional segmentation methods is always problematic due to intensity similarity between lesions and normal tissues, so that multispectral MRI modalities were often employed for this purpose. However, the high costs of MRI scan and the severity of patient conditions restrict the collection of multiple images. Therefore, in this paper, a new 3-D automatic lesion detection approach was proposed, which required only a single type of anatomical MRI scan. It was developed on a theory that, when lesions were present, the voxel-intensity-based segmentation and the spatial-location-based tissue distribution should be inconsistent in the regions of lesions. The degree of this inconsistency was calculated, which indicated the likelihood of tissue abnormality. Lesions were identified when the inconsistency exceeded a defined threshold. In this approach, the intensity-based segmentation was implemented by the conventional fuzzy c-mean (FCM) algorithm, while the spatial location of tissues was provided by prior tissue probability maps. The use of simulated MRI lesions allowed us to quantitatively evaluate the performance of the proposed method, as the size and location of lesions were prespecified. The results showed that our method effectively detected lesions with 40-80% signal reduction compared to normal tissues (similarity index > 0.7). The capability of the proposed method in practice was also demonstrated on real infarct lesions from 15 stroke patients, where the lesions detected were in broad agreement with true lesions. Furthermore, a comparison to a statistical segmentation approach presented in the literature suggested that our 3-D lesion detection approach was more reliable. Future work will focus on adapting the current method to multiple sclerosis lesion detection.

Comparison of internal dose estimates obtained using organ-level, voxel S value, and Monte Carlo techniques

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grimes, Joshua, E-mail: grimes.joshua@mayo.edu; Celler, Anna

2014-09-15

(D90) agreeing within ±3%, on average. Conclusions: Several aspects of OLINDA/EXM dose calculation were compared with patient-specific dose estimates obtained using Monte Carlo. Differences in patient anatomy led to large differences in cross-organ doses. However, total organ doses were still in good agreement since most of the deposited dose is due to self-irradiation. Comparison of voxelized doses calculated by Monte Carlo and the voxel S value technique showed that the 3D dose distributions produced by the respective methods are nearly identical.« less

CEREBRA: a 3-D visualization tool for brain network extracted from fMRI data.

PubMed

Nasir, Baris; Yarman Vural, Fatos T

2016-08-01

In this paper, we introduce a new tool, CEREBRA, to visualize the 3D network of human brain, extracted from the fMRI data. The tool aims to analyze the brain connectivity by representing the selected voxels as the nodes of the network. The edge weights among the voxels are estimated by considering the relationships among the voxel time series. The tool enables the researchers to observe the active brain regions and the interactions among them by using graph theoretic measures, such as, the edge weight and node degree distributions. CEREBRA provides an interactive interface with basic display and editing options for the researchers to study their hypotheses about the connectivity of the brain network. CEREBRA interactively simplifies the network by selecting the active voxels and the most correlated edge weights. The researchers may remove the voxels and edges by using local and global thresholds selected on the window. The built-in graph reduction algorithms are then eliminate the irrelevant regions, voxels and edges and display various properties of the network. The toolbox is capable of space-time representation of the voxel time series and estimated arc weights by using the animated heat maps.

Sodium 3D COncentration MApping (COMA 3D) using 23Na and proton MRI

NASA Astrophysics Data System (ADS)

Truong, Milton L.; Harrington, Michael G.; Schepkin, Victor D.; Chekmenev, Eduard Y.

2014-10-01

Functional changes of sodium 3D MRI signals were converted into millimolar concentration changes using an open-source fully automated MATLAB toolbox. These concentration changes are visualized via 3D sodium concentration maps, and they are overlaid over conventional 3D proton images to provide high-resolution co-registration for easy correlation of functional changes to anatomical regions. Nearly 5000/h concentration maps were generated on a personal computer (ca. 2012) using 21.1 T 3D sodium MRI brain images of live rats with spatial resolution of 0.8 × 0.8 × 0.8 mm3 and imaging matrices of 60 × 60 × 60. The produced concentration maps allowed for non-invasive quantitative measurement of in vivo sodium concentration in the normal rat brain as a functional response to migraine-like conditions. The presented work can also be applied to sodium-associated changes in migraine, cancer, and other metabolic abnormalities that can be sensed by molecular imaging. The MATLAB toolbox allows for automated image analysis of the 3D images acquired on the Bruker platform and can be extended to other imaging platforms. The resulting images are presented in a form of series of 2D slices in all three dimensions in native MATLAB and PDF formats. The following is provided: (a) MATLAB source code for image processing, (b) the detailed processing procedures, (c) description of the code and all sub-routines, (d) example data sets of initial and processed data. The toolbox can be downloaded at: http://www.vuiis.vanderbilt.edu/ truongm/COMA3D/.

- and Graph-Based Point Cloud Segmentation of 3d Scenes Using Perceptual Grouping Laws

NASA Astrophysics Data System (ADS)

Xu, Y.; Hoegner, L.; Tuttas, S.; Stilla, U.

2017-05-01

Segmentation is the fundamental step for recognizing and extracting objects from point clouds of 3D scene. In this paper, we present a strategy for point cloud segmentation using voxel structure and graph-based clustering with perceptual grouping laws, which allows a learning-free and completely automatic but parametric solution for segmenting 3D point cloud. To speak precisely, two segmentation methods utilizing voxel and supervoxel structures are reported and tested. The voxel-based data structure can increase efficiency and robustness of the segmentation process, suppressing the negative effect of noise, outliers, and uneven points densities. The clustering of voxels and supervoxel is carried out using graph theory on the basis of the local contextual information, which commonly conducted utilizing merely pairwise information in conventional clustering algorithms. By the use of perceptual laws, our method conducts the segmentation in a pure geometric way avoiding the use of RGB color and intensity information, so that it can be applied to more general applications. Experiments using different datasets have demonstrated that our proposed methods can achieve good results, especially for complex scenes and nonplanar surfaces of objects. Quantitative comparisons between our methods and other representative segmentation methods also confirms the effectiveness and efficiency of our proposals.

Estimation of urinary stone composition by automated processing of CT images.

PubMed

Chevreau, Grégoire; Troccaz, Jocelyne; Conort, Pierre; Renard-Penna, Raphaëlle; Mallet, Alain; Daudon, Michel; Mozer, Pierre

2009-10-01

The objective of this article was developing an automated tool for routine clinical practice to estimate urinary stone composition from CT images based on the density of all constituent voxels. A total of 118 stones for which the composition had been determined by infrared spectroscopy were placed in a helical CT scanner. A standard acquisition, low-dose and high-dose acquisitions were performed. All voxels constituting each stone were automatically selected. A dissimilarity index evaluating variations of density around each voxel was created in order to minimize partial volume effects: stone composition was established on the basis of voxel density of homogeneous zones. Stone composition was determined in 52% of cases. Sensitivities for each compound were: uric acid: 65%, struvite: 19%, cystine: 78%, carbapatite: 33.5%, calcium oxalate dihydrate: 57%, calcium oxalate monohydrate: 66.5%, brushite: 75%. Low-dose acquisition did not lower the performances (P < 0.05). This entirely automated approach eliminates manual intervention on the images by the radiologist while providing identical performances including for low-dose protocols.

Striatal D(2)/D(3) receptor availability is inversely correlated with cannabis consumption in chronic marijuana users.

PubMed

Albrecht, Daniel S; Skosnik, Patrick D; Vollmer, Jennifer M; Brumbaugh, Margaret S; Perry, Kevin M; Mock, Bruce H; Zheng, Qi-Huang; Federici, Lauren A; Patton, Elizabeth A; Herring, Christine M; Yoder, Karmen K

2013-02-01

Although the incidence of cannabis abuse/dependence in Americans is rising, the neurobiology of cannabis addiction is not well understood. Imaging studies have demonstrated deficits in striatal D(2)/D(3) receptor availability in several substance-dependent populations. However, this has not been studied in currently using chronic cannabis users. The purpose of this study was to compare striatal D(2)/D(3) receptor availability between currently using chronic cannabis users and healthy controls. Eighteen right-handed males age 18-34 were studied. Ten subjects were chronic cannabis users; eight were demographically matched controls. Subjects underwent a [(11)C]raclopride (RAC) PET scan. Striatal RAC binding potential (BP(ND)) was calculated on a voxel-wise basis. Prior to scanning, urine samples were obtained from cannabis users for quantification of urine Δ-9-tetrahydrocannabinol (THC) and THC metabolites (11-nor-Δ-9-THC-9-carboxylic acid; THC-COOH and 11-hydroxy-THC;OH-THC). There were no differences in D(2)/D(3) receptor availability between cannabis users and controls. Voxel-wise analyses revealed that RAC BP(ND) values were negatively associated with both urine levels of cannabis metabolites and self-report of recent cannabis consumption. In this sample, current cannabis use was not associated with deficits in striatal D(2)/D(3) receptor availability. There was an inverse relationship between chronic cannabis use and striatal RAC BP(ND). Additional studies are needed to identify the neurochemical consequences of chronic cannabis use on the dopamine system. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Automation and validation of micronucleus detection in the 3D EpiDerm™ human reconstructed skin assay and correlation with 2D dose responses.

PubMed

Chapman, K E; Thomas, A D; Wills, J W; Pfuhler, S; Doak, S H; Jenkins, G J S

2014-05-01

Recent restrictions on the testing of cosmetic ingredients in animals have resulted in the need to test the genotoxic potential of chemicals exclusively in vitro prior to licensing. However, as current in vitro tests produce some misleading positive results, sole reliance on such tests could prevent some chemicals with safe or beneficial exposure levels from being marketed. The 3D human reconstructed skin micronucleus (RSMN) assay is a promising new in vitro approach designed to assess genotoxicity of dermally applied compounds. The assay utilises a highly differentiated in vitro model of the human epidermis. For the first time, we have applied automated micronucleus detection to this assay using MetaSystems Metafer Slide Scanning Platform (Metafer), demonstrating concordance with manual scoring. The RSMN assay's fixation protocol was found to be compatible with the Metafer, providing a considerably shorter alternative to the recommended Metafer protocol. Lowest observed genotoxic effect levels (LOGELs) were observed for mitomycin-C at 4.8 µg/ml and methyl methanesulfonate (MMS) at 1750 µg/ml when applied topically to the skin surface. In-medium dosing with MMS produced a LOGEL of 20 µg/ml, which was very similar to the topical LOGEL when considering the total mass of MMS added. Comparisons between 3D medium and 2D LOGELs resulted in a 7-fold difference in total mass of MMS applied to each system, suggesting a protective function of the 3D microarchitecture. Interestingly, hydrogen peroxide (H2O2), a positive clastogen in 2D systems, tested negative in this assay. A non-genotoxic carcinogen, methyl carbamate, produced negative results, as expected. We also demonstrated expression of the DNA repair protein N-methylpurine-DNA glycosylase in EpiDerm™. Our preliminary validation here demonstrates that the RSMN assay may be a valuable follow-up to the current in vitro test battery, and together with its automation, could contribute to minimising unnecessary in vivo

3D surface voxel tracing corrector for accurate bone segmentation.

PubMed

Guo, Haoyan; Song, Sicong; Wang, Jinke; Guo, Maozu; Cheng, Yuanzhi; Wang, Yadong; Tamura, Shinichi

2018-06-18

For extremely close bones, their boundaries are weak and diffused due to strong interaction between adjacent surfaces. These factors prevent the accurate segmentation of bone structure. To alleviate these difficulties, we propose an automatic method for accurate bone segmentation. The method is based on a consideration of the 3D surface normal direction, which is used to detect the bone boundary in 3D CT images. Our segmentation method is divided into three main stages. Firstly, we consider a surface tracing corrector combined with Gaussian standard deviation [Formula: see text] to improve the estimation of normal direction. Secondly, we determine an optimal value of [Formula: see text] for each surface point during this normal direction correction. Thirdly, we construct the 1D signal and refining the rough boundary along the corrected normal direction. The value of [Formula: see text] is used in the first directional derivative of the Gaussian to refine the location of the edge point along accurate normal direction. Because the normal direction is corrected and the value of [Formula: see text] is optimized, our method is robust to noise images and narrow joint space caused by joint degeneration. We applied our method to 15 wrists and 50 hip joints for evaluation. In the wrist segmentation, Dice overlap coefficient (DOC) of [Formula: see text]% was obtained by our method. In the hip segmentation, fivefold cross-validations were performed for two state-of-the-art methods. Forty hip joints were used for training in two state-of-the-art methods, 10 hip joints were used for testing and performing comparisons. The DOCs of [Formula: see text], [Formula: see text]%, and [Formula: see text]% were achieved by our method for the pelvis, the left femoral head and the right femoral head, respectively. Our method was shown to improve segmentation accuracy for several specific challenging cases. The results demonstrate that our approach achieved a superior accuracy over two

Voxel-Based Neighborhood for Spatial Shape Pattern Classification of Lidar Point Clouds with Supervised Learning

PubMed Central

Plaza-Leiva, Victoria; Gomez-Ruiz, Jose Antonio; Mandow, Anthony; García-Cerezo, Alfonso

2017-01-01

Improving the effectiveness of spatial shape features classification from 3D lidar data is very relevant because it is largely used as a fundamental step towards higher level scene understanding challenges of autonomous vehicles and terrestrial robots. In this sense, computing neighborhood for points in dense scans becomes a costly process for both training and classification. This paper proposes a new general framework for implementing and comparing different supervised learning classifiers with a simple voxel-based neighborhood computation where points in each non-overlapping voxel in a regular grid are assigned to the same class by considering features within a support region defined by the voxel itself. The contribution provides offline training and online classification procedures as well as five alternative feature vector definitions based on principal component analysis for scatter, tubular and planar shapes. Moreover, the feasibility of this approach is evaluated by implementing a neural network (NN) method previously proposed by the authors as well as three other supervised learning classifiers found in scene processing methods: support vector machines (SVM), Gaussian processes (GP), and Gaussian mixture models (GMM). A comparative performance analysis is presented using real point clouds from both natural and urban environments and two different 3D rangefinders (a tilting Hokuyo UTM-30LX and a Riegl). Classification performance metrics and processing time measurements confirm the benefits of the NN classifier and the feasibility of voxel-based neighborhood. PMID:28294963

Voxel-Based Neighborhood for Spatial Shape Pattern Classification of Lidar Point Clouds with Supervised Learning.

PubMed

Plaza-Leiva, Victoria; Gomez-Ruiz, Jose Antonio; Mandow, Anthony; García-Cerezo, Alfonso

2017-03-15

Improving the effectiveness of spatial shape features classification from 3D lidar data is very relevant because it is largely used as a fundamental step towards higher level scene understanding challenges of autonomous vehicles and terrestrial robots. In this sense, computing neighborhood for points in dense scans becomes a costly process for both training and classification. This paper proposes a new general framework for implementing and comparing different supervised learning classifiers with a simple voxel-based neighborhood computation where points in each non-overlapping voxel in a regular grid are assigned to the same class by considering features within a support region defined by the voxel itself. The contribution provides offline training and online classification procedures as well as five alternative feature vector definitions based on principal component analysis for scatter, tubular and planar shapes. Moreover, the feasibility of this approach is evaluated by implementing a neural network (NN) method previously proposed by the authors as well as three other supervised learning classifiers found in scene processing methods: support vector machines (SVM), Gaussian processes (GP), and Gaussian mixture models (GMM). A comparative performance analysis is presented using real point clouds from both natural and urban environments and two different 3D rangefinders (a tilting Hokuyo UTM-30LX and a Riegl). Classification performance metrics and processing time measurements confirm the benefits of the NN classifier and the feasibility of voxel-based neighborhood.

Multi-Scale Voxel Segmentation for Terrestrial Lidar Data within Marshes

NASA Astrophysics Data System (ADS)

Nguyen, C. T.; Starek, M. J.; Tissot, P.; Gibeaut, J. C.

2016-12-01

The resilience of marshes to a rising sea is dependent on their elevation response. Terrestrial laser scanning (TLS) is a detailed topographic approach for accurate, dense surface measurement with high potential for monitoring of marsh surface elevation response. The dense point cloud provides a 3D representation of the surface, which includes both terrain and non-terrain objects. Extraction of topographic information requires filtering of the data into like-groups or classes, therefore, methods must be incorporated to identify structure in the data prior to creation of an end product. A voxel representation of three-dimensional space provides quantitative visualization and analysis for pattern recognition. The objectives of this study are threefold: 1) apply a multi-scale voxel approach to effectively extract geometric features from the TLS point cloud data, 2) investigate the utility of K-means and Self Organizing Map (SOM) clustering algorithms for segmentation, and 3) utilize a variety of validity indices to measure the quality of the result. TLS data were collected at a marsh site along the central Texas Gulf Coast using a Riegl VZ 400 TLS. The site consists of both exposed and vegetated surface regions. To characterize structure of the point cloud, octree segmentation is applied to create a tree data structure of voxels containing the points. The flexibility of voxels in size and point density makes this algorithm a promising candidate to locally extract statistical and geometric features of the terrain including surface normal and curvature. The characteristics of the voxel itself such as the volume and point density are also computed and assigned to each point as are laser pulse characteristics. The features extracted from the voxelization are then used as input for clustering of the points using the K-means and SOM clustering algorithms. Optimal number of clusters are then determined based on evaluation of cluster separability criterions. Results for

[Gray matter abnormalities in developmental stuttering determined with voxel-based morphometry].

PubMed

Song, Lu-ping; Peng, Dan-ling; Jin, Zhen; Yao, Li; Ning, Ning; Guo, Xiao-juan; Zhang, Tong

2007-11-06

To investigate the differences of regional grey matter volume between adults with persistent developmental stuttering and fluent speaking adults, and to determine whether stutterers have anomalous anatomy of speech-relevant brain areas that possibly affect speech fluency. High-resolution magnetic resonance imaging (MRI) scanning was performed on 10 adults with developmental stuttering, aged 26 (21 - 35) with the onset age of 4 (3 - 7) and 12 age, sex, hand preference, and education-matched controls. The customized brain templates were created in order to improve spatial normalization and segmentation. Then automated preprocessing of MRI data was conducted using an optimized version of VBM, a fully automated unbiased and objective whole-brain MRI analysis technique. VBM analysis revealed that compared with the controls, the stuttering adults had significant clusters of locally gray matter volume increased in the superior temporal, middle temporal, precentral and postcentral gyrus, and inferior parietal lobule of the bilateral hemisphere (P < 0.001), the numbers of increased gray matter volume in the right and left hemispheres were 60,247 and 48,782 voxels respectively. The, Grey matter decrease was shown with an overall decreased gray matter volume of 32 394 voxels, mainly in the bilateral cerebella posterior lobe and dorsal part of medulla, especially inferior semi-lunar lobule, followed by cerebellar tonsil and bilateral medulla in comparison with the controls (P < 0.001). The reduction of the regional gray matter volume of bilateral cerebella and medulla is related to the neural mechanism of the controlling disorder of speech production and may be the essential cause of stuttering. Some areas with increased gray matter volume in temporal lobe, parietal lobe, and frontal lobe, may be the result of long term functional compensation for the cerebella and medulla function deficiency.

Making data matter: Voxel printing for the digital fabrication of data across scales and domains.

PubMed

Bader, Christoph; Kolb, Dominik; Weaver, James C; Sharma, Sunanda; Hosny, Ahmed; Costa, João; Oxman, Neri

2018-05-01

We present a multimaterial voxel-printing method that enables the physical visualization of data sets commonly associated with scientific imaging. Leveraging voxel-based control of multimaterial three-dimensional (3D) printing, our method enables additive manufacturing of discontinuous data types such as point cloud data, curve and graph data, image-based data, and volumetric data. By converting data sets into dithered material deposition descriptions, through modifications to rasterization processes, we demonstrate that data sets frequently visualized on screen can be converted into physical, materially heterogeneous objects. Our approach alleviates the need to postprocess data sets to boundary representations, preventing alteration of data and loss of information in the produced physicalizations. Therefore, it bridges the gap between digital information representation and physical material composition. We evaluate the visual characteristics and features of our method, assess its relevance and applicability in the production of physical visualizations, and detail the conversion of data sets for multimaterial 3D printing. We conclude with exemplary 3D-printed data sets produced by our method pointing toward potential applications across scales, disciplines, and problem domains.

Patient Scenarios Illustrating Benefits of Automation in DoD Medical Treatment Facilities.

DTIC Science & Technology

1981-10-23

d-ntif by block nmber) This report outlines the difference that automation may make in patient encounters within the military health care system. Two...automation may make in patient encounters with the military health care system, as part of a task to characterize the benefit set of automation in...FI-RI4 323 PATIENT SCENARIOS ILLUSTRATING BENEFITS OF AUTOM ATION 1/1 IDOD MEDICAL TREATMENT FACILITIES(U) LITTLE (ARTHUR D) INC CAMBRIDGE MR

Open-Source 3-D Platform for Low-Cost Scientific Instrument Ecosystem.

PubMed

Zhang, C; Wijnen, B; Pearce, J M

2016-08-01

The combination of open-source software and hardware provides technically feasible methods to create low-cost, highly customized scientific research equipment. Open-source 3-D printers have proven useful for fabricating scientific tools. Here the capabilities of an open-source 3-D printer are expanded to become a highly flexible scientific platform. An automated low-cost 3-D motion control platform is presented that has the capacity to perform scientific applications, including (1) 3-D printing of scientific hardware; (2) laboratory auto-stirring, measuring, and probing; (3) automated fluid handling; and (4) shaking and mixing. The open-source 3-D platform not only facilities routine research while radically reducing the cost, but also inspires the creation of a diverse array of custom instruments that can be shared and replicated digitally throughout the world to drive down the cost of research and education further. © 2016 Society for Laboratory Automation and Screening.

Breast mass characterization using 3D automated ultrasound as an adjunct to digital breast tomosynthesis: A pilot study

PubMed Central

Padilla, Frederic; Roubidoux, Marilyn A.; Paramagul, Chintana; Sinha, Sumedha P.; Goodsitt, Mitchell M.; Le Carpentier, Gerald L.; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Fowlkes, Brian J.; Joe, Annette D.; Klein, Katherine A.; Nees, Alexis V.; Noroozian, Mitra; Patterson, Stephanie K.; Pinsky, Renee W.; Hooi, Fong Ming; Carson, Paul L.

2013-01-01

Objective To retrospectively evaluate the effect of 3D automated ultrasound (3D-AUS) as an adjunct to digital breast tomosynthesis (DBT) on radiologists’ performance and confidence in discriminating malignant and benign breast masses. Methods Two-view DBT (CC and MLO or Lateral) and single-view 3D-AUS were acquired on 51 patients with (subsequently) biopsy-proven masses (13 malignant, 38 benign). Six experienced radiologists rated, on a 13-point scale, the likelihood of malignancy of an identified mass, first by reading the DBT alone, followed immediately by reading the DBT with automatically co-registered 3D-AUS. The diagnostic performance of each method was measured using ROC analysis. and changes in sensitivity and specificity with the McNemar test. After each reading, radiologists took a survey to rate their confidence level in using DBT alone vs combined DBT/3D-AUS as potential screening modalities. Results The six radiologists had an average area under the ROC curve of 0.92 for both modalities (range 0.89–0.97 for DBT, 0.90–0.94 for DBT/3D-AUS). With BI-RADS rating of 4 as the threshold for biopsy recommendation, the average sensitivity of the radiologists increased from 96% to 100% (p>0.08) with 3D-AUS, while the specificity decreased from 33% to 25% (p>0.28). Survey responses indicated an increased confidence in potentially using DBT for screening when 3D-AUS was added (p<0.05 for each reader). Conclusions In this initial reader study, no significant difference in ROC performance was found with the addition of 3D-AUS to DBT. However, a trend to an improved discrimination of malignancy was observed when adding 3D-AUS. Radiologists’ confidence also improved with DBT/3DAUS compared to DBT alone. PMID:23269714

Magnetic resonance imaging for monitoring therapeutic response in a transgenic mouse model of Alzheimer's disease using voxel-based analysis of amyloid plaques.

PubMed

Kim, Jae-Hun; Ha, Tae Lin; Im, Geun Ho; Yang, Jehoon; Seo, Sang Won; Chung, Julius Juhyun; Chae, Sun Young; Lee, In Su; Lee, Jung Hee

2014-03-05

In this study, we have shown the potential of a voxel-based analysis for imaging amyloid plaques and its utility in monitoring therapeutic response in Alzheimer's disease (AD) mice using manganese oxide nanoparticles conjugated with an antibody of Aβ1-40 peptide (HMON-abAβ40). T1-weighted MR brain images of a drug-treated AD group (n=7), a nontreated AD group (n=7), and a wild-type group (n=7) were acquired using a 7.0 T MRI system before (D-1), 24-h (D+1) after, and 72-h (D+3) after injection with an HMON-abAβ40 contrast agent. For the treatment of AD mice, DAPT was injected intramuscularly into AD transgenic mice (50 mg/kg of body weight). For voxel-based analysis, the skull-stripped mouse brain images were spatially normalized, and these voxels' intensities were corrected to reduce voxel intensity differences across scans in different mice. Statistical analysis showed higher normalized MR signal intensity in the frontal cortex and hippocampus of AD mice over wild-type mice on D+1 and D+3 (P<0.01, uncorrected for multiple comparisons). After the treatment of AD mice, the normalized MR signal intensity in the frontal cortex and hippocampus decreased significantly in comparison with nontreated AD mice on D+1 and D+3 (P<0.01, uncorrected for multiple comparisons). These results were confirmed by histological analysis using a thioflavin staining. This unique strategy allows us to detect brain regions that are subjected to amyloid plaque deposition and has the potential for human applications in monitoring therapeutic response for drug development in AD.

Zero Launch Mass 3D Printer

NASA Image and Video Library

2018-05-01

Nathan Gelino, a research engineer, manually loads materials into the Zero Launch Mass 3-D Printer at Kennedy Space Center’s Swamp Works Tuesday. The 3-D printer heated the pellets to about 600 degrees F and extruded them to produce specimens for material strength properties testing. Automated pellet delivery system will be added to the printer soon.

Rotating and translating anthropomorphic head voxel models to establish an horizontal Frankfort plane for dental CBCT Monte Carlo simulations: a dose comparison study

NASA Astrophysics Data System (ADS)

Stratis, A.; Zhang, G.; Jacobs, R.; Bogaerts, R.; Bosmans, H.

2016-12-01

In order to carry out Monte Carlo (MC) dosimetry studies, voxel phantoms, modeling human anatomy, and organ-based segmentation of CT image data sets are applied to simulation frameworks. The resulting voxel phantoms preserve patient CT acquisition geometry; in the case of head voxel models built upon head CT images, the head support with which CT scanners are equipped introduces an inclination to the head, and hence to the head voxel model. In dental cone beam CT (CBCT) imaging, patients are always positioned in such a way that the Frankfort line is horizontal, implying that there is no head inclination. The orientation of the head is important, as it influences the distance of critical radiosensitive organs like the thyroid and the esophagus from the x-ray tube. This work aims to propose a procedure to adjust head voxel phantom orientation, and to investigate the impact of head inclination on organ doses in dental CBCT MC dosimetry studies. The female adult ICRP, and three in-house-built paediatric voxel phantoms were in this study. An EGSnrc MC framework was employed to simulate two commonly used protocols; a Morita Accuitomo 170 dental CBCT scanner (FOVs: 60  ×  60 mm2 and 80  ×  80 mm2, standard resolution), and a 3D Teeth protocol (FOV: 100  ×  90 mm2) in a Planmeca Promax 3D MAX scanner. Result analysis revealed large absorbed organ dose differences in radiosensitive organs between the original and the geometrically corrected voxel models of this study, ranging from  -45.6% to 39.3%. Therefore, accurate dental CBCT MC dose calculations require geometrical adjustments to be applied to head voxel models.

Improved 3D live-wire method with application to 3D CT chest image analysis

NASA Astrophysics Data System (ADS)

Lu, Kongkuo; Higgins, William E.

2006-03-01

The definition of regions of interests (ROIs), such as suspect cancer nodules or lymph nodes in 3D CT chest images, is often difficult because of the complexity of the phenomena that give rise to them. Manual slice tracing has been used widely for years for such problems, because it is easy to implement and guaranteed to work. But the manual method is extremely time-consuming, especially for high-solution 3D images which may have hundreds of slices, and it is subject to operator biases. Numerous automated image-segmentation methods have been proposed, but they are generally strongly application dependent, and even the "most robust" methods have difficulty in defining complex anatomical ROIs. To address this problem, the semi-automatic interactive paradigm referred to as "live wire" segmentation has been proposed by researchers. In live-wire segmentation, the human operator interactively defines an ROI's boundary guided by an active automated method which suggests what to define. This process in general is far faster, more reproducible and accurate than manual tracing, while, at the same time, permitting the definition of complex ROIs having ill-defined boundaries. We propose a 2D live-wire method employing an improved cost over previous works. In addition, we define a new 3D live-wire formulation that enables rapid definition of 3D ROIs. The method only requires the human operator to consider a few slices in general. Experimental results indicate that the new 2D and 3D live-wire approaches are efficient, allow for high reproducibility, and are reliable for 2D and 3D object segmentation.

Assessment of averaging spatially correlated noise for 3-D radial imaging.

PubMed

Stobbe, Robert W; Beaulieu, Christian

2011-07-01

Any measurement of signal intensity obtained from an image will be corrupted by noise. If the measurement is from one voxel, an error bound associated with noise can be assigned if the standard deviation of noise in the image is known. If voxels are averaged together within a region of interest (ROI) and the image noise is uncorrelated, the error bound associated with noise will be reduced in proportion to the square root of the number of voxels in the ROI. However, when 3-D-radial images are created the image noise will be spatially correlated. In this paper, an equation is derived and verified with simulated noise for the computation of noise averaging when image noise is correlated, facilitating the assessment of noise characteristics for different 3-D-radial imaging methodologies. It is already known that if the radial evolution of projections are altered such that constant sampling density is produced in k-space, the signal-to-noise ratio (SNR) inefficiency of standard radial imaging (SR) can effectively be eliminated (assuming a uniform transfer function is desired). However, it is shown in this paper that the low-frequency noise power reduction of SR will produce beneficial (anti-) correlation of noise and enhanced noise averaging characteristics. If an ROI contains only one voxel a radial evolution altered uniform k-space sampling technique such as twisted projection imaging (TPI) will produce an error bound ~35% less with respect to noise than SR, however, for an ROI containing 16 voxels the SR methodology will facilitate an error bound ~20% less than TPI. If a filtering transfer function is desired, it is shown that designing sampling density to create the filter shape has both SNR and noise correlation advantages over sampling k-space uniformly. In this context SR is also beneficial. Two sets of 48 images produced from a saline phantom with sodium MRI at 4.7T are used to experimentally measure noise averaging characteristics of radial imaging and good

3D Imaging and Automated Ice Bottom Tracking of Canadian Arctic Archipelago Ice Sounding Data

NASA Astrophysics Data System (ADS)

Paden, J. D.; Xu, M.; Sprick, J.; Athinarapu, S.; Crandall, D.; Burgess, D. O.; Sharp, M. J.; Fox, G. C.; Leuschen, C.; Stumpf, T. M.

2016-12-01

The basal topography of the Canadian Arctic Archipelago ice caps is unknown for a number of the glaciers which drain the ice caps. The basal topography is needed for calculating present sea level contribution using the surface mass balance and discharge method and to understand future sea level contributions using ice flow model studies. During the NASA Operation IceBridge 2014 arctic campaign, the Multichannel Coherent Radar Depth Sounder (MCoRDS) used a three transmit beam setting (left beam, nadir beam, right beam) to illuminate a wide swath across the ice glacier in a single pass during three flights over the archipelago. In post processing we have used a combination of 3D imaging methods to produce images for each of the three beams which are then merged to produce a single digitally formed wide swath beam. Because of the high volume of data produced by 3D imaging, manual tracking of the ice bottom is impractical on a large scale. To solve this problem, we propose an automated technique for extracting ice bottom surfaces by viewing the task as an inference problem on a probabilistic graphical model. We first estimate layer boundaries to generate a seed surface, and then incorporate additional sources of evidence, such as ice masks, surface digital elevation models, and feedback from human users, to refine the surface in a discrete energy minimization formulation. We investigate the performance of the imaging and tracking algorithms using flight crossovers since crossing lines should produce consistent maps of the terrain beneath the ice surface and compare manually tracked "ground truth" to the automated tracking algorithms. We found the swath width at the nominal flight altitude of 1000 m to be approximately 3 km. Since many of the glaciers in the archipelago are narrower than this, the radar imaging, in these instances, was able to measure the full glacier cavity in a single pass.

TU-F-CAMPUS-J-04: Impact of Voxel Anisotropy On Statistic Texture Features of Oncologic PET: A Simulation Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, F; Byrd, D; Bowen, S

2015-06-15

Purpose: Texture metrics extracted from oncologic PET have been investigated with respect to their usefulness as definitive indicants for prognosis in a variety of cancer. Metric calculation is often based on cubic voxels. Most commonly used PET scanners, however, produce rectangular voxels, which may change texture metrics. The objective of this study was to examine the variability of PET texture feature metrics resulting from voxel anisotropy. Methods: Sinograms of NEMA NU-2 phantom for 18F-FDG were simulated using the ASIM simulation tool. The obtained projection data was reconstructed (3D-OSEM) on grids of cubic and rectangular voxels, producing PET images of resolutionmore » of 2.73x2.73x3.27mm3 and 3.27x3.27x3.27mm3, respectively. An interpolated dataset obtained from resampling the rectangular voxel data for isotropic voxel dimension (3.27mm) was also considered. For each image dataset, 28 texture parameters based on grey-level co-occurrence matrices (GLCOM), intensity histograms (GLIH), neighborhood difference matrices (GLNDM), and zone size matrices (GLZSM) were evaluated within lesions of diameter of 33, 28, 22, and 17mm. Results: In reference to the isotopic image data, texture features appearing on the rectangular voxel data varied with a range of -34-10% for GLCOM based, -31-39% for GLIH based, -80 -161% for GLNDM based, and −6–45% for GLZSM based while varied with a range of -35-23% for GLCOM based, -27-35% for GLIH based, -65-86% for GLNDM based, and -22 -18% for GLZSM based for the interpolated image data. For the anisotropic data, GLNDM-cplx exhibited the largest extent of variation (161%) while GLZSM-zp showed the least (<1%). As to the interpolated data, GLNDM-busy varied the most (86%) while GLIH-engy varied the least (<1%). Conclusion: Variability of texture appearance on oncologic PET with respect to voxel representation is substantial and feature-dependent. It necessitates consideration of standardized voxel representation for inter

Voxel-based lesion mapping of meningioma: a comprehensive lesion location mapping of 260 lesions.

PubMed

Hirayama, Ryuichi; Kinoshita, Manabu; Arita, Hideyuki; Kagawa, Naoki; Kishima, Haruhiko; Hashimoto, Naoya; Fujimoto, Yasunori; Yoshimine, Toshiki

2018-06-01

OBJECTIVE In the present study the authors aimed to determine preferred locations of meningiomas by avoiding descriptive analysis and instead using voxel-based lesion mapping and 3D image-rendering techniques. METHODS Magnetic resonance images obtained in 248 treatment-naïve meningioma patients with 260 lesions were retrospectively and consecutively collected. All images were registered to a 1-mm isotropic, high-resolution, T1-weighted brain atlas provided by the Montreal Neurological Institute (the MNI152), and a lesion frequency map was created, followed by 3D volume rendering to visualize the preferred locations of meningiomas in 3D. RESULTS The 3D lesion frequency map clearly showed that skull base structures such as parasellar, sphenoid wing, and petroclival regions were commonly affected by the tumor. The middle one-third of the superior sagittal sinus was most commonly affected in parasagittal tumors. Substantial lesion accumulation was observed around the leptomeninges covering the central sulcus and the sylvian fissure, with very few lesions observed at the frontal, parietal, and occipital convexities. CONCLUSIONS Using an objective visualization method, meningiomas were shown to be located around the middle third of the superior sagittal sinus, the perisylvian convexity, and the skull base. These observations, which are in line with previous descriptive analyses, justify further use of voxel-based lesion mapping techniques to help understand the biological nature of this disease.

3D-templated, fully automated microfluidic input/output multiplexer for endocrine tissue culture and secretion sampling.

PubMed

Li, Xiangpeng; Brooks, Jessica C; Hu, Juan; Ford, Katarena I; Easley, Christopher J

2017-01-17

A fully automated, 16-channel microfluidic input/output multiplexer (μMUX) has been developed for interfacing to primary cells and to improve understanding of the dynamics of endocrine tissue function. The device utilizes pressure driven push-up valves for precise manipulation of nutrient input and hormone output dynamics, allowing time resolved interrogation of the cells. The ability to alternate any of the 16 channels from input to output, and vice versa, provides for high experimental flexibility without the need to alter microchannel designs. 3D-printed interface templates were custom designed to sculpt the above-channel polydimethylsiloxane (PDMS) in microdevices, creating millimeter scale reservoirs and confinement chambers to interface primary murine islets and adipose tissue explants to the μMUX sampling channels. This μMUX device and control system was first programmed for dynamic studies of pancreatic islet function to collect ∼90 minute insulin secretion profiles from groups of ∼10 islets. The automated system was also operated in temporal stimulation and cell imaging mode. Adipose tissue explants were exposed to a temporal mimic of post-prandial insulin and glucose levels, while simultaneous switching between labeled and unlabeled free fatty acid permitted fluorescent imaging of fatty acid uptake dynamics in real time over a ∼2.5 hour period. Application with varying stimulation and sampling modes on multiple murine tissue types highlights the inherent flexibility of this novel, 3D-templated μMUX device. The tissue culture reservoirs and μMUX control components presented herein should be adaptable as individual modules in other microfluidic systems, such as organ-on-a-chip devices, and should be translatable to different tissues such as liver, heart, skeletal muscle, and others.

Automated anatomical labeling method for abdominal arteries extracted from 3D abdominal CT images

NASA Astrophysics Data System (ADS)

Oda, Masahiro; Hoang, Bui Huy; Kitasaka, Takayuki; Misawa, Kazunari; Fujiwara, Michitaka; Mori, Kensaku

2012-02-01

This paper presents an automated anatomical labeling method of abdominal arteries. In abdominal surgery, understanding of blood vessel structure concerning with a target organ is very important. Branching pattern of blood vessels differs among individuals. It is required to develop a system that can assist understanding of a blood vessel structure and anatomical names of blood vessels of a patient. Previous anatomical labbeling methods for abdominal arteries deal with either of the upper or lower abdominal arteries. In this paper, we present an automated anatomical labeling method of both of the upper and lower abdominal arteries extracted from CT images. We obtain a tree structure of artery regions and calculate feature values for each branch. These feature values include the diameter, curvature, direction, and running vectors of a branch. Target arteries of this method are grouped based on branching conditions. The following processes are separately applied for each group. We compute candidate artery names by using classifiers that are trained to output artery names. A correction process of the candidate anatomical names based on the rule of majority is applied to determine final names. We applied the proposed method to 23 cases of 3D abdominal CT images. Experimental results showed that the proposed method is able to perform nomenclature of entire major abdominal arteries. The recall and the precision rates of labeling are 79.01% and 80.41%, respectively.

Reliability of voxel gray values in cone beam computed tomography for preoperative implant planning assessment.

PubMed

Parsa, Azin; Ibrahim, Norliza; Hassan, Bassam; Motroni, Alessandro; van der Stelt, Paul; Wismeijer, Daniel

2012-01-01

To assess the reliability of cone beam computed tomography (CBCT) voxel gray value measurements using Hounsfield units (HU) derived from multislice computed tomography (MSCT) as a clinical reference (gold standard). Ten partially edentulous human mandibular cadavers were scanned by two types of computed tomography (CT) modalities: multislice CT and cone beam CT. On MSCT scans, eight regions of interest (ROI) designating the site for preoperative implant placement were selected in each mandible. The datasets from both CT systems were matched using a three-dimensional (3D) registration algorithm. The mean voxel gray values of the region around the implant sites were compared between MSCT and CBCT. Significant differences between the mean gray values obtained by CBCT and HU by MSCT were found. In all the selected ROIs, CBCT showed higher mean values than MSCT. A strong correlation (R=0.968) between mean voxel gray values of CBCT and mean HU of MSCT was determined. Voxel gray values from CBCT deviate from actual HU units. However, a strong linear correlation exists, which may permit deriving actual HU units from CBCT using linear regression models.

Detection of the nipple in automated 3D breast ultrasound using coronal slab-average-projection and cumulative probability map

NASA Astrophysics Data System (ADS)

Kim, Hannah; Hong, Helen

2014-03-01

We propose an automatic method for nipple detection on 3D automated breast ultrasound (3D ABUS) images using coronal slab-average-projection and cumulative probability map. First, to identify coronal images that appeared remarkable distinction between nipple-areola region and skin, skewness of each coronal image is measured and the negatively skewed images are selected. Then, coronal slab-average-projection image is reformatted from selected images. Second, to localize nipple-areola region, elliptical ROI covering nipple-areola region is detected using Hough ellipse transform in coronal slab-average-projection image. Finally, to separate the nipple from areola region, 3D Otsu's thresholding is applied to the elliptical ROI and cumulative probability map in the elliptical ROI is generated by assigning high probability to low intensity region. False detected small components are eliminated using morphological opening and the center point of detected nipple region is calculated. Experimental results show that our method provides 94.4% nipple detection rate.

Automated liver sampling using a gradient dual-echo Dixon-based technique.

PubMed

Bashir, Mustafa R; Dale, Brian M; Merkle, Elmar M; Boll, Daniel T

2012-05-01

Magnetic resonance spectroscopy of the liver requires input from a physicist or physician at the time of acquisition to insure proper voxel selection, while in multiecho chemical shift imaging, numerous regions of interest must be manually selected in order to ensure analysis of a representative portion of the liver parenchyma. A fully automated technique could improve workflow by selecting representative portions of the liver prior to human analysis. Complete volumes from three-dimensional gradient dual-echo acquisitions with two-point Dixon reconstruction acquired at 1.5 and 3 T were analyzed in 100 subjects, using an automated liver sampling algorithm, based on ratio pairs calculated from signal intensity image data as fat-only/water-only and log(in-phase/opposed-phase) on a voxel-by-voxel basis. Using different gridding variations of the algorithm, the average correct liver volume samples ranged from 527 to 733 mL. The average percentage of sample located within the liver ranged from 95.4 to 97.1%, whereas the average incorrect volume selected was 16.5-35.4 mL (2.9-4.6%). Average run time was 19.7-79.0 s. The algorithm consistently selected large samples of the hepatic parenchyma with small amounts of erroneous extrahepatic sampling, and run times were feasible for execution on an MRI system console during exam acquisition. Copyright © 2011 Wiley Periodicals, Inc.

TU-CD-207-09: Analysis of the 3-D Shape of Patients’ Breast for Breast Imaging and Surgery Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Agasthya, G; Sechopoulos, I

2015-06-15

Purpose: Develop a method to accurately capture the 3-D shape of patients’ external breast surface before and during breast compression for mammography/tomosynthesis. Methods: During this IRB-approved, HIPAA-compliant study, 50 women were recruited to undergo 3-D breast surface imaging during breast compression and imaging for the cranio-caudal (CC) view on a digital mammography/breast tomosynthesis system. Digital projectors and cameras mounted on tripods were used to acquire 3-D surface images of the breast, in three conditions: (a) positioned on the support paddle before compression, (b) during compression by the compression paddle and (c) the anterior-posterior view with the breast in its natural,more » unsupported position. The breast was compressed to standard full compression with the compression paddle and a tomosynthesis image was acquired simultaneously with the 3-D surface. The 3-D surface curvature and deformation with respect to the uncompressed surface was analyzed using contours. The 3-D surfaces were voxelized to capture breast shape in a format that can be manipulated for further analysis. Results: A protocol was developed to accurately capture the 3-D shape of patients’ breast before and during compression for mammography. Using a pair of 3-D scanners, the 50 patient breasts were scanned in three conditions, resulting in accurate representations of the breast surfaces. The surfaces were post processed, analyzed using contours and voxelized, with 1 mm{sup 3} voxels, converting the breast shape into a format that can be easily modified as required. Conclusion: Accurate characterization of the breast curvature and shape for the generation of 3-D models is possible. These models can be used for various applications such as improving breast dosimetry, accurate scatter estimation, conducting virtual clinical trials and validating compression algorithms. Ioannis Sechopoulos is consultant for Fuji Medical Systems USA.« less

Automated 3D Phenotype Analysis Using Data Mining

PubMed Central

Plyusnin, Ilya; Evans, Alistair R.; Karme, Aleksis; Gionis, Aristides; Jernvall, Jukka

2008-01-01

The ability to analyze and classify three-dimensional (3D) biological morphology has lagged behind the analysis of other biological data types such as gene sequences. Here, we introduce the techniques of data mining to the study of 3D biological shapes to bring the analyses of phenomes closer to the efficiency of studying genomes. We compiled five training sets of highly variable morphologies of mammalian teeth from the MorphoBrowser database. Samples were labeled either by dietary class or by conventional dental types (e.g. carnassial, selenodont). We automatically extracted a multitude of topological attributes using Geographic Information Systems (GIS)-like procedures that were then used in several combinations of feature selection schemes and probabilistic classification models to build and optimize classifiers for predicting the labels of the training sets. In terms of classification accuracy, computational time and size of the feature sets used, non-repeated best-first search combined with 1-nearest neighbor classifier was the best approach. However, several other classification models combined with the same searching scheme proved practical. The current study represents a first step in the automatic analysis of 3D phenotypes, which will be increasingly valuable with the future increase in 3D morphology and phenomics databases. PMID:18320060

Sculplexity: Sculptures of Complexity using 3D printing

NASA Astrophysics Data System (ADS)

Reiss, D. S.; Price, J. J.; Evans, T. S.

2013-11-01

We show how to convert models of complex systems such as 2D cellular automata into a 3D printed object. Our method takes into account the limitations inherent to 3D printing processes and materials. Our approach automates the greater part of this task, bypassing the use of CAD software and the need for manual design. As a proof of concept, a physical object representing a modified forest fire model was successfully printed. Automated conversion methods similar to the ones developed here can be used to create objects for research, for demonstration and teaching, for outreach, or simply for aesthetic pleasure. As our outputs can be touched, they may be particularly useful for those with visual disabilities.

NIF Ignition Target 3D Point Design

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, O; Marinak, M; Milovich, J

2008-11-05

We have developed an input file for running 3D NIF hohlraums that is optimized such that it can be run in 1-2 days on parallel computers. We have incorporated increasing levels of automation into the 3D input file: (1) Configuration controlled input files; (2) Common file for 2D and 3D, different types of capsules (symcap, etc.); and (3) Can obtain target dimensions, laser pulse, and diagnostics settings automatically from NIF Campaign Management Tool. Using 3D Hydra calculations to investigate different problems: (1) Intrinsic 3D asymmetry; (2) Tolerance to nonideal 3D effects (e.g. laser power balance, pointing errors); and (3) Syntheticmore » diagnostics.« less

Standardization of automated 25-hydroxyvitamin D assays: How successful is it?

PubMed

Elsenberg, E H A M; Ten Boekel, E; Huijgen, H; Heijboer, A C

2017-12-01

Multiple 25(OH)D assays have recently been aligned to improve comparibility. In this study we investigated the performance of these assays using both native single-donor sera with target values certified by a reference method as well as single donor sera from a heterogeneous patient population. 25(OH)D levels were measured in twenty reference samples (Ref!25OHD; Labquality, Finland) using five automated methods (Lumipulse, Liaison, Cobas, iSYS and Access) and one aligned ID-XLC-MS/MS method (slope: 1,00; intercept: 0,00; R=0,996). Furthermore, 25(OH)D concentrations measured in 50 pregnant women and 52 random patients using the 5 automated assays were compared to the ID-XLC-MS/MS. In addition, Vitamin D binding protein (DBP) was measured. Most automated assays showed significant differences in 25(OH)D levels measured in reference samples. Slopes varied from 1,00 to 1,33, intercepts from -5.48 to -15,81nmol/L and the R from 0,971 to 0,997. This inaccuracy was even more prominent in a heterogeneous patient population. Slopes varied from 0,75 to 1,35, intercepts from -9.02 to 11,51nmol/L and the R from 0,840 to 0,949. For most assays the deviation in 25(OH)D concentration increased with elevating DBP concentrations suggesting that DBP might be one of the factors contributing to the inaccuracy in currently used automated 25(OH)D methods. Despite the use of standardized assays, we observed significant differences in 25(OH)D concentrations in some automated methods using reference material obtained from healthy single donor sera. In sera of a patient population this inaccuracy was even worse which is highly concerning as patient samples are being investigated in clinical laboratories. Copyright © 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Development, validation, and implementation of a patient-specific Monte Carlo 3D internal dosimetry platform

NASA Astrophysics Data System (ADS)

Besemer, Abigail E.

Targeted radionuclide therapy is emerging as an attractive treatment option for a broad spectrum of tumor types because it has the potential to simultaneously eradicate both the primary tumor site as well as the metastatic disease throughout the body. Patient-specific absorbed dose calculations for radionuclide therapies are important for reducing the risk of normal tissue complications and optimizing tumor response. However, the only FDA approved software for internal dosimetry calculates doses based on the MIRD methodology which estimates mean organ doses using activity-to-dose scaling factors tabulated from standard phantom geometries. Despite the improved dosimetric accuracy afforded by direct Monte Carlo dosimetry methods these methods are not widely used in routine clinical practice because of the complexity of implementation, lack of relevant standard protocols, and longer dose calculation times. The main goal of this work was to develop a Monte Carlo internal dosimetry platform in order to (1) calculate patient-specific voxelized dose distributions in a clinically feasible time frame, (2) examine and quantify the dosimetric impact of various parameters and methodologies used in 3D internal dosimetry methods, and (3) develop a multi-criteria treatment planning optimization framework for multi-radiopharmaceutical combination therapies. This platform utilizes serial PET/CT or SPECT/CT images to calculate voxelized 3D internal dose distributions with the Monte Carlo code Geant4. Dosimetry can be computed for any diagnostic or therapeutic radiopharmaceutical and for both pre-clinical and clinical applications. In this work, the platform's dosimetry calculations were successfully validated against previously published reference doses values calculated in standard phantoms for a variety of radionuclides, over a wide range of photon and electron energies, and for many different organs and tumor sizes. Retrospective dosimetry was also calculated for various pre

Practical interpretation of CYP2D6 haplotypes: Comparison and integration of automated and expert calling.

PubMed

Ruaño, Gualberto; Kocherla, Mohan; Graydon, James S; Holford, Theodore R; Makowski, Gregory S; Goethe, John W

2016-05-01

We describe a population genetic approach to compare samples interpreted with expert calling (EC) versus automated calling (AC) for CYP2D6 haplotyping. The analysis represents 4812 haplotype calls based on signal data generated by the Luminex xMap analyzers from 2406 patients referred to a high-complexity molecular diagnostics laboratory for CYP450 testing. DNA was extracted from buccal swabs. We compared the results of expert calls (EC) and automated calls (AC) with regard to haplotype number and frequency. The ratio of EC to AC was 1:3. Haplotype frequencies from EC and AC samples were convergent across haplotypes, and their distribution was not statistically different between the groups. Most duplications required EC, as only expansions with homozygous or hemizygous haplotypes could be automatedly called. High-complexity laboratories can offer equivalent interpretation to automated calling for non-expanded CYP2D6 loci, and superior interpretation for duplications. We have validated scientific expert calling specified by scoring rules as standard operating procedure integrated with an automated calling algorithm. The integration of EC with AC is a practical strategy for CYP2D6 clinical haplotyping. Copyright © 2016 Elsevier B.V. All rights reserved.

The role of 3-D interactive visualization in blind surveys of H I in galaxies

NASA Astrophysics Data System (ADS)

Punzo, D.; van der Hulst, J. M.; Roerdink, J. B. T. M.; Oosterloo, T. A.; Ramatsoku, M.; Verheijen, M. A. W.

2015-09-01

Upcoming H I surveys will deliver large datasets, and automated processing using the full 3-D information (two positional dimensions and one spectral dimension) to find and characterize H I objects is imperative. In this context, visualization is an essential tool for enabling qualitative and quantitative human control on an automated source finding and analysis pipeline. We discuss how Visual Analytics, the combination of automated data processing and human reasoning, creativity and intuition, supported by interactive visualization, enables flexible and fast interaction with the 3-D data, helping the astronomer to deal with the analysis of complex sources. 3-D visualization, coupled to modeling, provides additional capabilities helping the discovery and analysis of subtle structures in the 3-D domain. The requirements for a fully interactive visualization tool are: coupled 1-D/2-D/3-D visualization, quantitative and comparative capabilities, combined with supervised semi-automated analysis. Moreover, the source code must have the following characteristics for enabling collaborative work: open, modular, well documented, and well maintained. We review four state of-the-art, 3-D visualization packages assessing their capabilities and feasibility for use in the case of 3-D astronomical data.

Automation of 3D reconstruction of neural tissue from large volume of conventional serial section transmission electron micrographs.

PubMed

Mishchenko, Yuriy

2009-01-30

We describe an approach for automation of the process of reconstruction of neural tissue from serial section transmission electron micrographs. Such reconstructions require 3D segmentation of individual neuronal processes (axons and dendrites) performed in densely packed neuropil. We first detect neuronal cell profiles in each image in a stack of serial micrographs with multi-scale ridge detector. Short breaks in detected boundaries are interpolated using anisotropic contour completion formulated in fuzzy-logic framework. Detected profiles from adjacent sections are linked together based on cues such as shape similarity and image texture. Thus obtained 3D segmentation is validated by human operators in computer-guided proofreading process. Our approach makes possible reconstructions of neural tissue at final rate of about 5 microm3/manh, as determined primarily by the speed of proofreading. To date we have applied this approach to reconstruct few blocks of neural tissue from different regions of rat brain totaling over 1000microm3, and used these to evaluate reconstruction speed, quality, error rates, and presence of ambiguous locations in neuropil ssTEM imaging data.

Determining Tooth Occlusal Surface Relief Indicator by Means of Automated 3d Shape Analysis

NASA Astrophysics Data System (ADS)

Gaboutchian, A. V.; Knyaz, V. A.

2017-05-01

Determining occlusal surface relief indicator plays an important role in odontometric tooth shape analysis. An analysis of the parameters of surface relief indicators provides valuable information about closure of dental arches (occlusion) and changes in structure of teeth in lifetime. Such data is relevant for dentistry or anthropology applications. Descriptive techniques commonly used for surface relief evaluation have limited precision which, as a result, does not provide for reliability of conclusions about structure and functioning of teeth. Parametric techniques developed for such applications need special facilities and are time-consuming which limits their spread and ease to access. Nevertheless the use of 3D models, obtained by photogrammetric techniques, allows attaining required measurements accuracy and has a potential for process automation. We introduce new approaches for determining tooth occlusal surface relief indicator and provide data on efficiency in use of different indicators in natural attrition evaluation.

Micro-CT Pore Scale Study Of Flow In Porous Media: Effect Of Voxel Resolution

NASA Astrophysics Data System (ADS)

Shah, S.; Gray, F.; Crawshaw, J.; Boek, E.

2014-12-01

In the last few years, pore scale studies have become the key to understanding the complex fluid flow processes in the fields of groundwater remediation, hydrocarbon recovery and environmental issues related to carbon storage and capture. A pore scale study is often comprised of two key procedures: 3D pore scale imaging and numerical modelling techniques. The essence of a pore scale study is to test the physics implemented in a model of complicated fluid flow processes at one scale (microscopic) and then apply the model to solve the problems associated with water resources and oil recovery at other scales (macroscopic and field). However, the process of up-scaling from the pore scale to the macroscopic scale has encountered many challenges due to both pore scale imaging and modelling techniques. Due to the technical limitations in the imaging method, there is always a compromise between the spatial (voxel) resolution and the physical volume of the sample (field of view, FOV) to be scanned by the imaging methods, specifically X-ray micro-CT (XMT) in our case In this study, a careful analysis was done to understand the effect of voxel size, using XMT to image the 3D pore space of a variety of porous media from sandstones to carbonates scanned at different voxel resolution (4.5 μm, 6.2 μm, 8.3 μm and 10.2 μm) but keeping the scanned FOV constant for all the samples. We systematically segment the micro-CT images into three phases, the macro-pore phase, an intermediate phase (unresolved micro-pores + grains) and the grain phase and then study the effect of voxel size on the structure of the macro-pore and the intermediate phases and the fluid flow properties using lattice-Boltzmann (LB) and pore network (PN) modelling methods. We have also applied a numerical coarsening algorithm (up-scale method) to reduce the computational power and time required to accurately predict the flow properties using the LB and PN method.

Magmatic Systems in 3-D

NASA Astrophysics Data System (ADS)

Kent, G. M.; Harding, A. J.; Babcock, J. M.; Orcutt, J. A.; Bazin, S.; Singh, S.; Detrick, R. S.; Canales, J. P.; Carbotte, S. M.; Diebold, J.

2002-12-01

Multichannel seismic (MCS) images of crustal magma chambers are ideal targets for advanced visualization techniques. In the mid-ocean ridge environment, reflections originating at the melt-lens are well separated from other reflection boundaries, such as the seafloor, layer 2A and Moho, which enables the effective use of transparency filters. 3-D visualization of seismic reflectivity falls into two broad categories: volume and surface rendering. Volumetric-based visualization is an extremely powerful approach for the rapid exploration of very dense 3-D datasets. These 3-D datasets are divided into volume elements or voxels, which are individually color coded depending on the assigned datum value; the user can define an opacity filter to reject plotting certain voxels. This transparency allows the user to peer into the data volume, enabling an easy identification of patterns or relationships that might have geologic merit. Multiple image volumes can be co-registered to look at correlations between two different data types (e.g., amplitude variation with offsets studies), in a manner analogous to draping attributes onto a surface. In contrast, surface visualization of seismic reflectivity usually involves producing "fence" diagrams of 2-D seismic profiles that are complemented with seafloor topography, along with point class data, draped lines and vectors (e.g. fault scarps, earthquake locations and plate-motions). The overlying seafloor can be made partially transparent or see-through, enabling 3-D correlations between seafloor structure and seismic reflectivity. Exploration of 3-D datasets requires additional thought when constructing and manipulating these complex objects. As numbers of visual objects grow in a particular scene, there is a tendency to mask overlapping objects; this clutter can be managed through the effective use of total or partial transparency (i.e., alpha-channel). In this way, the co-variation between different datasets can be investigated

3D osteocyte lacunar morphometric properties and distributions in human femoral cortical bone using synchrotron radiation micro-CT images.

PubMed

Dong, Pei; Haupert, Sylvain; Hesse, Bernhard; Langer, Max; Gouttenoire, Pierre-Jean; Bousson, Valérie; Peyrin, Françoise

2014-03-01

Osteocytes, the most numerous bone cells, are thought to be actively involved in the bone modeling and remodeling processes. The morphology of osteocyte is hypothesized to adapt according to the physiological mechanical loading. Three-dimensional micro-CT has recently been used to study osteocyte lacunae. In this work, we proposed a computationally efficient and validated automated image analysis method to quantify the 3D shape descriptors of osteocyte lacunae and their distribution in human femurs. Thirteen samples were imaged using Synchrotron Radiation (SR) micro-CT at ID19 of the ESRF with 1.4μm isotropic voxel resolution. With a field of view of about 2.9×2.9×1.4mm(3), the 3D images include several tens of thousands of osteocyte lacunae. We designed an automated quantification method to segment and extract 3D cell descriptors from osteocyte lacunae. An image moment-based approach was used to calculate the volume, length, width, height and anisotropy of each osteocyte lacuna. We employed a fast algorithm to further efficiently calculate the surface area, the Euler number and the structure model index (SMI) of each lacuna. We also introduced the 3D lacunar density map to directly visualize the lacunar density variation over a large field of view. We reported the lacunar morphometric properties and distributions as well as cortical bone histomorphometric indices on the 13 bone samples. The mean volume and surface were found to be 409.5±149.7μm(3) and 336.2±94.5μm(2). The average dimensions were of 18.9±4.9μm in length, 9.2±2.1μm in width and 4.8±1.1μm in depth. We found lacunar number density and six osteocyte lacunar descriptors, three axis lengths, two anisotropy ratios and SMI, that are significantly correlated to bone porosity at a same local region. The proposed method allowed an automatic and efficient direct 3D analysis of a large population of bone cells and is expected to provide reliable biological information for better understanding the

Automated 3D architecture reconstruction from photogrammetric structure-and-motion: A case study of the One Pilla pagoda, Hanoi, Vienam

NASA Astrophysics Data System (ADS)

To, T.; Nguyen, D.; Tran, G.

2015-04-01

Heritage system of Vietnam has decline because of poor-conventional condition. For sustainable development, it is required a firmly control, space planning organization, and reasonable investment. Moreover, in the field of Cultural Heritage, the use of automated photogrammetric systems, based on Structure from Motion techniques (SfM), is widely used. With the potential of high-resolution, low-cost, large field of view, easiness, rapidity and completeness, the derivation of 3D metric information from Structure-and- Motion images is receiving great attention. In addition, heritage objects in form of 3D physical models are recorded not only for documentation issues, but also for historical interpretation, restoration, cultural and educational purposes. The study suggests the archaeological documentation of the "One Pilla" pagoda placed in Hanoi capital, Vietnam. The data acquired through digital camera Cannon EOS 550D, CMOS APS-C sensor 22.3 x 14.9 mm. Camera calibration and orientation were carried out by VisualSFM, CMPMVS (Multi-View Reconstruction) and SURE (Photogrammetric Surface Reconstruction from Imagery) software. The final result represents a scaled 3D model of the One Pilla Pagoda and displayed different views in MeshLab software.

Feasibility of fabricating personalized 3D-printed bone grafts guided by high-resolution imaging

NASA Astrophysics Data System (ADS)

Hong, Abigail L.; Newman, Benjamin T.; Khalid, Arbab; Teter, Olivia M.; Kobe, Elizabeth A.; Shukurova, Malika; Shinde, Rohit; Sipzner, Daniel; Pignolo, Robert J.; Udupa, Jayaram K.; Rajapakse, Chamith S.

2017-03-01

Current methods of bone graft treatment for critical size bone defects can give way to several clinical complications such as limited available bone for autografts, non-matching bone structure, lack of strength which can compromise a patient's skeletal system, and sterilization processes that can prevent osteogenesis in the case of allografts. We intend to overcome these disadvantages by generating a patient-specific 3D printed bone graft guided by high-resolution medical imaging. Our synthetic model allows us to customize the graft for the patients' macro- and microstructure and correct any structural deficiencies in the re-meshing process. These 3D-printed models can presumptively serve as the scaffolding for human mesenchymal stem cell (hMSC) engraftment in order to facilitate bone growth. We performed highresolution CT imaging of a cadaveric human proximal femur at 0.030-mm isotropic voxels. We used these images to generate a 3D computer model that mimics bone geometry from micro to macro scale represented by STereoLithography (STL) format. These models were then reformatted to a format that can be interpreted by the 3D printer. To assess how much of the microstructure was replicated, 3D-printed models were re-imaged using micro-CT at 0.025-mm isotropic voxels and compared to original high-resolution CT images used to generate the 3D model in 32 sub-regions. We found a strong correlation between 3D-printed bone volume and volume of bone in the original images used for 3D printing (R2 = 0.97). We expect to further refine our approach with additional testing to create a viable synthetic bone graft with clinical functionality.

Initial results of the FUSION-X-US prototype combining 3D automated breast ultrasound and digital breast tomosynthesis.

PubMed

Schaefgen, Benedikt; Heil, Joerg; Barr, Richard G; Radicke, Marcus; Harcos, Aba; Gomez, Christina; Stieber, Anne; Hennigs, André; von Au, Alexandra; Spratte, Julia; Rauch, Geraldine; Rom, Joachim; Schütz, Florian; Sohn, Christof; Golatta, Michael

2018-06-01

To determine the feasibility of a prototype device combining 3D-automated breast ultrasound (ABVS) and digital breast tomosynthesis in a single device to detect and characterize breast lesions. In this prospective feasibility study, the FUSION-X-US prototype was used to perform digital breast tomosynthesis and ABVS in 23 patients with an indication for tomosynthesis based on current guidelines after clinical examination and standard imaging. The ABVS and tomosynthesis images of the prototype were interpreted separately by two blinded experts. The study compares the detection and BI-RADS® scores of breast lesions using only the tomosynthesis and ABVS data from the FUSION-X-US prototype to the results of the complete diagnostic workup. Image acquisition and processing by the prototype was fast and accurate, with some limitations in ultrasound coverage and image quality. In the diagnostic workup, 29 solid lesions (23 benign, including three cases with microcalcifications, and six malignant lesions) were identified. Using the prototype, all malignant lesions were detected and classified as malignant or suspicious by both investigators. Solid breast lesions can be localized accurately and fast by the Fusion-X-US system. Technical improvements of the ultrasound image quality and ultrasound coverage are needed to further study this new device. The prototype combines tomosynthesis and automated 3D-ultrasound (ABVS) in one device. It allows accurate detection of malignant lesions, directly correlating tomosynthesis and ABVS data. The diagnostic evaluation of the prototype-acquired data was interpreter-independent. The prototype provides a time-efficient and technically reliable diagnostic procedure. The combination of tomosynthesis and ABVS is a promising diagnostic approach.

3D change detection - Approaches and applications

NASA Astrophysics Data System (ADS)

Qin, Rongjun; Tian, Jiaojiao; Reinartz, Peter

2016-12-01

Due to the unprecedented technology development of sensors, platforms and algorithms for 3D data acquisition and generation, 3D spaceborne, airborne and close-range data, in the form of image based, Light Detection and Ranging (LiDAR) based point clouds, Digital Elevation Models (DEM) and 3D city models, become more accessible than ever before. Change detection (CD) or time-series data analysis in 3D has gained great attention due to its capability of providing volumetric dynamics to facilitate more applications and provide more accurate results. The state-of-the-art CD reviews aim to provide a comprehensive synthesis and to simplify the taxonomy of the traditional remote sensing CD techniques, which mainly sit within the boundary of 2D image/spectrum analysis, largely ignoring the particularities of 3D aspects of the data. The inclusion of 3D data for change detection (termed 3D CD), not only provides a source with different modality for analysis, but also transcends the border of traditional top-view 2D pixel/object-based analysis to highly detailed, oblique view or voxel-based geometric analysis. This paper reviews the recent developments and applications of 3D CD using remote sensing and close-range data, in support of both academia and industry researchers who seek for solutions in detecting and analyzing 3D dynamics of various objects of interest. We first describe the general considerations of 3D CD problems in different processing stages and identify CD types based on the information used, being the geometric comparison and geometric-spectral analysis. We then summarize relevant works and practices in urban, environment, ecology and civil applications, etc. Given the broad spectrum of applications and different types of 3D data, we discuss important issues in 3D CD methods. Finally, we present concluding remarks in algorithmic aspects of 3D CD.

Automatic needle segmentation in 3D ultrasound images using 3D Hough transform

NASA Astrophysics Data System (ADS)

Zhou, Hua; Qiu, Wu; Ding, Mingyue; Zhang, Songgeng

2007-12-01

3D ultrasound (US) is a new technology that can be used for a variety of diagnostic applications, such as obstetrical, vascular, and urological imaging, and has been explored greatly potential in the applications of image-guided surgery and therapy. Uterine adenoma and uterine bleeding are the two most prevalent diseases in Chinese woman, and a minimally invasive ablation system using an RF button electrode which is needle-like is being used to destroy tumor cells or stop bleeding currently. Now a 3D US guidance system has been developed to avoid accidents or death of the patient by inaccurate localizations of the electrode and the tumor position during treatment. In this paper, we described two automated techniques, the 3D Hough Transform (3DHT) and the 3D Randomized Hough Transform (3DRHT), which is potentially fast, accurate, and robust to provide needle segmentation in 3D US image for use of 3D US imaging guidance. Based on the representation (Φ , θ , ρ , α ) of straight lines in 3D space, we used the 3DHT algorithm to segment needles successfully assumed that the approximate needle position and orientation are known in priori. The 3DRHT algorithm was developed to detect needles quickly without any information of the 3D US images. The needle segmentation techniques were evaluated using the 3D US images acquired by scanning water phantoms. The experiments demonstrated the feasibility of two 3D needle segmentation algorithms described in this paper.

DG-AMMOS: a new tool to generate 3d conformation of small molecules using distance geometry and automated molecular mechanics optimization for in silico screening.

PubMed

Lagorce, David; Pencheva, Tania; Villoutreix, Bruno O; Miteva, Maria A

2009-11-13

Discovery of new bioactive molecules that could enter drug discovery programs or that could serve as chemical probes is a very complex and costly endeavor. Structure-based and ligand-based in silico screening approaches are nowadays extensively used to complement experimental screening approaches in order to increase the effectiveness of the process and facilitating the screening of thousands or millions of small molecules against a biomolecular target. Both in silico screening methods require as input a suitable chemical compound collection and most often the 3D structure of the small molecules has to be generated since compounds are usually delivered in 1D SMILES, CANSMILES or in 2D SDF formats. Here, we describe the new open source program DG-AMMOS which allows the generation of the 3D conformation of small molecules using Distance Geometry and their energy minimization via Automated Molecular Mechanics Optimization. The program is validated on the Astex dataset, the ChemBridge Diversity database and on a number of small molecules with known crystal structures extracted from the Cambridge Structural Database. A comparison with the free program Balloon and the well-known commercial program Omega generating the 3D of small molecules is carried out. The results show that the new free program DG-AMMOS is a very efficient 3D structure generator engine. DG-AMMOS provides fast, automated and reliable access to the generation of 3D conformation of small molecules and facilitates the preparation of a compound collection prior to high-throughput virtual screening computations. The validation of DG-AMMOS on several different datasets proves that generated structures are generally of equal quality or sometimes better than structures obtained by other tested methods.

3D vision system for intelligent milking robot automation

NASA Astrophysics Data System (ADS)

Akhloufi, M. A.

2013-12-01

In a milking robot, the correct localization and positioning of milking teat cups is of very high importance. The milking robots technology has not changed since a decade and is based primarily on laser profiles for teats approximate positions estimation. This technology has reached its limit and does not allow optimal positioning of the milking cups. Also, in the presence of occlusions, the milking robot fails to milk the cow. These problems, have economic consequences for producers and animal health (e.g. development of mastitis). To overcome the limitations of current robots, we have developed a new system based on 3D vision, capable of efficiently positioning the milking cups. A prototype of an intelligent robot system based on 3D vision for real-time positioning of a milking robot has been built and tested under various conditions on a synthetic udder model (in static and moving scenarios). Experimental tests, were performed using 3D Time-Of-Flight (TOF) and RGBD cameras. The proposed algorithms permit the online segmentation of teats by combing 2D and 3D visual information. The obtained results permit the teat 3D position computation. This information is then sent to the milking robot for teat cups positioning. The vision system has a real-time performance and monitors the optimal positioning of the cups even in the presence of motion. The obtained results, with both TOF and RGBD cameras, show the good performance of the proposed system. The best performance was obtained with RGBD cameras. This latter technology will be used in future real life experimental tests.

A multiscale approach for the reconstruction of the fiber architecture of the human brain based on 3D-PLI

PubMed Central

Reckfort, Julia; Wiese, Hendrik; Pietrzyk, Uwe; Zilles, Karl; Amunts, Katrin; Axer, Markus

2015-01-01

Structural connectivity of the brain can be conceptionalized as a multiscale organization. The present study is built on 3D-Polarized Light Imaging (3D-PLI), a neuroimaging technique targeting the reconstruction of nerve fiber orientations and therefore contributing to the analysis of brain connectivity. Spatial orientations of the fibers are derived from birefringence measurements of unstained histological sections that are interpreted by means of a voxel-based analysis. This implies that a single fiber orientation vector is obtained for each voxel, which reflects the net effect of all comprised fibers. We have utilized two polarimetric setups providing an object space resolution of 1.3 μm/px (microscopic setup) and 64 μm/px (macroscopic setup) to carry out 3D-PLI and retrieve fiber orientations of the same tissue samples, but at complementary voxel sizes (i.e., scales). The present study identifies the main sources which cause a discrepancy of the measured fiber orientations observed when measuring the same sample with the two polarimetric systems. As such sources the differing optical resolutions and diverging retardances of the implemented waveplates were identified. A methodology was implemented that enables the compensation of measured different systems' responses to the same birefringent sample. This opens up new ways to conduct multiscale analysis in brains by means of 3D-PLI and to provide a reliable basis for the transition between different scales of the nerve fiber architecture. PMID:26388744

45 CFR 310.5 - What options are available for Computerized Tribal IV-D Systems and office automation?

Code of Federal Regulations, 2010 CFR

2010-10-01

... to conduct automated data processing and recordkeeping activities through Office Automation... IV-D Systems and office automation? 310.5 Section 310.5 Public Welfare Regulations Relating to Public... AUTOMATION Requirements for Computerized Tribal IV-D Systems and Office Automation § 310.5 What options are...

TU-H-CAMPUS-JeP3-02: Automated Dose Accumulation and Dose Accuracy Assessment for Online Or Offline Adaptive Replanning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, G; Ahunbay, E; Li, X

Purpose: With introduction of high-quality treatment imaging during radiation therapy (RT) delivery, e.g., MR-Linac, adaptive replanning of either online or offline becomes appealing. Dose accumulation of delivered fractions, a prerequisite for the adaptive replanning, can be cumbersome and inaccurate. The purpose of this work is to develop an automated process to accumulate daily doses and to assess the dose accumulation accuracy voxel-by-voxel for adaptive replanning. Methods: The process includes the following main steps: 1) reconstructing daily dose for each delivered fraction with a treatment planning system (Monaco, Elekta) based on the daily images using machine delivery log file and consideringmore » patient repositioning if applicable, 2) overlaying the daily dose to the planning image based on deformable image registering (DIR) (ADMIRE, Elekta), 3) assessing voxel dose deformation accuracy based on deformation field using predetermined criteria, and 4) outputting accumulated dose and dose-accuracy volume histograms and parameters. Daily CTs acquired using a CT-on-rails during routine CT-guided RT for sample patients with head and neck and prostate cancers were used to test the process. Results: Daily and accumulated doses (dose-volume histograms, etc) along with their accuracies (dose-accuracy volume histogram) can be robustly generated using the proposed process. The test data for a head and neck cancer case shows that the gross tumor volume decreased by 20% towards the end of treatment course, and the parotid gland mean dose increased by 10%. Such information would trigger adaptive replanning for the subsequent fractions. The voxel-based accuracy in the accumulated dose showed that errors in accumulated dose near rigid structures were small. Conclusion: A procedure as well as necessary tools to automatically accumulate daily dose and assess dose accumulation accuracy is developed and is useful for adaptive replanning. Partially supported by Elekta

Mapping Cortical Laminar Structure in the 3D BigBrain.

PubMed

Wagstyl, Konrad; Lepage, Claude; Bludau, Sebastian; Zilles, Karl; Fletcher, Paul C; Amunts, Katrin; Evans, Alan C

2018-07-01

Histological sections offer high spatial resolution to examine laminar architecture of the human cerebral cortex; however, they are restricted by being 2D, hence only regions with sufficiently optimal cutting planes can be analyzed. Conversely, noninvasive neuroimaging approaches are whole brain but have relatively low resolution. Consequently, correct 3D cross-cortical patterns of laminar architecture have never been mapped in histological sections. We developed an automated technique to identify and analyze laminar structure within the high-resolution 3D histological BigBrain. We extracted white matter and pial surfaces, from which we derived histologically verified surfaces at the layer I/II boundary and within layer IV. Layer IV depth was strongly predicted by cortical curvature but varied between areas. This fully automated 3D laminar analysis is an important requirement for bridging high-resolution 2D cytoarchitecture and in vivo 3D neuroimaging. It lays the foundation for in-depth, whole-brain analyses of cortical layering.

3-D Imaging Systems for Agricultural Applications—A Review

PubMed Central

Vázquez-Arellano, Manuel; Griepentrog, Hans W.; Reiser, David; Paraforos, Dimitris S.

2016-01-01

Efficiency increase of resources through automation of agriculture requires more information about the production process, as well as process and machinery status. Sensors are necessary for monitoring the status and condition of production by recognizing the surrounding structures such as objects, field structures, natural or artificial markers, and obstacles. Currently, three dimensional (3-D) sensors are economically affordable and technologically advanced to a great extent, so a breakthrough is already possible if enough research projects are commercialized. The aim of this review paper is to investigate the state-of-the-art of 3-D vision systems in agriculture, and the role and value that only 3-D data can have to provide information about environmental structures based on the recent progress in optical 3-D sensors. The structure of this research consists of an overview of the different optical 3-D vision techniques, based on the basic principles. Afterwards, their application in agriculture are reviewed. The main focus lays on vehicle navigation, and crop and animal husbandry. The depth dimension brought by 3-D sensors provides key information that greatly facilitates the implementation of automation and robotics in agriculture. PMID:27136560

Automated 3D segmentation of intraretinal layers from optic nerve head optical coherence tomography images

NASA Astrophysics Data System (ADS)

Antony, Bhavna J.; Abràmoff, Michael D.; Lee, Kyungmoo; Sonkova, Pavlina; Gupta, Priya; Kwon, Young; Niemeijer, Meindert; Hu, Zhihong; Garvin, Mona K.

2010-03-01

Optical coherence tomography (OCT), being a noninvasive imaging modality, has begun to find vast use in the diagnosis and management of ocular diseases such as glaucoma, where the retinal nerve fiber layer (RNFL) has been known to thin. Furthermore, the recent availability of the considerably larger volumetric data with spectral-domain OCT has increased the need for new processing techniques. In this paper, we present an automated 3-D graph-theoretic approach for the segmentation of 7 surfaces (6 layers) of the retina from 3-D spectral-domain OCT images centered on the optic nerve head (ONH). The multiple surfaces are detected simultaneously through the computation of a minimum-cost closed set in a vertex-weighted graph constructed using edge/regional information, and subject to a priori determined varying surface interaction and smoothness constraints. The method also addresses the challenges posed by presence of the large blood vessels and the optic disc. The algorithm was compared to the average manual tracings of two observers on a total of 15 volumetric scans, and the border positioning error was found to be 7.25 +/- 1.08 μm and 8.94 +/- 3.76 μm for the normal and glaucomatous eyes, respectively. The RNFL thickness was also computed for 26 normal and 70 glaucomatous scans where the glaucomatous eyes showed a significant thinning (p < 0.01, mean thickness 73.7 +/- 32.7 μm in normal eyes versus 60.4 +/- 25.2 μm in glaucomatous eyes).

MicroCT-Based Skeletal Models for Use in Tomographic Voxel Phantoms for Radiological Protection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bolch, Wesley

The University of Florida (UF) proposes to develop two high-resolution image-based skeletal dosimetry models for direct use by ICRP Committee 2’s Task Group on Dose Calculation in their forthcoming Reference Voxel Male (RVM) and Reference Voxel Female (RVF) whole-body dosimetry phantoms. These two phantoms are CT-based, and thus do not have the image resolution to delineate and perform radiation transport modeling of the individual marrow cavities and bone trabeculae throughout their skeletal structures. Furthermore, new and innovative 3D microimaging techniques will now be required for the skeletal tissues following Committee 2’s revision of the target tissues of relevance for radiogenicmore » bone cancer induction. This target tissue had been defined in ICRP Publication 30 as a 10-μm cell layer on all bone surfaces of trabecular and cortical bone. The revised target tissue is now a 50-μm layer within the marrow cavities of trabecular bone only and is exclusive of the marrow adipocytes. Clearly, this new definition requires the use of 3D microimages of the trabecular architecture not available from past 2D optical studies of the adult skeleton. With our recent acquisition of two relatively young cadavers (males of age 18-years and 40-years), we will develop a series of reference skeletal models that can be directly applied to (1) the new ICRP reference voxel man and female phantoms developed for the ICRP, and (2) pediatric phantoms developed to target the ICRP reference children. Dosimetry data to be developed will include absorbed fractions for internal beta and alpha-particle sources, as well as photon and neutron fluence-to-dose response functions for direct use in external dosimetry studies of the ICRP reference workers and members of the general public« less

Volumetric 3D display using a DLP projection engine

NASA Astrophysics Data System (ADS)

Geng, Jason

2012-03-01

In this article, we describe a volumetric 3D display system based on the high speed DLPTM (Digital Light Processing) projection engine. Existing two-dimensional (2D) flat screen displays often lead to ambiguity and confusion in high-dimensional data/graphics presentation due to lack of true depth cues. Even with the help of powerful 3D rendering software, three-dimensional (3D) objects displayed on a 2D flat screen may still fail to provide spatial relationship or depth information correctly and effectively. Essentially, 2D displays have to rely upon capability of human brain to piece together a 3D representation from 2D images. Despite the impressive mental capability of human visual system, its visual perception is not reliable if certain depth cues are missing. In contrast, volumetric 3D display technologies to be discussed in this article are capable of displaying 3D volumetric images in true 3D space. Each "voxel" on a 3D image (analogous to a pixel in 2D image) locates physically at the spatial position where it is supposed to be, and emits light from that position toward omni-directions to form a real 3D image in 3D space. Such a volumetric 3D display provides both physiological depth cues and psychological depth cues to human visual system to truthfully perceive 3D objects. It yields a realistic spatial representation of 3D objects and simplifies our understanding to the complexity of 3D objects and spatial relationship among them.

Feasibility of rapid and automated importation of 3D echocardiographic left ventricular (LV) geometry into a finite element (FEM) analysis model

PubMed Central

Verhey, Janko F; Nathan, Nadia S

2004-01-01

Background Finite element method (FEM) analysis for intraoperative modeling of the left ventricle (LV) is presently not possible. Since 3D structural data of the LV is now obtainable using standard transesophageal echocardiography (TEE) devices intraoperatively, the present study describes a method to transfer this data into a commercially available FEM analysis system: ABAQUS©. Methods In this prospective study TomTec LV Analysis TEE© Software was used for semi-automatic endocardial border detection, reconstruction, and volume-rendering of the clinical 3D echocardiographic data. A newly developed software program MVCP FemCoGen©, written in Delphi, reformats the TomTec file structures in five patients for use in ABAQUS and allows visualization of regional deformation of the LV. Results This study demonstrates that a fully automated importation of 3D TEE data into FEM modeling is feasible and can be efficiently accomplished in the operating room. Conclusion For complete intraoperative 3D LV finite element analysis, three input elements are necessary: 1. time-gaited, reality-based structural information, 2. continuous LV pressure and 3. instantaneous tissue elastance. The first of these elements is now available using the methods presented herein. PMID:15473901

3D multi-scale FCN with random modality voxel dropout learning for Intervertebral Disc Localization and Segmentation from Multi-modality MR Images.

PubMed

Li, Xiaomeng; Dou, Qi; Chen, Hao; Fu, Chi-Wing; Qi, Xiaojuan; Belavý, Daniel L; Armbrecht, Gabriele; Felsenberg, Dieter; Zheng, Guoyan; Heng, Pheng-Ann

2018-04-01

Intervertebral discs (IVDs) are small joints that lie between adjacent vertebrae. The localization and segmentation of IVDs are important for spine disease diagnosis and measurement quantification. However, manual annotation is time-consuming and error-prone with limited reproducibility, particularly for volumetric data. In this work, our goal is to develop an automatic and accurate method based on fully convolutional networks (FCN) for the localization and segmentation of IVDs from multi-modality 3D MR data. Compared with single modality data, multi-modality MR images provide complementary contextual information, which contributes to better recognition performance. However, how to effectively integrate such multi-modality information to generate accurate segmentation results remains to be further explored. In this paper, we present a novel multi-scale and modality dropout learning framework to locate and segment IVDs from four-modality MR images. First, we design a 3D multi-scale context fully convolutional network, which processes the input data in multiple scales of context and then merges the high-level features to enhance the representation capability of the network for handling the scale variation of anatomical structures. Second, to harness the complementary information from different modalities, we present a random modality voxel dropout strategy which alleviates the co-adaption issue and increases the discriminative capability of the network. Our method achieved the 1st place in the MICCAI challenge on automatic localization and segmentation of IVDs from multi-modality MR images, with a mean segmentation Dice coefficient of 91.2% and a mean localization error of 0.62 mm. We further conduct extensive experiments on the extended dataset to validate our method. We demonstrate that the proposed modality dropout strategy with multi-modality images as contextual information improved the segmentation accuracy significantly. Furthermore, experiments conducted on

Improving the visualization of 3D ultrasound data with 3D filtering

NASA Astrophysics Data System (ADS)

Shamdasani, Vijay; Bae, Unmin; Managuli, Ravi; Kim, Yongmin

2005-04-01

compositing. 3D filtering of an ultrasound volume containing millions of voxels requires a large amount of computation, and doing it twice decreases the number of frames that can be visualized per second. To address this, we have developed several techniques to make computation efficient. For example, we have used the moving average method to filter a 128x128x128 volume with a 3x3x3 boxcar kernel in 17 ms on a single MAP processor running at 400 MHz. The same methods reduced the computing time on a Pentium 4 running at 3 GHz from 110 ms to 62 ms. We believe that our proposed method can improve 3D ultrasound visualization without sacrificing resolution and incurring an excessive computing time.

A 3D isodose manipulation tool for interactive dose shaping

NASA Astrophysics Data System (ADS)

Kamerling, C. P.; Ziegenhein, P.; Heinrich, H.; Oelfke, U.

2014-03-01

The interactive dose shaping (IDS) planning paradigm aims to perform interactive local dose adaptations of an IMRT plan without compromising already established valuable dose features in real-time. In this work we introduce an interactive 3D isodose manipulation tool which enables local modifications of a dose distribution intuitively by direct manipulation of an isodose surface. We developed an in-house IMRT TPS framework employing an IDS engine as well as a 3D GUI for dose manipulation and visualization. In our software an initial dose distribution can be interactively modified through an isodose surface manipulation tool by intuitively clicking on an isodose surface. To guide the user interaction, the position of the modification is indicated by a sphere while the mouse cursor hovers the isodose surface. The sphere's radius controls the locality of the modification. The tool induces a dose modification as a direct change of dose in one or more voxels, which is incrementally obtained by fluence adjustments. A subsequent recovery step identifies voxels with violated dose features and aims to recover their original dose. We showed a proof of concept study for the proposed tool by adapting the dose distribution of a prostate case (9 beams, coplanar). Single dose modifications take less than 2 seconds on an actual desktop PC.

Validation of 3D multimodality roadmapping in interventional neuroradiology

NASA Astrophysics Data System (ADS)

Ruijters, Daniel; Homan, Robert; Mielekamp, Peter; van de Haar, Peter; Babic, Drazenko

2011-08-01

Three-dimensional multimodality roadmapping is entering clinical routine utilization for neuro-vascular treatment. Its purpose is to navigate intra-arterial and intra-venous endovascular devices through complex vascular anatomy by fusing pre-operative computed tomography (CT) or magnetic resonance (MR) with the live fluoroscopy image. The fused image presents the real-time position of the intra-vascular devices together with the patient's 3D vascular morphology and its soft-tissue context. This paper investigates the effectiveness, accuracy, robustness and computation times of the described methods in order to assess their suitability for the intended clinical purpose: accurate interventional navigation. The mutual information-based 3D-3D registration proved to be of sub-voxel accuracy and yielded an average registration error of 0.515 mm and the live machine-based 2D-3D registration delivered an average error of less than 0.2 mm. The capture range of the image-based 3D-3D registration was investigated to characterize its robustness, and yielded an extent of 35 mm and 25° for >80% of the datasets for registration of 3D rotational angiography (3DRA) with CT, and 15 mm and 20° for >80% of the datasets for registration of 3DRA with MR data. The image-based 3D-3D registration could be computed within 8 s, while applying the machine-based 2D-3D registration only took 1.5 µs, which makes them very suitable for interventional use.

Impact of voxel size variation on CBCT-based diagnostic outcome in dentistry: a systematic review.

PubMed

Spin-Neto, Rubens; Gotfredsen, Erik; Wenzel, Ann

2013-08-01

The objective of this study was to make a systematic review on the impact of voxel size in cone beam computed tomography (CBCT)-based image acquisition, retrieving evidence regarding the diagnostic outcome of those images. The MEDLINE bibliographic database was searched from 1950 to June 2012 for reports comparing diverse CBCT voxel sizes. The search strategy was limited to English-language publications using the following combined terms in the search strategy: (voxel or FOV or field of view or resolution) and (CBCT or cone beam CT). The results from the review identified 20 publications that qualitatively or quantitatively assessed the influence of voxel size on CBCT-based diagnostic outcome, and in which the methodology/results comprised at least one of the expected parameters (image acquisition, reconstruction protocols, type of diagnostic task, and presence of a gold standard). The diagnostic task assessed in the studies was diverse, including the detection of root fractures, the detection of caries lesions, and accuracy of 3D surface reconstruction and of bony measurements, among others. From the studies assessed, it is clear that no general protocol can be yet defined for CBCT examination of specific diagnostic tasks in dentistry. Rationale in this direction is an important step to define the utility of CBCT imaging.

Mapping the MRI voxel volume in which thermal noise matches physiological noise--implications for fMRI.

PubMed

Bodurka, J; Ye, F; Petridou, N; Murphy, K; Bandettini, P A

2007-01-15

This work addresses the choice of the imaging voxel volume in blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI). Noise of physiological origin that is present in the voxel time course is a prohibitive factor in the detection of small activation-induced BOLD signal changes. If the physiological noise contribution dominates over the temporal fluctuation contribution in the imaging voxel, further increases in the voxel signal-to-noise ratio (SNR) will have diminished corresponding increases in temporal signal-to-noise (TSNR), resulting in reduced corresponding increases in the ability to detect activation induced signal changes. On the other hand, if the thermal and system noise dominate (suggesting a relatively low SNR) further decreases in SNR can prohibit detection of activation-induced signal changes. Here we have proposed and called the "suggested" voxel volume for fMRI the volume where thermal plus system-related and physiological noise variances are equal. Based on this condition we have created maps of fMRI suggested voxel volume from our experimental data at 3T, since this value will spatially vary depending on the contribution of physiologic noise in each voxel. Based on our fast EPI segmentation technique we have found that for gray matter (GM), white matter (WM), and cerebral spinal fluid (CSF) brain compartments the mean suggested cubical voxel volume is: (1.8 mm)3, (2.1 mm)3 and (1.4 mm)3, respectively. Serendipitously, (1.8 mm)3 cubical voxel volume for GM approximately matches the cortical thickness, thus optimizing BOLD contrast by minimizing partial volume averaging. The introduced suggested fMRI voxel volume can be a useful parameter for choice of imaging volume for functional studies.

A Novel Automated Method for Analyzing Cylindrical Computed Tomography Data

NASA Technical Reports Server (NTRS)

Roth, D. J.; Burke, E. R.; Rauser, R. W.; Martin, R. E.

2011-01-01

A novel software method is presented that is applicable for analyzing cylindrical and partially cylindrical objects inspected using computed tomography. This method involves unwrapping and re-slicing data so that the CT data from the cylindrical object can be viewed as a series of 2-D sheets in the vertical direction in addition to volume rendering and normal plane views provided by traditional CT software. The method is based on interior and exterior surface edge detection and under proper conditions, is FULLY AUTOMATED and requires no input from the user except the correct voxel dimension from the CT scan. The software is available from NASA in 32- and 64-bit versions that can be applied to gigabyte-sized data sets, processing data either in random access memory or primarily on the computer hard drive. Please inquire with the presenting author if further interested. This software differentiates itself in total from other possible re-slicing software solutions due to complete automation and advanced processing and analysis capabilities.

WE-AB-202-07: Ventilation CT: Voxel-Level Comparison with Hyperpolarized Helium-3 & Xenon-129 MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tahir, B; Marshall, H; Hughes, P

Purpose: To compare the spatial correlation of ventilation surrogates computed from inspiratory and expiratory breath-hold CT with hyperpolarized Helium-3 & Xenon-129 MRI in a cohort of lung cancer patients. Methods: 5 patients underwent expiration & inspiration breath-hold CT. Xenon-129 & {sup 1}H MRI were also acquired at the same inflation state as inspiratory CT. This was followed immediately by acquisition of Helium-3 & {sup 1}H MRI in the same breath and at the same inflation state as inspiratory CT. Expiration CT was deformably registered to inspiration CT for calculation of ventilation CT from voxel-wise differences in Hounsfield units. Inspiration CTmore » and the Xenon-129’s corresponding anatomical {sup 1}H MRI were registered to Helium-3 MRI via the same-breath anatomical {sup 1}H MRI. This enabled direct comparison of CT ventilation with Helium-3 MRI & Xenon-129 MRI for the median values in corresponding regions of interest, ranging from finer to coarser in-plane dimensions of 10 by 10, 20 by 20, 30 by 30 and 40 by 40, located within the lungs as defined by the same-breath {sup 1}H MRI lung mask. Spearman coefficients were used to assess voxel-level correlation. Results: The median Spearman’s coefficients of ventilation CT with Helium-3 & Xenon-129 MRI for ROIs of 10 by 10, 20 by 20, 30 by 30 and 40 by 40 were 0.52, 0.56, 0.60 and 0.68 and 0.40, 0.42, 0.52 and 0.70, respectively. Conclusion: This work demonstrates a method of acquiring CT & hyperpolarized gas MRI (Helium-3 & Xenon-129 MRI) in similar breath-holds to enable direct spatial comparison of ventilation maps. Initial results show moderate correlation between ventilation CT & hyperpolarized gas MRI, improving for coarser regions which could be attributable to the inherent noise in CT intensity, non-ventilatory effects and registration errors at the voxel-level. Thus, it may be more beneficial to quantify ventilation at a more regional level.« less

Volumetric 3D display with multi-layered active screens for enhanced the depth perception (Conference Presentation)

NASA Astrophysics Data System (ADS)

Kim, Hak-Rin; Park, Min-Kyu; Choi, Jun-Chan; Park, Ji-Sub; Min, Sung-Wook

2016-09-01

Three-dimensional (3D) display technology has been studied actively because it can offer more realistic images compared to the conventional 2D display. Various psychological factors such as accommodation, binocular parallax, convergence and motion parallax are used to recognize a 3D image. For glass-type 3D displays, they use only the binocular disparity in 3D depth cues. However, this method cause visual fatigue and headaches due to accommodation conflict and distorted depth perception. Thus, the hologram and volumetric display are expected to be an ideal 3D display. Holographic displays can represent realistic images satisfying the entire factors of depth perception. But, it require tremendous amount of data and fast signal processing. The volumetric 3D displays can represent images using voxel which is a physical volume. However, it is required for large data to represent the depth information on voxel. In order to simply encode 3D information, the compact type of depth fused 3D (DFD) display, which can create polarization distributed depth map (PDDM) image having both 2D color image and depth image is introduced. In this paper, a new volumetric 3D display system is shown by using PDDM image controlled by polarization controller. In order to introduce PDDM image, polarization states of the light through spatial light modulator (SLM) was analyzed by Stokes parameter depending on the gray level. Based on the analysis, polarization controller is properly designed to convert PDDM image into sectioned depth images. After synchronizing PDDM images with active screens, we can realize reconstructed 3D image. Acknowledgment This work was supported by `The Cross-Ministry Giga KOREA Project' grant from the Ministry of Science, ICT and Future Planning, Korea

ART 3.5D: an algorithm to label arteries and veins from three-dimensional angiography.

PubMed

Barra, Beatrice; De Momi, Elena; Ferrigno, Giancarlo; Pero, Guglielmo; Cardinale, Francesco; Baselli, Giuseppe

2016-10-01

Preoperative three-dimensional (3-D) visualization of brain vasculature by digital subtraction angiography from computerized tomography (CT) in neurosurgery is gaining more and more importance, since vessels are the primary landmarks both for organs at risk and for navigation. Surgical embolization of cerebral aneurysms and arteriovenous malformations, epilepsy surgery, and stereoelectroencephalography are a few examples. Contrast-enhanced cone-beam computed tomography (CE-CBCT) represents a powerful facility, since it is capable of acquiring images in the operation room, shortly before surgery. However, standard 3-D reconstructions do not provide a direct distinction between arteries and veins, which is of utmost importance and is left to the surgeon's inference so far. Pioneering attempts by true four-dimensional (4-D) CT perfusion scans were already described, though at the expense of longer acquisition protocols, higher dosages, and sensible resolution losses. Hence, space is open to approaches attempting to recover the contrast dynamics from standard CE-CBCT, on the basis of anomalies overlooked in the standard 3-D approach. This paper aims at presenting algebraic reconstruction technique (ART) 3.5D, a method that overcomes the clinical limitations of 4-D CT, from standard 3-D CE-CBCT scans. The strategy works on the 3-D angiography, previously segmented in the standard way, and reprocesses the dynamics hidden in the raw data to recover an approximate dynamics in each segmented voxel. Next, a classification algorithm labels the angiographic voxels and artery or vein. Numerical simulations were performed on a digital phantom of a simplified 3-D vasculature with contrast transit. CE-CBCT projections were simulated and used for ART 3.5D testing. We achieved up to 90% classification accuracy in simulations, proving the feasibility of the presented approach for dynamic information recovery for arteries and veins segmentation.

FluidCam 1&2 - UAV-based Fluid Lensing Instruments for High-Resolution 3D Subaqueous Imaging and Automated Remote Biosphere Assessment of Reef Ecosystems

NASA Astrophysics Data System (ADS)

Chirayath, V.; Instrella, R.

2016-02-01

We present NASA ESTO FluidCam 1 & 2, Visible and NIR Fluid-Lensing-enabled imaging payloads for Unmanned Aerial Vehicles (UAVs). Developed as part of a focused 2014 earth science technology grant, FluidCam 1&2 are Fluid-Lensing-based computational optical imagers designed for automated 3D mapping and remote sensing of underwater coastal targets from airborne platforms. Fluid Lensing has been used to map underwater reefs in 3D in American Samoa and Hamelin Pool, Australia from UAV platforms at sub-cm scale, which has proven a valuable tool in modern marine research for marine biosphere assessment and conservation. We share FluidCam 1&2 instrument validation and testing results as well as preliminary processed data from field campaigns. Petabyte-scale aerial survey efforts using Fluid Lensing to image at-risk reefs demonstrate broad applicability to large-scale automated species identification, morphology studies and reef ecosystem characterization for shallow marine environments and terrestrial biospheres, of crucial importance to improving bathymetry data for physical oceanographic models and understanding climate change's impact on coastal zones, global oxygen production, carbon sequestration.

FluidCam 1&2 - UAV-Based Fluid Lensing Instruments for High-Resolution 3D Subaqueous Imaging and Automated Remote Biosphere Assessment of Reef Ecosystems

NASA Astrophysics Data System (ADS)

Chirayath, V.

2015-12-01

We present NASA ESTO FluidCam 1 & 2, Visible and NIR Fluid-Lensing-enabled imaging payloads for Unmanned Aerial Vehicles (UAVs). Developed as part of a focused 2014 earth science technology grant, FluidCam 1&2 are Fluid-Lensing-based computational optical imagers designed for automated 3D mapping and remote sensing of underwater coastal targets from airborne platforms. Fluid Lensing has been used to map underwater reefs in 3D in American Samoa and Hamelin Pool, Australia from UAV platforms at sub-cm scale, which has proven a valuable tool in modern marine research for marine biosphere assessment and conservation. We share FluidCam 1&2 instrument validation and testing results as well as preliminary processed data from field campaigns. Petabyte-scale aerial survey efforts using Fluid Lensing to image at-risk reefs demonstrate broad applicability to large-scale automated species identification, morphology studies and reef ecosystem characterization for shallow marine environments and terrestrial biospheres, of crucial importance to improving bathymetry data for physical oceanographic models and understanding climate change's impact on coastal zones, global oxygen production, carbon sequestration.

Automated 3D reconstruction of interiors with multiple scan views

NASA Astrophysics Data System (ADS)

Sequeira, Vitor; Ng, Kia C.; Wolfart, Erik; Goncalves, Joao G. M.; Hogg, David C.

1998-12-01

This paper presents two integrated solutions for realistic 3D model acquisition and reconstruction; an early prototype, in the form of a push trolley, and a later prototype in the form of an autonomous robot. The systems encompass all hardware and software required, from laser and video data acquisition, processing and output of texture-mapped 3D models in VRML format, to batteries for power supply and wireless network communications. The autonomous version is also equipped with a mobile platform and other sensors for the purpose of automatic navigation. The applications for such a system range from real estate and tourism (e.g., showing a 3D computer model of a property to a potential buyer or tenant) or as tool for content creation (e.g., creating 3D models of heritage buildings or producing broadcast quality virtual studios). The system can also be used in industrial environments as a reverse engineering tool to update the design of a plant, or as a 3D photo-archive for insurance purposes. The system is Internet compatible: the photo-realistic models can be accessed via the Internet and manipulated interactively in 3D using a common Web browser with a VRML plug-in. Further information and example reconstructed models are available on- line via the RESOLV web-page at http://www.scs.leeds.ac.uk/resolv/.

3-D ultrasound volume reconstruction using the direct frame interpolation method.

PubMed

Scheipers, Ulrich; Koptenko, Sergei; Remlinger, Rachel; Falco, Tony; Lachaine, Martin

2010-11-01

A new method for 3-D ultrasound volume reconstruction using tracked freehand 3-D ultrasound is proposed. The method is based on solving the forward volume reconstruction problem using direct interpolation of high-resolution ultrasound B-mode image frames. A series of ultrasound B-mode image frames (an image series) is acquired using the freehand scanning technique and position sensing via optical tracking equipment. The proposed algorithm creates additional intermediate image frames by directly interpolating between two or more adjacent image frames of the original image series. The target volume is filled using the original frames in combination with the additionally constructed frames. Compared with conventional volume reconstruction methods, no additional filling of empty voxels or holes within the volume is required, because the whole extent of the volume is defined by the arrangement of the original and the additionally constructed B-mode image frames. The proposed direct frame interpolation (DFI) method was tested on two different data sets acquired while scanning the head and neck region of different patients. The first data set consisted of eight B-mode 2-D frame sets acquired under optimal laboratory conditions. The second data set consisted of 73 image series acquired during a clinical study. Sample volumes were reconstructed for all 81 image series using the proposed DFI method with four different interpolation orders, as well as with the pixel nearest-neighbor method using three different interpolation neighborhoods. In addition, volumes based on a reduced number of image frames were reconstructed for comparison of the different methods' accuracy and robustness in reconstructing image data that lies between the original image frames. The DFI method is based on a forward approach making use of a priori information about the position and shape of the B-mode image frames (e.g., masking information) to optimize the reconstruction procedure and to reduce

Needle segmentation using 3D Hough transform in 3D TRUS guided prostate transperineal therapy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qiu Wu; Imaging Research Laboratories, Robarts Research Institute, Western University, London, Ontario N6A 5K8; Yuchi Ming

Purpose: Prostate adenocarcinoma is the most common noncutaneous malignancy in American men with over 200 000 new cases diagnosed each year. Prostate interventional therapy, such as cryotherapy and brachytherapy, is an effective treatment for prostate cancer. Its success relies on the correct needle implant position. This paper proposes a robust and efficient needle segmentation method, which acts as an aid to localize the needle in three-dimensional (3D) transrectal ultrasound (TRUS) guided prostate therapy. Methods: The procedure of locating the needle in a 3D TRUS image is a three-step process. First, the original 3D ultrasound image containing a needle is cropped;more » the cropped image is then converted to a binary format based on its histogram. Second, a 3D Hough transform based needle segmentation method is applied to the 3D binary image in order to locate the needle axis. The position of the needle endpoint is finally determined by an optimal threshold based analysis of the intensity probability distribution. The overall efficiency is improved through implementing a coarse-fine searching strategy. The proposed method was validated in tissue-mimicking agar phantoms, chicken breast phantoms, and 3D TRUS patient images from prostate brachytherapy and cryotherapy procedures by comparison to the manual segmentation. The robustness of the proposed approach was tested by means of varying parameters such as needle insertion angle, needle insertion length, binarization threshold level, and cropping size. Results: The validation results indicate that the proposed Hough transform based method is accurate and robust, with an achieved endpoint localization accuracy of 0.5 mm for agar phantom images, 0.7 mm for chicken breast phantom images, and 1 mm for in vivo patient cryotherapy and brachytherapy images. The mean execution time of needle segmentation algorithm was 2 s for a 3D TRUS image with size of 264 Multiplication-Sign 376 Multiplication-Sign 630 voxels

Automated 3D closed surface segmentation: application to vertebral body segmentation in CT images.

PubMed

Liu, Shuang; Xie, Yiting; Reeves, Anthony P

2016-05-01

A fully automated segmentation algorithm, progressive surface resolution (PSR), is presented in this paper to determine the closed surface of approximately convex blob-like structures that are common in biomedical imaging. The PSR algorithm was applied to the cortical surface segmentation of 460 vertebral bodies on 46 low-dose chest CT images, which can be potentially used for automated bone mineral density measurement and compression fracture detection. The target surface is realized by a closed triangular mesh, which thereby guarantees the enclosure. The surface vertices of the triangular mesh representation are constrained along radial trajectories that are uniformly distributed in 3D angle space. The segmentation is accomplished by determining for each radial trajectory the location of its intersection with the target surface. The surface is first initialized based on an input high confidence boundary image and then resolved progressively based on a dynamic attraction map in an order of decreasing degree of evidence regarding the target surface location. For the visual evaluation, the algorithm achieved acceptable segmentation for 99.35 % vertebral bodies. Quantitative evaluation was performed on 46 vertebral bodies and achieved overall mean Dice coefficient of 0.939 (with max [Formula: see text] 0.957, min [Formula: see text] 0.906 and standard deviation [Formula: see text] 0.011) using manual annotations as the ground truth. Both visual and quantitative evaluations demonstrate encouraging performance of the PSR algorithm. This novel surface resolution strategy provides uniform angular resolution for the segmented surface with computation complexity and runtime that are linearly constrained by the total number of vertices of the triangular mesh representation.

Automated tracking and quantification of angiogenic vessel formation in 3D microfluidic devices.

PubMed

Wang, Mengmeng; Ong, Lee-Ling Sharon; Dauwels, Justin; Asada, H Harry

2017-01-01

Angiogenesis, the growth of new blood vessels from pre-existing vessels, is a critical step in cancer invasion. Better understanding of the angiogenic mechanisms is required to develop effective antiangiogenic therapies for cancer treatment. We culture angiogenic vessels in 3D microfluidic devices under different Sphingosin-1-phosphate (S1P) conditions and develop an automated vessel formation tracking system (AVFTS) to track the angiogenic vessel formation and extract quantitative vessel information from the experimental time-lapse phase contrast images. The proposed AVFTS first preprocesses the experimental images, then applies a distance transform and an augmented fast marching method in skeletonization, and finally implements the Hungarian method in branch tracking. When applying the AVFTS to our experimental data, we achieve 97.3% precision and 93.9% recall by comparing with the ground truth obtained from manual tracking by visual inspection. This system enables biologists to quantitatively compare the influence of different growth factors. Specifically, we conclude that the positive S1P gradient increases cell migration and vessel elongation, leading to a higher probability for branching to occur. The AVFTS is also applicable to distinguish tip and stalk cells by considering the relative cell locations in a branch. Moreover, we generate a novel type of cell lineage plot, which not only provides cell migration and proliferation histories but also demonstrates cell phenotypic changes and branch information.

Differential and relaxed image foresting transform for graph-cut segmentation of multiple 3D objects.

PubMed

Moya, Nikolas; Falcão, Alexandre X; Ciesielski, Krzysztof C; Udupa, Jayaram K

2014-01-01

Graph-cut algorithms have been extensively investigated for interactive binary segmentation, when the simultaneous delineation of multiple objects can save considerable user's time. We present an algorithm (named DRIFT) for 3D multiple object segmentation based on seed voxels and Differential Image Foresting Transforms (DIFTs) with relaxation. DRIFT stands behind efficient implementations of some state-of-the-art methods. The user can add/remove markers (seed voxels) along a sequence of executions of the DRIFT algorithm to improve segmentation. Its first execution takes linear time with the image's size, while the subsequent executions for corrections take sublinear time in practice. At each execution, DRIFT first runs the DIFT algorithm, then it applies diffusion filtering to smooth boundaries between objects (and background) and, finally, it corrects possible objects' disconnection occurrences with respect to their seeds. We evaluate DRIFT in 3D CT-images of the thorax for segmenting the arterial system, esophagus, left pleural cavity, right pleural cavity, trachea and bronchi, and the venous system.

The visible ear simulator: a public PC application for GPU-accelerated haptic 3D simulation of ear surgery based on the visible ear data.

PubMed

Sorensen, Mads Solvsten; Mosegaard, Jesper; Trier, Peter

2009-06-01

Existing virtual simulators for middle ear surgery are based on 3-dimensional (3D) models from computed tomographic or magnetic resonance imaging data in which image quality is limited by the lack of detail (maximum, approximately 50 voxels/mm3), natural color, and texture of the source material.Virtual training often requires the purchase of a program, a customized computer, and expensive peripherals dedicated exclusively to this purpose. The Visible Ear freeware library of digital images from a fresh-frozen human temporal bone was segmented, and real-time volume rendered as a 3D model of high-fidelity, true color, and great anatomic detail and realism of the surgically relevant structures. A haptic drilling model was developed for surgical interaction with the 3D model. Realistic visualization in high-fidelity (approximately 125 voxels/mm3) and true color, 2D, or optional anaglyph stereoscopic 3D was achieved on a standard Core 2 Duo personal computer with a GeForce 8,800 GTX graphics card, and surgical interaction was provided through a relatively inexpensive (approximately $2,500) Phantom Omni haptic 3D pointing device. This prototype is published for download (approximately 120 MB) as freeware at http://www.alexandra.dk/ves/index.htm.With increasing personal computer performance, future versions may include enhanced resolution (up to 8,000 voxels/mm3) and realistic interaction with deformable soft tissue components such as skin, tympanic membrane, dura, and cholesteatomas-features some of which are not possible with computed tomographic-/magnetic resonance imaging-based systems.

Faster Aerodynamic Simulation With Cart3D

NASA Technical Reports Server (NTRS)

2003-01-01

A NASA-developed aerodynamic simulation tool is ensuring the safety of future space operations while providing designers and engineers with an automated, highly accurate computer simulation suite. Cart3D, co-winner of NASA's 2002 Software of the Year award, is the result of over 10 years of research and software development conducted by Michael Aftosmis and Dr. John Melton of Ames Research Center and Professor Marsha Berger of the Courant Institute at New York University. Cart3D offers a revolutionary approach to computational fluid dynamics (CFD), the computer simulation of how fluids and gases flow around an object of a particular design. By fusing technological advancements in diverse fields such as mineralogy, computer graphics, computational geometry, and fluid dynamics, the software provides a new industrial geometry processing and fluid analysis capability with unsurpassed automation and efficiency.

Wavelet-based fMRI analysis: 3-D denoising, signal separation, and validation metrics

PubMed Central

Khullar, Siddharth; Michael, Andrew; Correa, Nicolle; Adali, Tulay; Baum, Stefi A.; Calhoun, Vince D.

2010-01-01

We present a novel integrated wavelet-domain based framework (w-ICA) for 3-D de-noising functional magnetic resonance imaging (fMRI) data followed by source separation analysis using independent component analysis (ICA) in the wavelet domain. We propose the idea of a 3-D wavelet-based multi-directional de-noising scheme where each volume in a 4-D fMRI data set is sub-sampled using the axial, sagittal and coronal geometries to obtain three different slice-by-slice representations of the same data. The filtered intensity value of an arbitrary voxel is computed as an expected value of the de-noised wavelet coefficients corresponding to the three viewing geometries for each sub-band. This results in a robust set of de-noised wavelet coefficients for each voxel. Given the decorrelated nature of these de-noised wavelet coefficients; it is possible to obtain more accurate source estimates using ICA in the wavelet domain. The contributions of this work can be realized as two modules. First, the analysis module where we combine a new 3-D wavelet denoising approach with better signal separation properties of ICA in the wavelet domain, to yield an activation component that corresponds closely to the true underlying signal and is maximally independent with respect to other components. Second, we propose and describe two novel shape metrics for post-ICA comparisons between activation regions obtained through different frameworks. We verified our method using simulated as well as real fMRI data and compared our results against the conventional scheme (Gaussian smoothing + spatial ICA: s-ICA). The results show significant improvements based on two important features: (1) preservation of shape of the activation region (shape metrics) and (2) receiver operating characteristic (ROC) curves. It was observed that the proposed framework was able to preserve the actual activation shape in a consistent manner even for very high noise levels in addition to significant reduction in false

3D tomographic imaging with the γ-eye planar scintigraphic gamma camera

NASA Astrophysics Data System (ADS)

Tunnicliffe, H.; Georgiou, M.; Loudos, G. K.; Simcox, A.; Tsoumpas, C.

2017-11-01

γ-eye is a desktop planar scintigraphic gamma camera (100 mm × 50 mm field of view) designed by BET Solutions as an affordable tool for dynamic, whole body, small-animal imaging. This investigation tests the viability of using γ-eye for the collection of tomographic data for 3D SPECT reconstruction. Two software packages, QSPECT and STIR (software for tomographic image reconstruction), have been compared. Reconstructions have been performed using QSPECT’s implementation of the OSEM algorithm and STIR’s OSMAPOSL (Ordered Subset Maximum A Posteriori One Step Late) and OSSPS (Ordered Subsets Separable Paraboloidal Surrogate) algorithms. Reconstructed images of phantom and mouse data have been assessed in terms of spatial resolution, sensitivity to varying activity levels and uniformity. The effect of varying the number of iterations, the voxel size (1.25 mm default voxel size reduced to 0.625 mm and 0.3125 mm), the point spread function correction and the weight of prior terms were explored. While QSPECT demonstrated faster reconstructions, STIR outperformed it in terms of resolution (as low as 1 mm versus 3 mm), particularly when smaller voxel sizes were used, and in terms of uniformity, particularly when prior terms were used. Little difference in terms of sensitivity was seen throughout.

a Novel Method for Automation of 3d Hydro Break Line Generation from LIDAR Data Using Matlab

NASA Astrophysics Data System (ADS)

Toscano, G. J.; Gopalam, U.; Devarajan, V.

2013-08-01

Water body detection is necessary to generate hydro break lines, which are in turn useful in creating deliverables such as TINs, contours, DEMs from LiDAR data. Hydro flattening follows the detection and delineation of water bodies (lakes, rivers, ponds, reservoirs, streams etc.) with hydro break lines. Manual hydro break line generation is time consuming and expensive. Accuracy and processing time depend on the number of vertices marked for delineation of break lines. Automation with minimal human intervention is desired for this operation. This paper proposes using a novel histogram analysis of LiDAR elevation data and LiDAR intensity data to automatically detect water bodies. Detection of water bodies using elevation information was verified by checking against LiDAR intensity data since the spectral reflectance of water bodies is very small compared with that of land and vegetation in near infra-red wavelength range. Detection of water bodies using LiDAR intensity data was also verified by checking against LiDAR elevation data. False detections were removed using morphological operations and 3D break lines were generated. Finally, a comparison of automatically generated break lines with their semi-automated/manual counterparts was performed to assess the accuracy of the proposed method and the results were discussed.

Reduced dimensionality (3,2)D NMR experiments and their automated analysis: implications to high-throughput structural studies on proteins.

PubMed

Reddy, Jithender G; Kumar, Dinesh; Hosur, Ramakrishna V

2015-02-01

Protein NMR spectroscopy has expanded dramatically over the last decade into a powerful tool for the study of their structure, dynamics, and interactions. The primary requirement for all such investigations is sequence-specific resonance assignment. The demand now is to obtain this information as rapidly as possible and in all types of protein systems, stable/unstable, soluble/insoluble, small/big, structured/unstructured, and so on. In this context, we introduce here two reduced dimensionality experiments – (3,2)D-hNCOcanH and (3,2)D-hNcoCAnH – which enhance the previously described 2D NMR-based assignment methods quite significantly. Both the experiments can be recorded in just about 2-3 h each and hence would be of immense value for high-throughput structural proteomics and drug discovery research. The applicability of the method has been demonstrated using alpha-helical bovine apo calbindin-D9k P43M mutant (75 aa) protein. Automated assignment of this data using AUTOBA has been presented, which enhances the utility of these experiments. The backbone resonance assignments so derived are utilized to estimate secondary structures and the backbone fold using Web-based algorithms. Taken together, we believe that the method and the protocol proposed here can be used for routine high-throughput structural studies of proteins. Copyright © 2014 John Wiley & Sons, Ltd.

From pixel to voxel: a deeper view of biological tissue by 3D mass spectral imaging

PubMed Central

Ye, Hui; Greer, Tyler; Li, Lingjun

2011-01-01

Three dimensional mass spectral imaging (3D MSI) is an exciting field that grants the ability to study a broad mass range of molecular species ranging from small molecules to large proteins by creating lateral and vertical distribution maps of select compounds. Although the general premise behind 3D MSI is simple, factors such as choice of ionization method, sample handling, software considerations and many others must be taken into account for the successful design of a 3D MSI experiment. This review provides a brief overview of ionization methods, sample preparation, software types and technological advancements driving 3D MSI research of a wide range of low- to high-mass analytes. Future perspectives in this field are also provided to conclude that the positive and promises ever-growing applications in the biomedical field with continuous developments of this powerful analytical tool. PMID:21320052

"3D fusion" echocardiography improves 3D left ventricular assessment: comparison with 2D contrast echocardiography.

PubMed

Augustine, Daniel; Yaqub, Mohammad; Szmigielski, Cezary; Lima, Eduardo; Petersen, Steffen E; Becher, Harald; Noble, J Alison; Leeson, Paul

2015-02-01

Three-dimensional fusion echocardiography (3DFE) is a novel postprocessing approach that utilizes imaging data acquired from multiple 3D acquisitions. We assessed image quality, endocardial border definition, and cardiac wall motion in patients using 3DFE compared to standard 3D images (3D) and results obtained with contrast echocardiography (2DC). Twenty-four patients (mean age 66.9 ± 13 years, 17 males, 7 females) undergoing 2DC had three, noncontrast, 3D apical volumes acquired at rest. Images were fused using an automated image fusion approach. Quality of the 3DFE was compared to both 3D and 2DC based on contrast-to-noise ratio (CNR) and endocardial border definition. We then compared clinical wall-motion score index (WMSI) calculated from 3DFE and 3D to those obtained from 2DC images. Fused 3D volumes had significantly improved CNR (8.92 ± 1.35 vs. 6.59 ± 1.19, P < 0.0005) and segmental image quality (2.42 ± 0.99 vs. 1.93 ± 1.18, P < 0.005) compared to unfused 3D acquisitions. Levels achieved were closer to scores for 2D contrast images (CNR: 9.04 ± 2.21, P = 0.6; segmental image quality: 2.91 ± 0.37, P < 0.005). WMSI calculated from fused 3D volumes did not differ significantly from those obtained from 2D contrast echocardiography (1.06 ± 0.09 vs. 1.07 ± 0.15, P = 0.69), whereas unfused images produced significantly more variable results (1.19 ± 0.30). This was confirmed by a better intraclass correlation coefficient (ICC 0.72; 95% CI 0.32-0.88) relative to comparisons with unfused images (ICC 0.56; 95% CI 0.02-0.81). 3DFE significantly improves left ventricular image quality compared to unfused 3D in a patient population and allows noncontrast assessment of wall motion that approaches that achieved with 2D contrast echocardiography. © 2014, Wiley Periodicals, Inc.

Method for modeling post-mortem biometric 3D fingerprints

NASA Astrophysics Data System (ADS)

Rajeev, Srijith; Shreyas, Kamath K. M.; Agaian, Sos S.

2016-05-01

Despite the advancements of fingerprint recognition in 2-D and 3-D domain, authenticating deformed/post-mortem fingerprints continue to be an important challenge. Prior cleansing and reconditioning of the deceased finger is required before acquisition of the fingerprint. The victim's finger needs to be precisely and carefully operated by a medium to record the fingerprint impression. This process may damage the structure of the finger, which subsequently leads to higher false rejection rates. This paper proposes a non-invasive method to perform 3-D deformed/post-mortem finger modeling, which produces a 2-D rolled equivalent fingerprint for automated verification. The presented novel modeling method involves masking, filtering, and unrolling. Computer simulations were conducted on finger models with different depth variations obtained from Flashscan3D LLC. Results illustrate that the modeling scheme provides a viable 2-D fingerprint of deformed models for automated verification. The quality and adaptability of the obtained unrolled 2-D fingerprints were analyzed using NIST fingerprint software. Eventually, the presented method could be extended to other biometric traits such as palm, foot, tongue etc. for security and administrative applications.

MAP3D: a media processor approach for high-end 3D graphics

NASA Astrophysics Data System (ADS)

Darsa, Lucia; Stadnicki, Steven; Basoglu, Chris

1999-12-01

Equator Technologies, Inc. has used a software-first approach to produce several programmable and advanced VLIW processor architectures that have the flexibility to run both traditional systems tasks and an array of media-rich applications. For example, Equator's MAP1000A is the world's fastest single-chip programmable signal and image processor targeted for digital consumer and office automation markets. The Equator MAP3D is a proposal for the architecture of the next generation of the Equator MAP family. The MAP3D is designed to achieve high-end 3D performance and a variety of customizable special effects by combining special graphics features with high performance floating-point and media processor architecture. As a programmable media processor, it offers the advantages of a completely configurable 3D pipeline--allowing developers to experiment with different algorithms and to tailor their pipeline to achieve the highest performance for a particular application. With the support of Equator's advanced C compiler and toolkit, MAP3D programs can be written in a high-level language. This allows the compiler to successfully find and exploit any parallelism in a programmer's code, thus decreasing the time to market of a given applications. The ability to run an operating system makes it possible to run concurrent applications in the MAP3D chip, such as video decoding while executing the 3D pipelines, so that integration of applications is easily achieved--using real-time decoded imagery for texturing 3D objects, for instance. This novel architecture enables an affordable, integrated solution for high performance 3D graphics.

Nodule Detection in a Lung Region that's Segmented with Using Genetic Cellular Neural Networks and 3D Template Matching with Fuzzy Rule Based Thresholding

PubMed Central

Osman, Onur; Ucan, Osman N.

2008-01-01

Objective The purpose of this study was to develop a new method for automated lung nodule detection in serial section CT images with using the characteristics of the 3D appearance of the nodules that distinguish themselves from the vessels. Materials and Methods Lung nodules were detected in four steps. First, to reduce the number of region of interests (ROIs) and the computation time, the lung regions of the CTs were segmented using Genetic Cellular Neural Networks (G-CNN). Then, for each lung region, ROIs were specified with using the 8 directional search; +1 or -1 values were assigned to each voxel. The 3D ROI image was obtained by combining all the 2-Dimensional (2D) ROI images. A 3D template was created to find the nodule-like structures on the 3D ROI image. Convolution of the 3D ROI image with the proposed template strengthens the shapes that are similar to those of the template and it weakens the other ones. Finally, fuzzy rule based thresholding was applied and the ROI's were found. To test the system's efficiency, we used 16 cases with a total of 425 slices, which were taken from the Lung Image Database Consortium (LIDC) dataset. Results The computer aided diagnosis (CAD) system achieved 100% sensitivity with 13.375 FPs per case when the nodule thickness was greater than or equal to 5.625 mm. Conclusion Our results indicate that the detection performance of our algorithm is satisfactory, and this may well improve the performance of computer-aided detection of lung nodules. PMID:18253070

PONDEROSA-C/S: client-server based software package for automated protein 3D structure determination.

PubMed

Lee, Woonghee; Stark, Jaime L; Markley, John L

2014-11-01

Peak-picking Of Noe Data Enabled by Restriction Of Shift Assignments-Client Server (PONDEROSA-C/S) builds on the original PONDEROSA software (Lee et al. in Bioinformatics 27:1727-1728. doi: 10.1093/bioinformatics/btr200, 2011) and includes improved features for structure calculation and refinement. PONDEROSA-C/S consists of three programs: Ponderosa Server, Ponderosa Client, and Ponderosa Analyzer. PONDEROSA-C/S takes as input the protein sequence, a list of assigned chemical shifts, and nuclear Overhauser data sets ((13)C- and/or (15)N-NOESY). The output is a set of assigned NOEs and 3D structural models for the protein. Ponderosa Analyzer supports the visualization, validation, and refinement of the results from Ponderosa Server. These tools enable semi-automated NMR-based structure determination of proteins in a rapid and robust fashion. We present examples showing the use of PONDEROSA-C/S in solving structures of four proteins: two that enable comparison with the original PONDEROSA package, and two from the Critical Assessment of automated Structure Determination by NMR (Rosato et al. in Nat Methods 6:625-626. doi: 10.1038/nmeth0909-625 , 2009) competition. The software package can be downloaded freely in binary format from http://pine.nmrfam.wisc.edu/download_packages.html. Registered users of the National Magnetic Resonance Facility at Madison can submit jobs to the PONDEROSA-C/S server at http://ponderosa.nmrfam.wisc.edu, where instructions, tutorials, and instructions can be found. Structures are normally returned within 1-2 days.

SigVox - A 3D feature matching algorithm for automatic street object recognition in mobile laser scanning point clouds

NASA Astrophysics Data System (ADS)

Wang, Jinhu; Lindenbergh, Roderik; Menenti, Massimo

2017-06-01

Urban road environments contain a variety of objects including different types of lamp poles and traffic signs. Its monitoring is traditionally conducted by visual inspection, which is time consuming and expensive. Mobile laser scanning (MLS) systems sample the road environment efficiently by acquiring large and accurate point clouds. This work proposes a methodology for urban road object recognition from MLS point clouds. The proposed method uses, for the first time, shape descriptors of complete objects to match repetitive objects in large point clouds. To do so, a novel 3D multi-scale shape descriptor is introduced, that is embedded in a workflow that efficiently and automatically identifies different types of lamp poles and traffic signs. The workflow starts by tiling the raw point clouds along the scanning trajectory and by identifying non-ground points. After voxelization of the non-ground points, connected voxels are clustered to form candidate objects. For automatic recognition of lamp poles and street signs, a 3D significant eigenvector based shape descriptor using voxels (SigVox) is introduced. The 3D SigVox descriptor is constructed by first subdividing the points with an octree into several levels. Next, significant eigenvectors of the points in each voxel are determined by principal component analysis (PCA) and mapped onto the appropriate triangle of a sphere approximating icosahedron. This step is repeated for different scales. By determining the similarity of 3D SigVox descriptors between candidate point clusters and training objects, street furniture is automatically identified. The feasibility and quality of the proposed method is verified on two point clouds obtained in opposite direction of a stretch of road of 4 km. 6 types of lamp pole and 4 types of road sign were selected as objects of interest. Ground truth validation showed that the overall accuracy of the ∼170 automatically recognized objects is approximately 95%. The results demonstrate

GPU-accelerated Kernel Regression Reconstruction for Freehand 3D Ultrasound Imaging.

PubMed

Wen, Tiexiang; Li, Ling; Zhu, Qingsong; Qin, Wenjian; Gu, Jia; Yang, Feng; Xie, Yaoqin

2017-07-01

Volume reconstruction method plays an important role in improving reconstructed volumetric image quality for freehand three-dimensional (3D) ultrasound imaging. By utilizing the capability of programmable graphics processing unit (GPU), we can achieve a real-time incremental volume reconstruction at a speed of 25-50 frames per second (fps). After incremental reconstruction and visualization, hole-filling is performed on GPU to fill remaining empty voxels. However, traditional pixel nearest neighbor-based hole-filling fails to reconstruct volume with high image quality. On the contrary, the kernel regression provides an accurate volume reconstruction method for 3D ultrasound imaging but with the cost of heavy computational complexity. In this paper, a GPU-based fast kernel regression method is proposed for high-quality volume after the incremental reconstruction of freehand ultrasound. The experimental results show that improved image quality for speckle reduction and details preservation can be obtained with the parameter setting of kernel window size of [Formula: see text] and kernel bandwidth of 1.0. The computational performance of the proposed GPU-based method can be over 200 times faster than that on central processing unit (CPU), and the volume with size of 50 million voxels in our experiment can be reconstructed within 10 seconds.

Inner and outer coronary vessel wall segmentation from CCTA using an active contour model with machine learning-based 3D voxel context-aware image force

NASA Astrophysics Data System (ADS)

Sivalingam, Udhayaraj; Wels, Michael; Rempfler, Markus; Grosskopf, Stefan; Suehling, Michael; Menze, Bjoern H.

2016-03-01

In this paper, we present a fully automated approach to coronary vessel segmentation, which involves calcification or soft plaque delineation in addition to accurate lumen delineation, from 3D Cardiac Computed Tomography Angiography data. Adequately virtualizing the coronary lumen plays a crucial role for simulating blood ow by means of fluid dynamics while additionally identifying the outer vessel wall in the case of arteriosclerosis is a prerequisite for further plaque compartment analysis. Our method is a hybrid approach complementing Active Contour Model-based segmentation with an external image force that relies on a Random Forest Regression model generated off-line. The regression model provides a strong estimate of the distance to the true vessel surface for every surface candidate point taking into account 3D wavelet-encoded contextual image features, which are aligned with the current surface hypothesis. The associated external image force is integrated in the objective function of the active contour model, such that the overall segmentation approach benefits from the advantages associated with snakes and from the ones associated with machine learning-based regression alike. This yields an integrated approach achieving competitive results on a publicly available benchmark data collection (Rotterdam segmentation challenge).

Automatic Reconstruction of Spacecraft 3D Shape from Imagery

NASA Astrophysics Data System (ADS)

Poelman, C.; Radtke, R.; Voorhees, H.

We describe a system that computes the three-dimensional (3D) shape of a spacecraft from a sequence of uncalibrated, two-dimensional images. While the mathematics of multi-view geometry is well understood, building a system that accurately recovers 3D shape from real imagery remains an art. A novel aspect of our approach is the combination of algorithms from computer vision, photogrammetry, and computer graphics. We demonstrate our system by computing spacecraft models from imagery taken by the Air Force Research Laboratory's XSS-10 satellite and DARPA's Orbital Express satellite. Using feature tie points (each identified in two or more images), we compute the relative motion of each frame and the 3D location of each feature using iterative linear factorization followed by non-linear bundle adjustment. The "point cloud" that results from this traditional shape-from-motion approach is typically too sparse to generate a detailed 3D model. Therefore, we use the computed motion solution as input to a volumetric silhouette-carving algorithm, which constructs a solid 3D model based on viewpoint consistency with the image frames. The resulting voxel model is then converted to a facet-based surface representation and is texture-mapped, yielding realistic images from arbitrary viewpoints. We also illustrate other applications of the algorithm, including 3D mensuration and stereoscopic 3D movie generation.

Segmentation and detection of fluorescent 3D spots.

PubMed

Ram, Sundaresh; Rodríguez, Jeffrey J; Bosco, Giovanni

2012-03-01

The 3D spatial organization of genes and other genetic elements within the nucleus is important for regulating gene expression. Understanding how this spatial organization is established and maintained throughout the life of a cell is key to elucidating the many layers of gene regulation. Quantitative methods for studying nuclear organization will lead to insights into the molecular mechanisms that maintain gene organization as well as serve as diagnostic tools for pathologies caused by loss of nuclear structure. However, biologists currently lack automated and high throughput methods for quantitative and qualitative global analysis of 3D gene organization. In this study, we use confocal microscopy and fluorescence in-situ hybridization (FISH) as a cytogenetic technique to detect and localize the presence of specific DNA sequences in 3D. FISH uses probes that bind to specific targeted locations on the chromosomes, appearing as fluorescent spots in 3D images obtained using fluorescence microscopy. In this article, we propose an automated algorithm for segmentation and detection of 3D FISH spots. The algorithm is divided into two stages: spot segmentation and spot detection. Spot segmentation consists of 3D anisotropic smoothing to reduce the effect of noise, top-hat filtering, and intensity thresholding, followed by 3D region-growing. Spot detection uses a Bayesian classifier with spot features such as volume, average intensity, texture, and contrast to detect and classify the segmented spots as either true or false spots. Quantitative assessment of the proposed algorithm demonstrates improved segmentation and detection accuracy compared to other techniques. Copyright © 2012 International Society for Advancement of Cytometry.

Digimouse: a 3D whole body mouse atlas from CT and cryosection data

PubMed Central

Dogdas, Belma; Stout, David; Chatziioannou, Arion F; Leahy, Richard M

2010-01-01

We have constructed a three-dimensional (3D) whole body mouse atlas from coregistered x-ray CT and cryosection data of a normal nude male mouse. High quality PET, x-ray CT and cryosection images were acquired post mortem from a single mouse placed in a stereotactic frame with fiducial markers visible in all three modalities. The image data were coregistered to a common coordinate system using the fiducials and resampled to an isotropic 0.1 mm voxel size. Using interactive editing tools we segmented and labelled whole brain, cerebrum, cerebellum, olfactory bulbs, striatum, medulla, masseter muscles, eyes, lachrymal glands, heart, lungs, liver, stomach, spleen, pancreas, adrenal glands, kidneys, testes, bladder, skeleton and skin surface. The final atlas consists of the 3D volume, in which the voxels are labelled to define the anatomical structures listed above, with coregistered PET, x-ray CT and cryosection images. To illustrate use of the atlas we include simulations of 3D bioluminescence and PET image reconstruction. Optical scatter and absorption values are assigned to each organ to simulate realistic photon transport within the animal for bioluminescence imaging. Similarly, 511 keV photon attenuation values are assigned to each structure in the atlas to simulate realistic photon attenuation in PET. The Digimouse atlas and data are available at http://neuroimage.usc.edu/Digimouse.html. PMID:17228106

An application of cascaded 3D fully convolutional networks for medical image segmentation.

PubMed

Roth, Holger R; Oda, Hirohisa; Zhou, Xiangrong; Shimizu, Natsuki; Yang, Ying; Hayashi, Yuichiro; Oda, Masahiro; Fujiwara, Michitaka; Misawa, Kazunari; Mori, Kensaku

2018-06-01

Recent advances in 3D fully convolutional networks (FCN) have made it feasible to produce dense voxel-wise predictions of volumetric images. In this work, we show that a multi-class 3D FCN trained on manually labeled CT scans of several anatomical structures (ranging from the large organs to thin vessels) can achieve competitive segmentation results, while avoiding the need for handcrafting features or training class-specific models. To this end, we propose a two-stage, coarse-to-fine approach that will first use a 3D FCN to roughly define a candidate region, which will then be used as input to a second 3D FCN. This reduces the number of voxels the second FCN has to classify to ∼10% and allows it to focus on more detailed segmentation of the organs and vessels. We utilize training and validation sets consisting of 331 clinical CT images and test our models on a completely unseen data collection acquired at a different hospital that includes 150 CT scans, targeting three anatomical organs (liver, spleen, and pancreas). In challenging organs such as the pancreas, our cascaded approach improves the mean Dice score from 68.5 to 82.2%, achieving the highest reported average score on this dataset. We compare with a 2D FCN method on a separate dataset of 240 CT scans with 18 classes and achieve a significantly higher performance in small organs and vessels. Furthermore, we explore fine-tuning our models to different datasets. Our experiments illustrate the promise and robustness of current 3D FCN based semantic segmentation of medical images, achieving state-of-the-art results. 1 . Copyright © 2018 Elsevier Ltd. All rights reserved.

Benchmarking of state-of-the-art needle detection algorithms in 3D ultrasound data volumes

NASA Astrophysics Data System (ADS)

Pourtaherian, Arash; Zinger, Svitlana; de With, Peter H. N.; Korsten, Hendrikus H. M.; Mihajlovic, Nenad

2015-03-01

Ultrasound-guided needle interventions are widely practiced in medical diagnostics and therapy, i.e. for biopsy guidance, regional anesthesia or for brachytherapy. Needle guidance using 2D ultrasound can be very challenging due to the poor needle visibility and the limited field of view. Since 3D ultrasound transducers are becoming more widely used, needle guidance can be improved and simplified with appropriate computer-aided analyses. In this paper, we compare two state-of-the-art 3D needle detection techniques: a technique based on line filtering from literature and a system employing Gabor transformation. Both algorithms utilize supervised classification to pre-select candidate needle voxels in the volume and then fit a model of the needle on the selected voxels. The major differences between the two approaches are in extracting the feature vectors for classification and selecting the criterion for fitting. We evaluate the performance of the two techniques using manually-annotated ground truth in several ex-vivo situations of different complexities, containing three different needle types with various insertion angles. This extensive evaluation provides better understanding on the limitations and advantages of each technique under different acquisition conditions, which is leading to the development of improved techniques for more reliable and accurate localization. Benchmarking results that the Gabor features are better capable of distinguishing the needle voxels in all datasets. Moreover, it is shown that the complete processing chain of the Gabor-based method outperforms the line filtering in accuracy and stability of the detection results.

Skeletal dosimetry in the MAX06 and the FAX06 phantoms for external exposure to photons based on vertebral 3D-microCT images

NASA Astrophysics Data System (ADS)

Kramer, R.; Khoury, H. J.; Vieira, J. W.; Kawrakow, I.

2006-12-01

3D-microCT images of vertebral bodies from three different individuals have been segmented into trabecular bone, bone marrow and bone surface cells (BSC), and then introduced into the spongiosa voxels of the MAX06 and the FAX06 phantoms, in order to calculate the equivalent dose to the red bone marrow (RBM) and the BSC in the marrow cavities of trabecular bone with the EGSnrc Monte Carlo code from whole-body exposure to external photon radiation. The MAX06 and the FAX06 phantoms consist of about 150 million 1.2 mm cubic voxels each, a part of which are spongiosa voxels surrounded by cortical bone. In order to use the segmented 3D-microCT images for skeletal dosimetry, spongiosa voxels in the MAX06 and the FAX06 phantom were replaced at runtime by so-called micro matrices representing segmented trabecular bone, marrow and BSC in 17.65, 30 and 60 µm cubic voxels. The 3D-microCT image-based RBM and BSC equivalent doses for external exposure to photons presented here for the first time for complete human skeletons are in agreement with the results calculated with the three correction factor method and the fluence-to-dose response functions for the same phantoms taking into account the conceptual differences between the different methods. Additionally the microCT image-based results have been compared with corresponding data from earlier studies for other human phantoms. This article is dedicated to Prof. Dr Guenter Drexler from the Laboratório de Ciências Radiológicas, State University of Rio de Janeiro, on the occasion of his 70th birthday.

Automated quantitative 3D analysis of aorta size, morphology, and mural calcification distributions

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kurugol, Sila, E-mail: sila.kurugol@childrens.harvard.edu; Come, Carolyn E.; Diaz, Alejandro A.

Purpose: The purpose of this work is to develop a fully automated pipeline to compute aorta morphology and calcification measures in large cohorts of CT scans that can be used to investigate the potential of these measures as imaging biomarkers of cardiovascular disease. Methods: The first step of the automated pipeline is aorta segmentation. The algorithm the authors propose first detects an initial aorta boundary by exploiting cross-sectional circularity of aorta in axial slices and aortic arch in reformatted oblique slices. This boundary is then refined by a 3D level-set segmentation that evolves the boundary to the location of nearbymore » edges. The authors then detect the aortic calcifications with thresholding and filter out the false positive regions due to nearby high intensity structures based on their anatomical location. The authors extract the centerline and oblique cross sections of the segmented aortas and compute the aorta morphology and calcification measures of the first 2500 subjects from COPDGene study. These measures include volume and number of calcified plaques and measures of vessel morphology such as average cross-sectional area, tortuosity, and arch width. Results: The authors computed the agreement between the algorithm and expert segmentations on 45 CT scans and obtained a closest point mean error of 0.62 ± 0.09 mm and a Dice coefficient of 0.92 ± 0.01. The calcification detection algorithm resulted in an improved true positive detection rate of 0.96 compared to previous work. The measurements of aorta size agreed with the measurements reported in previous work. The initial results showed associations of aorta morphology with calcification and with aging. These results may indicate aorta stiffening and unwrapping with calcification and aging. Conclusions: The authors have developed an objective tool to assess aorta morphology and aortic calcium plaques on CT scans that may be used to provide information about the presence of

Automated quantitative 3D analysis of aorta size, morphology, and mural calcification distributions.

PubMed

Kurugol, Sila; Come, Carolyn E; Diaz, Alejandro A; Ross, James C; Kinney, Greg L; Black-Shinn, Jennifer L; Hokanson, John E; Budoff, Matthew J; Washko, George R; San Jose Estepar, Raul

2015-09-01

The purpose of this work is to develop a fully automated pipeline to compute aorta morphology and calcification measures in large cohorts of CT scans that can be used to investigate the potential of these measures as imaging biomarkers of cardiovascular disease. The first step of the automated pipeline is aorta segmentation. The algorithm the authors propose first detects an initial aorta boundary by exploiting cross-sectional circularity of aorta in axial slices and aortic arch in reformatted oblique slices. This boundary is then refined by a 3D level-set segmentation that evolves the boundary to the location of nearby edges. The authors then detect the aortic calcifications with thresholding and filter out the false positive regions due to nearby high intensity structures based on their anatomical location. The authors extract the centerline and oblique cross sections of the segmented aortas and compute the aorta morphology and calcification measures of the first 2500 subjects from COPDGene study. These measures include volume and number of calcified plaques and measures of vessel morphology such as average cross-sectional area, tortuosity, and arch width. The authors computed the agreement between the algorithm and expert segmentations on 45 CT scans and obtained a closest point mean error of 0.62 ± 0.09 mm and a Dice coefficient of 0.92 ± 0.01. The calcification detection algorithm resulted in an improved true positive detection rate of 0.96 compared to previous work. The measurements of aorta size agreed with the measurements reported in previous work. The initial results showed associations of aorta morphology with calcification and with aging. These results may indicate aorta stiffening and unwrapping with calcification and aging. The authors have developed an objective tool to assess aorta morphology and aortic calcium plaques on CT scans that may be used to provide information about the presence of cardiovascular disease and its clinical impact in

Automated quantitative 3D analysis of aorta size, morphology, and mural calcification distributions

PubMed Central

Kurugol, Sila; Come, Carolyn E.; Diaz, Alejandro A.; Ross, James C.; Kinney, Greg L.; Black-Shinn, Jennifer L.; Hokanson, John E.; Budoff, Matthew J.; Washko, George R.; San Jose Estepar, Raul

2015-01-01

Purpose: The purpose of this work is to develop a fully automated pipeline to compute aorta morphology and calcification measures in large cohorts of CT scans that can be used to investigate the potential of these measures as imaging biomarkers of cardiovascular disease. Methods: The first step of the automated pipeline is aorta segmentation. The algorithm the authors propose first detects an initial aorta boundary by exploiting cross-sectional circularity of aorta in axial slices and aortic arch in reformatted oblique slices. This boundary is then refined by a 3D level-set segmentation that evolves the boundary to the location of nearby edges. The authors then detect the aortic calcifications with thresholding and filter out the false positive regions due to nearby high intensity structures based on their anatomical location. The authors extract the centerline and oblique cross sections of the segmented aortas and compute the aorta morphology and calcification measures of the first 2500 subjects from COPDGene study. These measures include volume and number of calcified plaques and measures of vessel morphology such as average cross-sectional area, tortuosity, and arch width. Results: The authors computed the agreement between the algorithm and expert segmentations on 45 CT scans and obtained a closest point mean error of 0.62 ± 0.09 mm and a Dice coefficient of 0.92 ± 0.01. The calcification detection algorithm resulted in an improved true positive detection rate of 0.96 compared to previous work. The measurements of aorta size agreed with the measurements reported in previous work. The initial results showed associations of aorta morphology with calcification and with aging. These results may indicate aorta stiffening and unwrapping with calcification and aging. Conclusions: The authors have developed an objective tool to assess aorta morphology and aortic calcium plaques on CT scans that may be used to provide information about the presence of cardiovascular

An Effective Post-Filtering Framework for 3-D PET Image Denoising Based on Noise and Sensitivity Characteristics

NASA Astrophysics Data System (ADS)

Kim, Ji Hye; Ahn, Il Jun; Nam, Woo Hyun; Ra, Jong Beom

2015-02-01

Positron emission tomography (PET) images usually suffer from a noticeable amount of statistical noise. In order to reduce this noise, a post-filtering process is usually adopted. However, the performance of this approach is limited because the denoising process is mostly performed on the basis of the Gaussian random noise. It has been reported that in a PET image reconstructed by the expectation-maximization (EM), the noise variance of each voxel depends on its mean value, unlike in the case of Gaussian noise. In addition, we observe that the variance also varies with the spatial sensitivity distribution in a PET system, which reflects both the solid angle determined by a given scanner geometry and the attenuation information of a scanned object. Thus, if a post-filtering process based on the Gaussian random noise is applied to PET images without consideration of the noise characteristics along with the spatial sensitivity distribution, the spatially variant non-Gaussian noise cannot be reduced effectively. In the proposed framework, to effectively reduce the noise in PET images reconstructed by the 3-D ordinary Poisson ordered subset EM (3-D OP-OSEM), we first denormalize an image according to the sensitivity of each voxel so that the voxel mean value can represent its statistical properties reliably. Based on our observation that each noisy denormalized voxel has a linear relationship between the mean and variance, we try to convert this non-Gaussian noise image to a Gaussian noise image. We then apply a block matching 4-D algorithm that is optimized for noise reduction of the Gaussian noise image, and reconvert and renormalize the result to obtain a final denoised image. Using simulated phantom data and clinical patient data, we demonstrate that the proposed framework can effectively suppress the noise over the whole region of a PET image while minimizing degradation of the image resolution.

A new method for automated discontinuity trace mapping on rock mass 3D surface model

NASA Astrophysics Data System (ADS)

Li, Xiaojun; Chen, Jianqin; Zhu, Hehua

2016-04-01

This paper presents an automated discontinuity trace mapping method on a 3D surface model of rock mass. Feature points of discontinuity traces are first detected using the Normal Tensor Voting Theory, which is robust to noisy point cloud data. Discontinuity traces are then extracted from feature points in four steps: (1) trace feature point grouping, (2) trace segment growth, (3) trace segment connection, and (4) redundant trace segment removal. A sensitivity analysis is conducted to identify optimal values for the parameters used in the proposed method. The optimal triangular mesh element size is between 5 cm and 6 cm; the angle threshold in the trace segment growth step is between 70° and 90°; the angle threshold in the trace segment connection step is between 50° and 70°, and the distance threshold should be at least 15 times the mean triangular mesh element size. The method is applied to the excavation face trace mapping of a drill-and-blast tunnel. The results show that the proposed discontinuity trace mapping method is fast and effective and could be used as a supplement to traditional direct measurement of discontinuity traces.

3D temporal subtraction on multislice CT images using nonlinear warping technique

NASA Astrophysics Data System (ADS)

Ishida, Takayuki; Katsuragawa, Shigehiko; Kawashita, Ikuo; Kim, Hyounseop; Itai, Yoshinori; Awai, Kazuo; Li, Qiang; Doi, Kunio

2007-03-01

The detection of very subtle lesions and/or lesions overlapped with vessels on CT images is a time consuming and difficult task for radiologists. In this study, we have developed a 3D temporal subtraction method to enhance interval changes between previous and current multislice CT images based on a nonlinear image warping technique. Our method provides a subtraction CT image which is obtained by subtraction of a previous CT image from a current CT image. Reduction of misregistration artifacts is important in the temporal subtraction method. Therefore, our computerized method includes global and local image matching techniques for accurate registration of current and previous CT images. For global image matching, we selected the corresponding previous section image for each current section image by using 2D cross-correlation between a blurred low-resolution current CT image and a blurred previous CT image. For local image matching, we applied the 3D template matching technique with translation and rotation of volumes of interests (VOIs) which were selected in the current and the previous CT images. The local shift vector for each VOI pair was determined when the cross-correlation value became the maximum in the 3D template matching. The local shift vectors at all voxels were determined by interpolation of shift vectors of VOIs, and then the previous CT image was nonlinearly warped according to the shift vector for each voxel. Finally, the warped previous CT image was subtracted from the current CT image. The 3D temporal subtraction method was applied to 19 clinical cases. The normal background structures such as vessels, ribs, and heart were removed without large misregistration artifacts. Thus, interval changes due to lung diseases were clearly enhanced as white shadows on subtraction CT images.

3D characterization of EMT cell density in developing cardiac cushions using optical coherence tomography (Conference Presentation)

NASA Astrophysics Data System (ADS)

Yu, Siyao; Gu, Shi; Zhao, Xiaowei; Liu, Yehe; Jenkins, Michael W.; Watanabe, Michiko; Rollins, Andrew M.

2017-02-01

Congenital heart defects (CHDs) are the most common birth defect, affecting between 4 and 75 per 1,000 live births depending on the inclusion criteria. Many of these defects can be traced to defects of cardiac cushions, critical structures during development that serve as precursors to many structures in the mature heart, including the atrial and ventricular septa, and all four sets of cardiac valves. Epithelial-mesenchymal transition (EMT) is the process through which cardiac cushions become populated with cells. Altered cushion size or altered cushion cell density has been linked to many forms of CHDs, however, quantitation of cell density in the complex 3D cushion structure poses a significant challenge to conventional histology. Optical coherence tomography (OCT) is a technique capable of 3D imaging of the developing heart, but typically lacks the resolution to differentiate individual cells. Our goal is to develop an algorithm to quantitatively characterize the density of cells in the developing cushion using 3D OCT imaging. First, in a heart volume, the atrioventricular (AV) cushions were manually segmented. Next, all voxel values in the region of interest were pooled together to generate a histogram. Finally, two populations of voxels were classified using either K-means classification, or a Gaussian mixture model (GMM). The voxel population with higher values represents cells in the cushion. To test the algorithm, we imaged and evaluated avian embryonic hearts at looping stages. As expected, our result suggested that the cell density increases with developmental stages. We validated the technique against scoring by expert readers.

Device and methods for "gold standard" registration of clinical 3D and 2D cerebral angiograms

NASA Astrophysics Data System (ADS)

Madan, Hennadii; Likar, Boštjan; Pernuš, Franjo; Å piclin, Žiga

2015-03-01

Translation of any novel and existing 3D-2D image registration methods into clinical image-guidance systems is limited due to lack of their objective validation on clinical image datasets. The main reason is that, besides the calibration of the 2D imaging system, a reference or "gold standard" registration is very difficult to obtain on clinical image datasets. In the context of cerebral endovascular image-guided interventions (EIGIs), we present a calibration device in the form of a headband with integrated fiducial markers and, secondly, propose an automated pipeline comprising 3D and 2D image processing, analysis and annotation steps, the result of which is a retrospective calibration of the 2D imaging system and an optimal, i.e., "gold standard" registration of 3D and 2D images. The device and methods were used to create the "gold standard" on 15 datasets of 3D and 2D cerebral angiograms, whereas each dataset was acquired on a patient undergoing EIGI for either aneurysm coiling or embolization of arteriovenous malformation. The use of the device integrated seamlessly in the clinical workflow of EIGI. While the automated pipeline eliminated all manual input or interactive image processing, analysis or annotation. In this way, the time to obtain the "gold standard" was reduced from 30 to less than one minute and the "gold standard" of 3D-2D registration on all 15 datasets of cerebral angiograms was obtained with a sub-0.1 mm accuracy.

Sparse representation-based volumetric super-resolution algorithm for 3D CT images of reservoir rocks

NASA Astrophysics Data System (ADS)

Li, Zhengji; Teng, Qizhi; He, Xiaohai; Yue, Guihua; Wang, Zhengyong

2017-09-01

The parameter evaluation of reservoir rocks can help us to identify components and calculate the permeability and other parameters, and it plays an important role in the petroleum industry. Until now, computed tomography (CT) has remained an irreplaceable way to acquire the microstructure of reservoir rocks. During the evaluation and analysis, large samples and high-resolution images are required in order to obtain accurate results. Owing to the inherent limitations of CT, however, a large field of view results in low-resolution images, and high-resolution images entail a smaller field of view. Our method is a promising solution to these data collection limitations. In this study, a framework for sparse representation-based 3D volumetric super-resolution is proposed to enhance the resolution of 3D voxel images of reservoirs scanned with CT. A single reservoir structure and its downgraded model are divided into a large number of 3D cubes of voxel pairs and these cube pairs are used to calculate two overcomplete dictionaries and the sparse-representation coefficients in order to estimate the high frequency component. Future more, to better result, a new feature extract method with combine BM4D together with Laplacian filter are introduced. In addition, we conducted a visual evaluation of the method, and used the PSNR and FSIM to evaluate it qualitatively.

Automatic needle segmentation in 3D ultrasound images using 3D improved Hough transform

NASA Astrophysics Data System (ADS)

Zhou, Hua; Qiu, Wu; Ding, Mingyue; Zhang, Songgen

2008-03-01

3D ultrasound (US) is a new technology that can be used for a variety of diagnostic applications, such as obstetrical, vascular, and urological imaging, and has been explored greatly potential in the applications of image-guided surgery and therapy. Uterine adenoma and uterine bleeding are the two most prevalent diseases in Chinese woman, and a minimally invasive ablation system using a needle-like RF button electrode is widely used to destroy tumor cells or stop bleeding. To avoid accidents or death of the patient by inaccurate localizations of the electrode and the tumor position during treatment, 3D US guidance system was developed. In this paper, a new automated technique, the 3D Improved Hough Transform (3DIHT) algorithm, which is potentially fast, accurate, and robust to provide needle segmentation in 3D US image for use of 3D US imaging guidance, was presented. Based on the coarse-fine search strategy and a four parameter representation of lines in 3D space, 3DIHT algorithm can segment needles quickly, accurately and robustly. The technique was evaluated using the 3D US images acquired by scanning a water phantom. The segmentation position deviation of the line was less than 2mm and angular deviation was much less than 2°. The average computational time measured on a Pentium IV 2.80GHz PC computer with a 381×381×250 image was less than 2s.

Automation of serum (1→3)-beta-D-glucan testing allows reliable and rapid discrimination of patients with and without candidemia.

PubMed

Prüller, Florian; Wagner, Jasmin; Raggam, Reinhard B; Hoenigl, Martin; Kessler, Harald H; Truschnig-Wilders, Martie; Krause, Robert

2014-07-01

Testing for (1→3)-beta-D-glucan (BDG) is used for detection of invasive fungal infection. However, current assays lack automation and the ability to conduct rapid single-sample testing. The Fungitell assay was adopted for automation and evaluated using clinical samples from patients with culture-proven candidemia and from culture-negative controls in duplicate. A comparison with the standard assay protocol was made in order to establish analytical specifications. With the automated protocol, the analytical measuring range was 8-2500 pg/ml of BDG, and precision testing resulted in coefficients of variation that ranged from 3.0% to 5.5%. Samples from 15 patients with culture-proven candidemia and 94 culture-negative samples were evaluated. All culture-proven samples showed BDG values >80 pg/ml (mean 1247 pg/ml; range, 116-2990 pg/ml), which were considered positive. Of the 94 culture-negative samples, 92 had BDG values <60 pg/ml (mean, 28 pg/ml), which were considered to be negative, and 2 samples were false-positive (≥80 pg/ml; up to 124 pg/ml). Results could be obtained within 45 min and showed excellent agreement with results obtained with the standard assay protocol. The automated Fungitell assay proved to be reliable and rapid for diagnosis of candidemia. It was demonstrated to be feasible and cost efficient for both single-sample and large-scale testing of serum BDG. Its 1-h time-to-result will allow better support for clinicians in the management of antifungal therapy. © The Author 2014. Published by Oxford University Press on behalf of The International Society for Human and Animal Mycology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

3D deeply supervised network for automated segmentation of volumetric medical images.

PubMed

Dou, Qi; Yu, Lequan; Chen, Hao; Jin, Yueming; Yang, Xin; Qin, Jing; Heng, Pheng-Ann

2017-10-01

While deep convolutional neural networks (CNNs) have achieved remarkable success in 2D medical image segmentation, it is still a difficult task for CNNs to segment important organs or structures from 3D medical images owing to several mutually affected challenges, including the complicated anatomical environments in volumetric images, optimization difficulties of 3D networks and inadequacy of training samples. In this paper, we present a novel and efficient 3D fully convolutional network equipped with a 3D deep supervision mechanism to comprehensively address these challenges; we call it 3D DSN. Our proposed 3D DSN is capable of conducting volume-to-volume learning and inference, which can eliminate redundant computations and alleviate the risk of over-fitting on limited training data. More importantly, the 3D deep supervision mechanism can effectively cope with the optimization problem of gradients vanishing or exploding when training a 3D deep model, accelerating the convergence speed and simultaneously improving the discrimination capability. Such a mechanism is developed by deriving an objective function that directly guides the training of both lower and upper layers in the network, so that the adverse effects of unstable gradient changes can be counteracted during the training procedure. We also employ a fully connected conditional random field model as a post-processing step to refine the segmentation results. We have extensively validated the proposed 3D DSN on two typical yet challenging volumetric medical image segmentation tasks: (i) liver segmentation from 3D CT scans and (ii) whole heart and great vessels segmentation from 3D MR images, by participating two grand challenges held in conjunction with MICCAI. We have achieved competitive segmentation results to state-of-the-art approaches in both challenges with a much faster speed, corroborating the effectiveness of our proposed 3D DSN. Copyright © 2017 Elsevier B.V. All rights reserved.

TH-CD-206-02: BEST IN PHYSICS (IMAGING): 3D Prostate Segmentation in MR Images Using Patch-Based Anatomical Signature

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, X; Jani, A; Rossi, P

Purpose: MRI has shown promise in identifying prostate tumors with high sensitivity and specificity for the detection of prostate cancer. Accurate segmentation of the prostate plays a key role various tasks: to accurately localize prostate boundaries for biopsy needle placement and radiotherapy, to initialize multi-modal registration algorithms or to obtain the region of interest for computer-aided detection of prostate cancer. However, manual segmentation during biopsy or radiation therapy can be time consuming and subject to inter- and intra-observer variation. This study’s purpose it to develop an automated method to address this technical challenge. Methods: We present an automated multi-atlas segmentationmore » for MR prostate segmentation using patch-based label fusion. After an initial preprocessing for all images, all the atlases are non-rigidly registered to a target image. And then, the resulting transformation is used to propagate the anatomical structure labels of the atlas into the space of the target image. The top L similar atlases are further chosen by measuring intensity and structure difference in the region of interest around prostate. Finally, using voxel weighting based on patch-based anatomical signature, the label that the majority of all warped labels predict for each voxel is used for the final segmentation of the target image. Results: This segmentation technique was validated with a clinical study of 13 patients. The accuracy of our approach was assessed using the manual segmentation (gold standard). The mean volume Dice Overlap Coefficient was 89.5±2.9% between our and manual segmentation, which indicate that the automatic segmentation method works well and could be used for 3D MRI-guided prostate intervention. Conclusion: We have developed a new prostate segmentation approach based on the optimal feature learning label fusion framework, demonstrated its clinical feasibility, and validated its accuracy. This segmentation technique

An Automated Treatment Plan Quality Control Tool for Intensity-Modulated Radiation Therapy Using a Voxel-Weighting Factor-Based Re-Optimization Algorithm.

PubMed

Song, Ting; Li, Nan; Zarepisheh, Masoud; Li, Yongbao; Gautier, Quentin; Zhou, Linghong; Mell, Loren; Jiang, Steve; Cerviño, Laura

2016-01-01

Intensity-modulated radiation therapy (IMRT) currently plays an important role in radiotherapy, but its treatment plan quality can vary significantly among institutions and planners. Treatment plan quality control (QC) is a necessary component for individual clinics to ensure that patients receive treatments with high therapeutic gain ratios. The voxel-weighting factor-based plan re-optimization mechanism has been proved able to explore a larger Pareto surface (solution domain) and therefore increase the possibility of finding an optimal treatment plan. In this study, we incorporated additional modules into an in-house developed voxel weighting factor-based re-optimization algorithm, which was enhanced as a highly automated and accurate IMRT plan QC tool (TPS-QC tool). After importing an under-assessment plan, the TPS-QC tool was able to generate a QC report within 2 minutes. This QC report contains the plan quality determination as well as information supporting the determination. Finally, the IMRT plan quality can be controlled by approving quality-passed plans and replacing quality-failed plans using the TPS-QC tool. The feasibility and accuracy of the proposed TPS-QC tool were evaluated using 25 clinically approved cervical cancer patient IMRT plans and 5 manually created poor-quality IMRT plans. The results showed high consistency between the QC report quality determinations and the actual plan quality. In the 25 clinically approved cases that the TPS-QC tool identified as passed, a greater difference could be observed for dosimetric endpoints for organs at risk (OAR) than for planning target volume (PTV), implying that better dose sparing could be achieved in OAR than in PTV. In addition, the dose-volume histogram (DVH) curves of the TPS-QC tool re-optimized plans satisfied the dosimetric criteria more frequently than did the under-assessment plans. In addition, the criteria for unsatisfied dosimetric endpoints in the 5 poor-quality plans could typically be

An Automated Treatment Plan Quality Control Tool for Intensity-Modulated Radiation Therapy Using a Voxel-Weighting Factor-Based Re-Optimization Algorithm

PubMed Central

Song, Ting; Li, Nan; Zarepisheh, Masoud; Li, Yongbao; Gautier, Quentin; Zhou, Linghong; Mell, Loren; Jiang, Steve; Cerviño, Laura

2016-01-01

Intensity-modulated radiation therapy (IMRT) currently plays an important role in radiotherapy, but its treatment plan quality can vary significantly among institutions and planners. Treatment plan quality control (QC) is a necessary component for individual clinics to ensure that patients receive treatments with high therapeutic gain ratios. The voxel-weighting factor-based plan re-optimization mechanism has been proved able to explore a larger Pareto surface (solution domain) and therefore increase the possibility of finding an optimal treatment plan. In this study, we incorporated additional modules into an in-house developed voxel weighting factor-based re-optimization algorithm, which was enhanced as a highly automated and accurate IMRT plan QC tool (TPS-QC tool). After importing an under-assessment plan, the TPS-QC tool was able to generate a QC report within 2 minutes. This QC report contains the plan quality determination as well as information supporting the determination. Finally, the IMRT plan quality can be controlled by approving quality-passed plans and replacing quality-failed plans using the TPS-QC tool. The feasibility and accuracy of the proposed TPS-QC tool were evaluated using 25 clinically approved cervical cancer patient IMRT plans and 5 manually created poor-quality IMRT plans. The results showed high consistency between the QC report quality determinations and the actual plan quality. In the 25 clinically approved cases that the TPS-QC tool identified as passed, a greater difference could be observed for dosimetric endpoints for organs at risk (OAR) than for planning target volume (PTV), implying that better dose sparing could be achieved in OAR than in PTV. In addition, the dose-volume histogram (DVH) curves of the TPS-QC tool re-optimized plans satisfied the dosimetric criteria more frequently than did the under-assessment plans. In addition, the criteria for unsatisfied dosimetric endpoints in the 5 poor-quality plans could typically be

Accelerating IMRT optimization by voxel sampling

NASA Astrophysics Data System (ADS)

Martin, Benjamin C.; Bortfeld, Thomas R.; Castañon, David A.

2007-12-01

This paper presents a new method for accelerating intensity-modulated radiation therapy (IMRT) optimization using voxel sampling. Rather than calculating the dose to the entire patient at each step in the optimization, the dose is only calculated for some randomly selected voxels. Those voxels are then used to calculate estimates of the objective and gradient which are used in a randomized version of a steepest descent algorithm. By selecting different voxels on each step, we are able to find an optimal solution to the full problem. We also present an algorithm to automatically choose the best sampling rate for each structure within the patient during the optimization. Seeking further improvements, we experimented with several other gradient-based optimization algorithms and found that the delta-bar-delta algorithm performs well despite the randomness. Overall, we were able to achieve approximately an order of magnitude speedup on our test case as compared to steepest descent.

Automatic pole-like object modeling via 3D part-based analysis of point cloud

NASA Astrophysics Data System (ADS)

He, Liu; Yang, Haoxiang; Huang, Yuchun

2016-10-01

Pole-like objects, including trees, lampposts and traffic signs, are indispensable part of urban infrastructure. With the advance of vehicle-based laser scanning (VLS), massive point cloud of roadside urban areas becomes applied in 3D digital city modeling. Based on the property that different pole-like objects have various canopy parts and similar trunk parts, this paper proposed the 3D part-based shape analysis to robustly extract, identify and model the pole-like objects. The proposed method includes: 3D clustering and recognition of trunks, voxel growing and part-based 3D modeling. After preprocessing, the trunk center is identified as the point that has local density peak and the largest minimum inter-cluster distance. Starting from the trunk centers, the remaining points are iteratively clustered to the same centers of their nearest point with higher density. To eliminate the noisy points, cluster border is refined by trimming boundary outliers. Then, candidate trunks are extracted based on the clustering results in three orthogonal planes by shape analysis. Voxel growing obtains the completed pole-like objects regardless of overlaying. Finally, entire trunk, branch and crown part are analyzed to obtain seven feature parameters. These parameters are utilized to model three parts respectively and get signal part-assembled 3D model. The proposed method is tested using the VLS-based point cloud of Wuhan University, China. The point cloud includes many kinds of trees, lampposts and other pole-like posters under different occlusions and overlaying. Experimental results show that the proposed method can extract the exact attributes and model the roadside pole-like objects efficiently.

Optofluidic fabrication for 3D-shaped particles

NASA Astrophysics Data System (ADS)

Paulsen, Kevin S.; di Carlo, Dino; Chung, Aram J.

2015-04-01

Complex three-dimensional (3D)-shaped particles could play unique roles in biotechnology, structural mechanics and self-assembly. Current methods of fabricating 3D-shaped particles such as 3D printing, injection moulding or photolithography are limited because of low-resolution, low-throughput or complicated/expensive procedures. Here, we present a novel method called optofluidic fabrication for the generation of complex 3D-shaped polymer particles based on two coupled processes: inertial flow shaping and ultraviolet (UV) light polymerization. Pillars within fluidic platforms are used to deterministically deform photosensitive precursor fluid streams. The channels are then illuminated with patterned UV light to polymerize the photosensitive fluid, creating particles with multi-scale 3D geometries. The fundamental advantages of optofluidic fabrication include high-resolution, multi-scalability, dynamic tunability, simple operation and great potential for bulk fabrication with full automation. Through different combinations of pillar configurations, flow rates and UV light patterns, an infinite set of 3D-shaped particles is available, and a variety are demonstrated.

Intuitive Terrain Reconstruction Using Height Observation-Based Ground Segmentation and 3D Object Boundary Estimation

PubMed Central

Song, Wei; Cho, Kyungeun; Um, Kyhyun; Won, Chee Sun; Sim, Sungdae

2012-01-01

Mobile robot operators must make rapid decisions based on information about the robot’s surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produced a voxel map and textured mesh from the 2D and 3D datasets collected by a robot’s array of sensors, but some upper parts of objects are beyond the sensors’ measurements and these parts are missing in the terrain reconstruction result. This result is an incomplete terrain model. To solve this problem, we present a new ground segmentation method to detect non-ground data in the reconstructed voxel map. Our method uses height histograms to estimate the ground height range, and a Gibbs-Markov random field model to refine the segmentation results. To reconstruct a complete terrain model of the 3D environment, we develop a 3D boundary estimation method for non-ground objects. We apply a boundary detection technique to the 2D image, before estimating and refining the actual height values of the non-ground vertices in the reconstructed textured mesh. Our proposed methods were tested in an outdoor environment in which trees and buildings were not completely sensed. Our results show that the time required for ground segmentation is faster than that for data sensing, which is necessary for a real-time approach. In addition, those parts of objects that were not sensed are accurately recovered to retrieve their real-world appearances. PMID:23235454

Intuitive terrain reconstruction using height observation-based ground segmentation and 3D object boundary estimation.

PubMed

Song, Wei; Cho, Kyungeun; Um, Kyhyun; Won, Chee Sun; Sim, Sungdae

2012-12-12

Mobile robot operators must make rapid decisions based on information about the robot's surrounding environment. This means that terrain modeling and photorealistic visualization are required for the remote operation of mobile robots. We have produced a voxel map and textured mesh from the 2D and 3D datasets collected by a robot's array of sensors, but some upper parts of objects are beyond the sensors' measurements and these parts are missing in the terrain reconstruction result. This result is an incomplete terrain model. To solve this problem, we present a new ground segmentation method to detect non-ground data in the reconstructed voxel map. Our method uses height histograms to estimate the ground height range, and a Gibbs-Markov random field model to refine the segmentation results. To reconstruct a complete terrain model of the 3D environment, we develop a 3D boundary estimation method for non-ground objects. We apply a boundary detection technique to the 2D image, before estimating and refining the actual height values of the non-ground vertices in the reconstructed textured mesh. Our proposed methods were tested in an outdoor environment in which trees and buildings were not completely sensed. Our results show that the time required for ground segmentation is faster than that for data sensing, which is necessary for a real-time approach. In addition, those parts of objects that were not sensed are accurately recovered to retrieve their real-world appearances.

Validation of the Gatortail method for accurate sizing of pulmonary vessels from 3D medical images.

PubMed

O'Dell, Walter G; Gormaley, Anne K; Prida, David A

2017-12-01

, representing vessel diameters ranging from 1.2 to 7 mm. The linear regression fit gave a slope of 1.056 and an R 2 value of 0.989. These three metrics reflect superior agreement of the radii estimates relative to previously published results over all sizes tested. Sizing via matched Gaussian filters resulted in size underestimates of >33% over all three test vessels, while the tubularity-metric matching exhibited a sizing uncertainty of >50%. In the human chest CT data set, the vessel voxel intensity profiles with and without branch model optimization showed excellent agreement and improvement in the objective measure of image similarity. Gatortail has been demonstrated to be an automated, objective, accurate and robust method for sizing of vessels in 3D non-invasively from chest CT scans. We anticipate that Gatortail, an image-based approach to automatically compute estimates of blood vessel radii and trajectories from 3D medical images, will facilitate future quantitative evaluation of vascular response to disease and environmental insult and improve understanding of the biological mechanisms underlying vascular disease processes. © 2017 American Association of Physicists in Medicine.

Investigating structural brain changes of dehydration using voxel-based morphometry.

PubMed

Streitbürger, Daniel-Paolo; Möller, Harald E; Tittgemeyer, Marc; Hund-Georgiadis, Margret; Schroeter, Matthias L; Mueller, Karsten

2012-01-01

Dehydration can affect the volume of brain structures, which might imply a confound in volumetric and morphometric studies of normal or diseased brain. Six young, healthy volunteers were repeatedly investigated using three-dimensional T(1)-weighted magnetic resonance imaging during states of normal hydration, hyperhydration, and dehydration to assess volume changes in gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). The datasets were analyzed using voxel-based morphometry (VBM), a widely used voxel-wise statistical analysis tool, FreeSurfer, a fully automated volumetric segmentation measure, and SIENAr a longitudinal brain-change detection algorithm. A significant decrease of GM and WM volume associated with dehydration was found in various brain regions, most prominently, in temporal and sub-gyral parietal areas, in the left inferior orbito-frontal region, and in the extra-nuclear region. Moreover, we found consistent increases in CSF, that is, an expansion of the ventricular system affecting both lateral ventricles, the third, and the fourth ventricle. Similar degrees of shrinkage in WM volume and increase of the ventricular system have been reported in studies of mild cognitive impairment or Alzheimer's disease during disease progression. Based on these findings, a potential confound in GM and WM or ventricular volume studies due to the subjects' hydration state cannot be excluded and should be appropriately addressed in morphometric studies of the brain.

Investigating Structural Brain Changes of Dehydration Using Voxel-Based Morphometry

PubMed Central

Streitbürger, Daniel-Paolo; Möller, Harald E.; Tittgemeyer, Marc; Hund-Georgiadis, Margret; Schroeter, Matthias L.; Mueller, Karsten

2012-01-01

Dehydration can affect the volume of brain structures, which might imply a confound in volumetric and morphometric studies of normal or diseased brain. Six young, healthy volunteers were repeatedly investigated using three-dimensional T 1-weighted magnetic resonance imaging during states of normal hydration, hyperhydration, and dehydration to assess volume changes in gray matter (GM), white matter (WM), and cerebrospinal fluid (CSF). The datasets were analyzed using voxel-based morphometry (VBM), a widely used voxel-wise statistical analysis tool, FreeSurfer, a fully automated volumetric segmentation measure, and SIENAr a longitudinal brain-change detection algorithm. A significant decrease of GM and WM volume associated with dehydration was found in various brain regions, most prominently, in temporal and sub-gyral parietal areas, in the left inferior orbito-frontal region, and in the extra-nuclear region. Moreover, we found consistent increases in CSF, that is, an expansion of the ventricular system affecting both lateral ventricles, the third, and the fourth ventricle. Similar degrees of shrinkage in WM volume and increase of the ventricular system have been reported in studies of mild cognitive impairment or Alzheime s disease during disease progression. Based on these findings, a potential confound in GM and WM or ventricular volume studies due to the subjects’ hydration state cannot be excluded and should be appropriately addressed in morphometric studies of the brain. PMID:22952926

Fabricating 3D figurines with personalized faces.

PubMed

Tena, J Rafael; Mahler, Moshe; Beeler, Thabo; Grosse, Max; Hengchin Yeh; Matthews, Iain

2013-01-01

We present a semi-automated system for fabricating figurines with faces that are personalised to the individual likeness of the customer. The efficacy of the system has been demonstrated by commercial deployments at Walt Disney World Resort and Star Wars Celebration VI in Orlando Florida. Although the system is semi automated, human intervention is limited to a few simple tasks to maintain the high throughput and consistent quality required for commercial application. In contrast to existing systems that fabricate custom heads that are assembled to pre-fabricated plastic bodies, our system seamlessly integrates 3D facial data with a predefined figurine body into a unique and continuous object that is fabricated as a single piece. The combination of state-of-the-art 3D capture, modelling, and printing that are the core of our system provide the flexibility to fabricate figurines whose complexity is only limited by the creativity of the designer.

Real-time 3D adaptive filtering for portable imaging systems

NASA Astrophysics Data System (ADS)

Bockenbach, Olivier; Ali, Murtaza; Wainwright, Ian; Nadeski, Mark

2015-03-01

Portable imaging devices have proven valuable for emergency medical services both in the field and hospital environments and are becoming more prevalent in clinical settings where the use of larger imaging machines is impractical. 3D adaptive filtering is one of the most advanced techniques aimed at noise reduction and feature enhancement, but is computationally very demanding and hence often not able to run with sufficient performance on a portable platform. In recent years, advanced multicore DSPs have been introduced that attain high processing performance while maintaining low levels of power dissipation. These processors enable the implementation of complex algorithms like 3D adaptive filtering, improving the image quality of portable medical imaging devices. In this study, the performance of a 3D adaptive filtering algorithm on a digital signal processor (DSP) is investigated. The performance is assessed by filtering a volume of size 512x256x128 voxels sampled at a pace of 10 MVoxels/sec.

Vel-IO 3D: A tool for 3D velocity model construction, optimization and time-depth conversion in 3D geological modeling workflow

NASA Astrophysics Data System (ADS)

Maesano, Francesco E.; D'Ambrogi, Chiara

2017-02-01

We present Vel-IO 3D, a tool for 3D velocity model creation and time-depth conversion, as part of a workflow for 3D model building. The workflow addresses the management of large subsurface dataset, mainly seismic lines and well logs, and the construction of a 3D velocity model able to describe the variation of the velocity parameters related to strong facies and thickness variability and to high structural complexity. Although it is applicable in many geological contexts (e.g. foreland basins, large intermountain basins), it is particularly suitable in wide flat regions, where subsurface structures have no surface expression. The Vel-IO 3D tool is composed by three scripts, written in Python 2.7.11, that automate i) the 3D instantaneous velocity model building, ii) the velocity model optimization, iii) the time-depth conversion. They determine a 3D geological model that is consistent with the primary geological constraints (e.g. depth of the markers on wells). The proposed workflow and the Vel-IO 3D tool have been tested, during the EU funded Project GeoMol, by the construction of the 3D geological model of a flat region, 5700 km2 in area, located in the central part of the Po Plain. The final 3D model showed the efficiency of the workflow and Vel-IO 3D tool in the management of large amount of data both in time and depth domain. A 4 layer-cake velocity model has been applied to a several thousand (5000-13,000 m) thick succession, with 15 horizons from Triassic up to Pleistocene, complicated by a Mesozoic extensional tectonics and by buried thrusts related to Southern Alps and Northern Apennines.

The Bubble Box: Towards an Automated Visual Sensor for 3D Analysis and Characterization of Marine Gas Release Sites.

PubMed

Jordt, Anne; Zelenka, Claudius; von Deimling, Jens Schneider; Koch, Reinhard; Köser, Kevin

2015-12-05

Several acoustic and optical techniques have been used for characterizing natural and anthropogenic gas leaks (carbon dioxide, methane) from the ocean floor. Here, single-camera based methods for bubble stream observation have become an important tool, as they help estimating flux and bubble sizes under certain assumptions. However, they record only a projection of a bubble into the camera and therefore cannot capture the full 3D shape, which is particularly important for larger, non-spherical bubbles. The unknown distance of the bubble to the camera (making it appear larger or smaller than expected) as well as refraction at the camera interface introduce extra uncertainties. In this article, we introduce our wide baseline stereo-camera deep-sea sensor bubble box that overcomes these limitations, as it observes bubbles from two orthogonal directions using calibrated cameras. Besides the setup and the hardware of the system, we discuss appropriate calibration and the different automated processing steps deblurring, detection, tracking, and 3D fitting that are crucial to arrive at a 3D ellipsoidal shape and rise speed of each bubble. The obtained values for single bubbles can be aggregated into statistical bubble size distributions or fluxes for extrapolation based on diffusion and dissolution models and large scale acoustic surveys. We demonstrate and evaluate the wide baseline stereo measurement model using a controlled test setup with ground truth information.

The Bubble Box: Towards an Automated Visual Sensor for 3D Analysis and Characterization of Marine Gas Release Sites

PubMed Central

Jordt, Anne; Zelenka, Claudius; Schneider von Deimling, Jens; Koch, Reinhard; Köser, Kevin

2015-01-01

Several acoustic and optical techniques have been used for characterizing natural and anthropogenic gas leaks (carbon dioxide, methane) from the ocean floor. Here, single-camera based methods for bubble stream observation have become an important tool, as they help estimating flux and bubble sizes under certain assumptions. However, they record only a projection of a bubble into the camera and therefore cannot capture the full 3D shape, which is particularly important for larger, non-spherical bubbles. The unknown distance of the bubble to the camera (making it appear larger or smaller than expected) as well as refraction at the camera interface introduce extra uncertainties. In this article, we introduce our wide baseline stereo-camera deep-sea sensor bubble box that overcomes these limitations, as it observes bubbles from two orthogonal directions using calibrated cameras. Besides the setup and the hardware of the system, we discuss appropriate calibration and the different automated processing steps deblurring, detection, tracking, and 3D fitting that are crucial to arrive at a 3D ellipsoidal shape and rise speed of each bubble. The obtained values for single bubbles can be aggregated into statistical bubble size distributions or fluxes for extrapolation based on diffusion and dissolution models and large scale acoustic surveys. We demonstrate and evaluate the wide baseline stereo measurement model using a controlled test setup with ground truth information. PMID:26690168

Image-Based 3D Face Modeling System

NASA Astrophysics Data System (ADS)

Park, In Kyu; Zhang, Hui; Vezhnevets, Vladimir

2005-12-01

This paper describes an automatic system for 3D face modeling using frontal and profile images taken by an ordinary digital camera. The system consists of four subsystems including frontal feature detection, profile feature detection, shape deformation, and texture generation modules. The frontal and profile feature detection modules automatically extract the facial parts such as the eye, nose, mouth, and ear. The shape deformation module utilizes the detected features to deform the generic head mesh model such that the deformed model coincides with the detected features. A texture is created by combining the facial textures augmented from the input images and the synthesized texture and mapped onto the deformed generic head model. This paper provides a practical system for 3D face modeling, which is highly automated by aggregating, customizing, and optimizing a bunch of individual computer vision algorithms. The experimental results show a highly automated process of modeling, which is sufficiently robust to various imaging conditions. The whole model creation including all the optional manual corrections takes only 2[InlineEquation not available: see fulltext.]3 minutes.

A new leg voxel model in two different positions for simulation of the non-uniform distribution of (241)Am in leg bones.

PubMed

Khalaf, Majid; Brey, Richard R; Meldrum, Jeff

2013-01-01

A new leg voxel model in two different positions (straight and bent) has been developed for in vivo measurement calibration purposes. This voxel phantom is a representation of a human leg that may provide a substantial enhancement to Monte Carlo modeling because it more accurately models different geometric leg positions and the non-uniform distribution of Am throughout the leg bones instead of assuming a one-position geometry and a uniform distribution of radionuclides. This was accomplished by performing a radiochemical analysis on small sections of the leg bones from the U.S. Transuranium and Uranium Registries (USTUR) case 0846. USTUR case 0846 represents an individual who was repeatedly contaminated by Am via chronic inhalation. To construct the voxel model, high resolution (2 mm) computed tomography (CT) images of the USTUR case 0846 leg were obtained in different positions. Thirty-six (36) objects (universes) were segmented manually from the CT images using 3D-Doctor software. Bones were divided into 30 small sections with an assigned weight exactly equal to the weight of bone sections obtained from radiochemical analysis of the USTUR case 0846 leg. The segmented images were then converted into a boundary file, and the Human Monitoring Laboratory (HML) voxelizer was used to convert the boundary file into the leg voxel phantom. Excluding the surrounding air regions, the straight leg phantom consists of 592,023 voxels, while the bent leg consists of 337,567 voxels. The resulting leg voxel model is now ready for use as an MCNPX input file to simulate in vivo measurement of bone-seeking radionuclides.

Implementation of 3 T Lactate-Edited 3D 1H MR Spectroscopic Imaging with Flyback Echo-Planar Readout for Gliomas Patients

PubMed Central

Chen, Albert P.; Zierhut, Matthew L.; Ozturk-Isik, Esin; Vigneron, Daniel B.; Nelson, Sarah J.

2010-01-01

The purpose of this study was to implement a new lactate-edited 3D 1H magnetic resonance spectroscopic imaging (MRSI) sequence at 3 T and demonstrate the feasibility of using this sequence for measuring lactate in patients with gliomas. A 3D PRESS MRSI sequence incorporating shortened, high bandwidth 180° pulses, new dual BASING lactate-editing pulses, high bandwidth very selective suppression (VSS) pulses and a flyback echo-planar readout was implemented at 3 T. Over-prescription factor of PRESS voxels was optimized using phantom to minimize chemical shift artifacts. The lactate-edited flyback sequence was compared with lactate-edited MRSI using conventional elliptical k-space sampling in a phantom and volunteers, and then applied to patients with gliomas. The results demonstrated the feasibility of detecting lactate within a short scan time of 9.5 min in both phantoms and patients. Over-prescription of voxels gave less chemical shift artifacts allowing detection of lactate on the majority of the selected volume. The normalized SNR of brain metabolites using the flyback encoding were comparable to the SNR of brain metabolites using conventional phase encoding MRSI. The specialized lactate-edited 3D MRSI sequence was able to detect lactate in brain tumor patients at 3 T. The implementation of this technique means that brain lactate can be evaluated in a routine clinical setting to study its potential as a marker for prognosis and response to therapy. PMID:20652745

Transthoracic 3D echocardiographic left heart chamber quantification in patients with bicuspid aortic valve disease.

PubMed

van den Hoven, Allard T; Mc-Ghie, Jackie S; Chelu, Raluca G; Duijnhouwer, Anthonie L; Baggen, Vivan J M; Coenen, Adriaan; Vletter, Wim B; Dijkshoorn, Marcel L; van den Bosch, Annemien E; Roos-Hesselink, Jolien W

2017-12-01

Integration of volumetric heart chamber quantification by 3D echocardiography into clinical practice has been hampered by several factors which a new fully automated algorithm (Left Heart Model, (LHM)) may help overcome. This study therefore aims to evaluate the feasibility and accuracy of the LHM software in quantifying left atrial and left ventricular volumes and left ventricular ejection fraction in a cohort of patients with a bicuspid aortic valve. Patients with a bicuspid aortic valve were prospectively included. All patients underwent 2D and 3D transthoracic echocardiography and computed tomography. Left atrial and ventricular volumes were obtained using the automated program, which did not require manual contour detection. For comparison manual and semi-automated measurements were performed using conventional 2D and 3D datasets. 53 patients were included, in four of those patients no 3D dataset could be acquired. Additionally, 12 patients were excluded based on poor imaging quality. Left ventricular end-diastolic and end-systolic volumes and ejection fraction calculated by the LHM correlated well with manual 2D and 3D measurements (Pearson's r between 0.43 and 0.97, p < 0.05). Left atrial volume (LAV) also correlated significantly although LHM did estimate larger LAV compared to both 2DE and 3DE (Pearson's r between 0.61 and 0.81, p < 0.01). The fully automated software works well in a real-world setting and helps to overcome some of the major hurdles in integrating 3D analysis into daily practice, as it is user-independent and highly reproducible in a group of patients with a clearly defined and well-studied valvular abnormality.

Finite-difference method Stokes solver (FDMSS) for 3D pore geometries: Software development, validation and case studies

NASA Astrophysics Data System (ADS)

Gerke, Kirill M.; Vasilyev, Roman V.; Khirevich, Siarhei; Collins, Daniel; Karsanina, Marina V.; Sizonenko, Timofey O.; Korost, Dmitry V.; Lamontagne, Sébastien; Mallants, Dirk

2018-05-01

Permeability is one of the fundamental properties of porous media and is required for large-scale Darcian fluid flow and mass transport models. Whilst permeability can be measured directly at a range of scales, there are increasing opportunities to evaluate permeability from pore-scale fluid flow simulations. We introduce the free software Finite-Difference Method Stokes Solver (FDMSS) that solves Stokes equation using a finite-difference method (FDM) directly on voxelized 3D pore geometries (i.e. without meshing). Based on explicit convergence studies, validation on sphere packings with analytically known permeabilities, and comparison against lattice-Boltzmann and other published FDM studies, we conclude that FDMSS provides a computationally efficient and accurate basis for single-phase pore-scale flow simulations. By implementing an efficient parallelization and code optimization scheme, permeability inferences can now be made from 3D images of up to 109 voxels using modern desktop computers. Case studies demonstrate the broad applicability of the FDMSS software for both natural and artificial porous media.

Application of 3-D imaging sensor for tracking minipigs in the open field test.

PubMed

Kulikov, Victor A; Khotskin, Nikita V; Nikitin, Sergey V; Lankin, Vasily S; Kulikov, Alexander V; Trapezov, Oleg V

2014-09-30

The minipig is a promising model in neurobiology and psychopharmacology. However, automated tracking of minipig behavior is still unresolved problem. The study was carried out on white, agouti and black (or spotted) minipiglets (n=108) bred in the Institute of Cytology and Genetics. New method of automated tracking of minipig behavior is based on Microsoft Kinect 3-D image sensor and the 3-D image reconstruction with EthoStudio software. The algorithms of distance run and time in the center evaluation were adapted for 3-D image data and new algorithm of vertical activity quantification was developed. The 3-D imaging system successfully detects white, black, spotted and agouti pigs in the open field test (OFT). No effect of sex or color on horizontal (distance run), vertical activities and time in the center was shown. Agouti pigs explored the arena more intensive than white or black animals, respectively. The OFT behavioral traits were compared with the fear reaction to experimenter. Time in the center of the OFT was positively correlated with fear reaction rank (ρ=0.21, p<0.05). Black pigs were significantly more fearful compared with white or agouti animals. The 3-D imaging system has three advantages over existing automated tracking systems: it avoids perspective distortion, distinguishes animals any color from any background and automatically evaluates vertical activity. The 3-D imaging system can be successfully applied for automated measurement of minipig behavior in neurobiological and psychopharmacological experiments. Copyright © 2014 Elsevier B.V. All rights reserved.

A novel Hessian based algorithm for rat kidney glomerulus detection in 3D MRI

NASA Astrophysics Data System (ADS)

Zhang, Min; Wu, Teresa; Bennett, Kevin M.

2015-03-01

The glomeruli of the kidney perform the key role of blood filtration and the number of glomeruli in a kidney is correlated with susceptibility to chronic kidney disease and chronic cardiovascular disease. This motivates the development of new technology using magnetic resonance imaging (MRI) to measure the number of glomeruli and nephrons in vivo. However, there is currently a lack of computationally efficient techniques to perform fast, reliable and accurate counts of glomeruli in MR images due to the issues inherent in MRI, such as acquisition noise, partial volume effects (the mixture of several tissue signals in a voxel) and bias field (spatial intensity inhomogeneity). Such challenges are particularly severe because the glomeruli are very small, (in our case, a MRI image is ~16 million voxels, each glomerulus is in the size of 8~20 voxels), and the number of glomeruli is very large. To address this, we have developed an efficient Hessian based Difference of Gaussians (HDoG) detector to identify the glomeruli on 3D rat MR images. The image is first smoothed via DoG followed by the Hessian process to pre-segment and delineate the boundary of the glomerulus candidates. This then provides a basis to extract regional features used in an unsupervised clustering algorithm, completing segmentation by removing the false identifications occurred in the pre-segmentation. The experimental results show that Hessian based DoG has the potential to automatically detect glomeruli,from MRI in 3D, enabling new measurements of renal microstructure and pathology in preclinical and clinical studies.

An Effective Algorithm Research of Scenario Voxelization Organization and Occlusion Culling

NASA Astrophysics Data System (ADS)

Lai, Guangling; Ding, Lu; Qin, Zhiyuan; Tong, Xiaochong

2016-11-01

Compared with the traditional triangulation approaches, the voxelized point cloud data can reduce the sensitivity of scenario and complexity of calculation. While on the base of the point cloud data, implementation scenario organization could be accomplishment by subtle voxel, but it will add more memory consumption. Therefore, an effective voxel representation method is very necessary. At present, the specific study of voxel visualization algorithm is less. This paper improved the ray tracing algorithm by the characteristics of voxel configuration. Firstly, according to the scope of point cloud data, determined the scope of the pixels on the screen. Then, calculated the light vector came from each pixel. Lastly, used the rules of voxel configuration to calculate all the voxel penetrated through by light. The voxels closest to viewpoint were named visible ones, the rest were all obscured ones. This experimental showed that the method could realize voxelization organization and voxel occlusion culling of implementation scenario efficiently, and increased the render efficiency.

3D-CDTI User Manual v2.1

NASA Technical Reports Server (NTRS)

Johnson, Walter; Battiste, Vernol

2016-01-01

The 3D-Cockpit Display of Traffic Information (3D-CDTI) is a flight deck tool that presents aircrew with: proximal traffic aircraft location, their current status and flight plan data; strategic conflict detection and alerting; automated conflict resolution strategies; the facility to graphically plan manual route changes; time-based, in-trail spacing on approach. The CDTI is manipulated via a touchpad on the flight deck, and by mouse when presented as part of a desktop flight simulator.

Optic disc boundary segmentation from diffeomorphic demons registration of monocular fundus image sequences versus 3D visualization of stereo fundus image pairs for automated early stage glaucoma assessment

NASA Astrophysics Data System (ADS)

Gatti, Vijay; Hill, Jason; Mitra, Sunanda; Nutter, Brian

2014-03-01

Despite the current availability in resource-rich regions of advanced technologies in scanning and 3-D imaging in current ophthalmology practice, world-wide screening tests for early detection and progression of glaucoma still consist of a variety of simple tools, including fundus image-based parameters such as CDR (cup to disc diameter ratio) and CAR (cup to disc area ratio), especially in resource -poor regions. Reliable automated computation of the relevant parameters from fundus image sequences requires robust non-rigid registration and segmentation techniques. Recent research work demonstrated that proper non-rigid registration of multi-view monocular fundus image sequences could result in acceptable segmentation of cup boundaries for automated computation of CAR and CDR. This research work introduces a composite diffeomorphic demons registration algorithm for segmentation of cup boundaries from a sequence of monocular images and compares the resulting CAR and CDR values with those computed manually by experts and from 3-D visualization of stereo pairs. Our preliminary results show that the automated computation of CDR and CAR from composite diffeomorphic segmentation of monocular image sequences yield values comparable with those from the other two techniques and thus may provide global healthcare with a cost-effective yet accurate tool for management of glaucoma in its early stage.

Fiducial-based fusion of 3D dental models with magnetic resonance imaging.

PubMed

Abdi, Amir H; Hannam, Alan G; Fels, Sidney

2018-04-16

Magnetic resonance imaging (MRI) is widely used in study of maxillofacial structures. While MRI is the modality of choice for soft tissues, it fails to capture hard tissues such as bone and teeth. Virtual dental models, acquired by optical 3D scanners, are becoming more accessible for dental practice and are starting to replace the conventional dental impressions. The goal of this research is to fuse the high-resolution 3D dental models with MRI to enhance the value of imaging for applications where detailed analysis of maxillofacial structures are needed such as patient examination, surgical planning, and modeling. A subject-specific dental attachment was digitally designed and 3D printed based on the subject's face width and dental anatomy. The attachment contained 19 semi-ellipsoidal concavities in predetermined positions where oil-based ellipsoidal fiducial markers were later placed. The MRI was acquired while the subject bit on the dental attachment. The spatial position of the center of mass of each fiducial in the resultant MR Image was calculated by averaging its voxels' spatial coordinates. The rigid transformation to fuse dental models to MRI was calculated based on the least squares mapping of corresponding fiducials and solved via singular-value decomposition. The target registration error (TRE) of the proposed fusion process, calculated in a leave-one-fiducial-out fashion, was estimated at 0.49 mm. The results suggest that 6-9 fiducials suffice to achieve a TRE of equal to half the MRI voxel size. Ellipsoidal oil-based fiducials produce distinguishable intensities in MRI and can be used as registration fiducials. The achieved accuracy of the proposed approach is sufficient to leverage the merged 3D dental models with the MRI data for a finer analysis of the maxillofacial structures where complete geometry models are needed.

A voxel visualization and analysis system based on AutoCAD

NASA Astrophysics Data System (ADS)

Marschallinger, Robert

1996-05-01

A collection of AutoLISP programs is presented which enable the visualization and analysis of voxel models by AutoCAD rel. 12/rel. 13. The programs serve as an interactive, graphical front end for manipulating the results of three-dimensional modeling software producing block estimation data. ASCII data files describing geometry and attributes per estimation block are imported and stored as a voxel array. Each voxel may contain multiple attributes, therefore different parameters may be incorporated in one voxel array. Voxel classification is implemented on a layer basis providing flexible treatment of voxel classes such as recoloring, peeling, or volumetry. A versatile clipping tool enables slicing voxel arrays according to combinations of three perpendicular clipping planes. The programs feature an up-to-date, graphical user interface for user-friendly operation by non AutoCAD specialists.

Towards next generation 3D cameras

NASA Astrophysics Data System (ADS)

Gupta, Mohit

2017-03-01

We are in the midst of a 3D revolution. Robots enabled by 3D cameras are beginning to autonomously drive cars, perform surgeries, and manage factories. However, when deployed in the real-world, these cameras face several challenges that prevent them from measuring 3D shape reliably. These challenges include large lighting variations (bright sunlight to dark night), presence of scattering media (fog, body tissue), and optically complex materials (metal, plastic). Due to these factors, 3D imaging is often the bottleneck in widespread adoption of several key robotics technologies. I will talk about our work on developing 3D cameras based on time-of-flight and active triangulation that addresses these long-standing problems. This includes designing `all-weather' cameras that can perform high-speed 3D scanning in harsh outdoor environments, as well as cameras that recover shape of objects with challenging material properties. These cameras are, for the first time, capable of measuring detailed (<100 microns resolution) scans in extremely demanding scenarios with low-cost components. Several of these cameras are making a practical impact in industrial automation, being adopted in robotic inspection and assembly systems.

Evaluation of right ventricular function by coronary computed tomography angiography using a novel automated 3D right ventricle volume segmentation approach: a validation study.