Computers in Biology and Medicine

Published by Elsevier
Print ISSN: 0010-4825
The velocity field and deposition fraction of the particles in the trachea and the first third generations of tracheobronchial tree are investigated with CFD simulation. The air flow rate of trachea is considered to be in the range of 15-60l/min in accordance to four different activity levels of male adults. A physiologically realistic dichotomic airway bifurcation geometry with structured hexahedral meshes are constructed. The simulations with different hexahedral mesh densities have shown that the grid independent results will be reached with the average dimensionless distance of the first cell to the walls of y(+)≈0.5. The deposition fraction graph for particles in the range of 0.1-10μm diameter has a minimum in the range of 0.1-1μm particle diameter and after that it increases for larger particles. The results of the simulations under different breathing pattern have shown that deposition fraction significantly increases at higher Reynolds and Stokes numbers.
While advances in statistical methods allow greater insight into the characteristics of diagnostic tests and of raters, researchers frequently rely on incomplete or inappropriate indices of performance. Lack of available computer software is probably an important barrier to optimal use of data collected to evaluate diagnostic tests and agreement between raters. A spreadsheet has been designed to provide comprehensive statistics for the assessment of diagnostic tests and inter-rater reliability when these investigations yield data that can be summarized in a 2x2 table. As well as a wide range of indices of test or rater performance, confidence intervals for these quantities are also calculated by the spreadsheet.
The suitability and performance characteristics of a recently introduced computer-controlled laboratory workstation (Biomek 1000) for use in automating sample transfer and reagent additions in radioimmunoassay techniques were assessed. The system is based on the use of disposable tips and, therefore, reduces any possible sample carry-over and eliminates the need for priming with the subsequent reduction in cost of reagents. However, the machine lacks the useful option of liquid-level sensing facility. Acceptable technical performance in terms of precision, accuracy and throughput was obtained with the Biomek 1000 which complied with international recommendations on the safety of hospital laboratory equipment.
SPECT images using radiopharmaceuticals are limited by noise caused by both random and systematic uncertainties. All the efforts so far have been directed only to minimize the random uncertainty and no attempt has ever been made to minimize the noise due to systematic uncertainty. As these radiopharmaceuticals encounter many systematic uncertainties during their formation, we constructed the covariance matrix with some of these systematic uncertainties for the gamma count rate of (113m)In. We describe the algorithm we have developed based on the technique of determinant inequalities and the concept of minimization of mutual information to process the covariance matrix element by element to minimize the noise caused by systematic uncertainty in the SPECT imaging of (113m)In and its utility to experimentalists to design and improve their process of measurement and instrumentation.
The present work aims at automatic identification of various sleep stages like, sleep stages 1, 2, slow wave sleep (sleep stages 3 and 4), REM sleep and wakefulness from single channel EEG signal. Automatic scoring of sleep stages was performed with the help of pattern recognition technique which involves feature extraction, selection and finally classification. Total 39 numbers of features from time domain, frequency domain and from non-linear analysis were extracted. After extraction of features, SVM based recursive feature elimination (RFE) technique was used to find the optimum number of feature subset which can provide significant classification performance with reduced number of features for the five different sleep stages. Finally for classification, binary SVMs were combined with one-against-all (OAA) strategy. Careful extraction and selection of optimum feature subset helped to reduce the classification error to 8.9% for training dataset, validated by k-fold cross-validation (CV) technique and 10.61% in the case of independent testing dataset. Agreement of the estimated sleep stages with those obtained by expert scoring for all sleep stages of training dataset was 0.877 and for independent testing dataset it was 0.8572. The proposed ensemble SVM-based method could be used as an efficient and cost-effective method for sleep staging with the advantage of reducing stress and burden imposed on subjects.
While most of the methods for quantitative regional cerebral blood flow (rCBF) determination in man requires expensive fast devices, a method is proposed using single photon emission computed tomography with a conventional rotating gamma camera and 133Xe inhalation. It is tested using a computer simulation of a cerebral exam and a simplified CBF map as a model. The results obtained show that this method is relevant and can be tested in clinical studies.
Currently, the Amersham caesium-137 afterloading system is widely used for gynecological treatment of tumors in uterine cervix. This paper introduces an expert system to determine the time of exposure of an Amersham afterloading system based on different combinations of applicator sources. The efficiency of the expert system achieves 93% of the clinical decisions taken by physicians. It is evaluated by both the experimental results and the actual clinical decisions.
Calpain-10 (CAPN10) is a cysteine protease that is activated by intracellular calcium (Ca(2+)) and known to be involved in diseases such as cancer, heart attack, and stroke. A role for the CAPN10 gene in diabetes mellitus type II was recently identified. Hyper activation of the enzyme initiates a series of destructive cycles that can cause irreversible damage to cells. The development of inhibitors may be useful as therapeutic agents for a number of calpainopathies. In this paper, we have used the homology modelling technique to determine the 3D structure of calpain-10 from Homo sapiens. The model of calpain-10 obtained by homology modelling suggests that its active site is conserved among family members and the main interactions are similar to those observed for μ-calpain. Structural analysis revealed that there are small differences in the charge distribution and molecular surface of the enzyme. These differences are probably less dependent on calcium for calpain-10 than they are for μ-calpain. In addition, the ion pair Cys(-)/His(+) formation was observed using of Molecular Dynamics (MD) simulations that were based upon hybrid quantum mechanical/molecular mechanical (QM/MM) approaches. Finally, the binding of the SNJ-1715 inhibitor to calpain-10 was investigated in order to further understand the mechanism of inhibition of calpain-10 by this inhibitor at the molecular level.
The author was invited to assist in the development of an evaluation methodology for the Strategy. One of the conundrums of measuring the information management & technology (IM&T) function is that infrastructure investments cannot be cost justified on a return on investment basis. The balanced scorecard (BSC) is a means to evaluate corporate performance from four different perspectives: the financial perspective, the internal business process perspective, the customer perspective, and the learning and growth perspective. An IM&T BSC for Information for Health was recommended as means of allowing managers to see the positive and negative impacts of IM&T activities on the factors that are important to the NHS as a whole.
Image database extensions for functional brain images were assessed by asking clinicians questions about (i) diagnosis confidence level before and after using the software; (ii) expected and unexpected differences between patient and control images; ...
A cancer pain management unit can benefit markedly from a well-planned documentation system for administrative and scientific purposes. This article presents the principles of such a computerized system based on relational data base programs. The described system has been used by the authors for the last seven years. The successful documentation of more than 1400 patients over treatment periods of up to 2 years has provided detailed administrative and scientific information.
Accurate simulation and evaluation of mandibular movement is fundamental for the analysis of functional changes and effects of the mandible and maxilla before and after surgical treatments. We applied principal axes of inertia to the three-dimensional ...
Running fractal dimensions were measured on four channels of an electroencephalogram (EEG) recorded from a normal volunteer. The changes in the background activity due to eye closure were clearly differentiated by the fractal method. The compressed spectral array (CSA) and the running fractal dimensions of the EEG showed corresponding changes with respect to change in the background activity. The fractal method was also successful in detecting low amplitude spikes and the changes in the patterns in the EEG. The effects of different window lengths and shifts on the running fractal dimension have also been studied. The utility of fractal method for EEG data compression is highlighted.
In this paper, a generalized application of Kohonen Network for automatic point correspondence of unimodal medical images is presented. Given a pair of two-dimensional medical images of the same anatomical region and a set of interest points in one of the images, the algorithm detects effectively the set of corresponding points in the second image, by exploiting the properties of the Kohonen self organizing maps (SOMs) and embedding them in a stochastic optimization framework. The correspondences are established by determining the parameters of local transformations that map the interest points of the first image to their corresponding points in the second image. The parameters of each transformation are computed in an iterative way, using a modification of the competitive learning, as implemented by SOMs. The proposed algorithm was tested on medical imaging data from three different modalities (CT, MR and red-free retinal images) subject to known and unknown transformations. The quantitative results in all cases exhibited sub-pixel accuracy. The algorithm also proved to work efficiently in the case of noise corrupted data. Finally, in comparison to a previously published algorithm that was also based on SOMs, as well as two widely used techniques for detection of point correspondences (template matching and iterative closest point), the proposed algorithm exhibits an improved performance in terms of accuracy and robustness.
Based on Huffman tree method, we propose a new 2D graphic representation of protein sequence. This representation can completely avoid loss of information in the transfer of data from a protein sequence to its graphic representation. The method consists of two parts. One is about the 0-1 codes of 20 amino acids by Huffman tree with amino acid frequency. The amino acid frequency is defined as the statistical number of an amino acid in the analyzed protein sequences. The other is about the 2D graphic representation of protein sequence based on the 0-1 codes. Then the applications of the method on ten ND5 genes and seven Escherichia coli strains are presented in detail. The results show that the proposed model may provide us with some new sights to understand the evolution patterns determined from protein sequences and complete genomes.
Magnetic resonance cholangio pancreatography (MRCP) has become a reference technique for biliary tree analysis. Typical MRCP images, however, suffer from difficulty in distinguishing the structure of the biliary tree in order to identify abnormalities, for clinical diagnosis. For efficiency in analysing MRCP image series, the need arises for the use of semi-automated image processing techniques. A segment-based multi-scale approach is described, incorporated with image selection, enhancement and watershed segmentation, to identify and reconstruct the hierarchical biliary tree structure in 2D MRCP images. The results achieved may be further extended to higher dimensional images.
In this paper, we compare ultrasound interrogations of actual CT-scanned images of trabecular bone with artificial randomly constructed bone. Even though it is known that actual bone does not have randomly distributed trabeculae, we find that the ultrasound attenuations are close enough to cast doubt on any microstructural information, such as trabeculae width and distance between trabeculae, being gleaned from such experiments. More precisely, we perform numerical simulations of ultrasound interrogation on cancellous bone to investigate the phenomenon of ultrasound attenuation as a function of excitation frequency and bone porosity. The theoretical model is based on acoustic propagation equations for a composite fluid-solid material and is solved by a staggered-grid finite-difference scheme in the time domain. Numerical experiments are performed on two-dimensional bone samples reconstructed from CT-scanned images of real human calcaneus and from random distributions of fluid-solid particles generated via the turning bands method. A detailed comparison is performed on various parameters such as the attenuation rate and speed of sound through the bone samples as well as the normalized broadband ultrasound attenuation coefficient. Comparing results from these two types of bone samples allows us to assess the role of bone microstructure in ultrasound attenuation. It is found that the random model provides suitable bone samples for ultrasound interrogation in the transverse direction of the trabecular network.
Atherosclerotic plaque can cause severe stenosis in the artery lumen. Blood flow through a substantially narrowed artery may have different flow characteristics and produce different forces acting on the plaque surface and artery wall. The disturbed flow and force fields in the lumen may have serious implications on vascular endothelial cells, smooth muscle cells, and circulating blood cells. In this work a simplified model is used to simulate a pulsatile non-Newtonian blood flow past a stenosed artery caused by atherosclerotic plaques of different severity. The focus is on a systematic parameter study of the effects of plaque size/geometry, flow Reynolds number, shear-rate dependent viscosity and flow pulsatility on the fluid wall shear stress and its gradient, fluid wall normal stress, and flow shear rate. The computational results obtained from this idealized model may shed light on the flow and force characteristics of more realistic blood flow through an atherosclerotic vessel.
The Clear-PEM system is a prototype machine for Positron Emission Mammography (PEM) under development within the Portuguese PET-Mammography consortium. We have embedded 2D image reconstruction algorithms implemented in IDL within the prototype's image analysis package. The IDL implementation of these algorithms proved to be accurate and computationally efficient. In this paper, we present the implementation of the MLEM, OSEM and ART 2D iterative image reconstruction algorithms for PEM using IDL. C and IDL implementations are compared using realistic Monte Carlo simulated data. We show that IDL can be used for the easy implementation of image reconstruction algorithms for emission tomography.
The gold standard for the study of the macro-anatomy of the aortic root are multi-detector computed tomography (MDCT) and magnetic resonance (MR) imaging. Both technologies have major advantages and limitations. Although 4D echo is entering the study of the aortic root, 2D echo is the most commonly used diagnostic tool in daily practice. We designed and developed an algorithm for 3D modeling of the aortic root based on measures taken routinely at 2D echocardiography from 20 healthy individuals with normal aortic root. The tool was then translated in 12 patients who underwent both echo and MDCT. The results obtained with the 3D modeling program were quantitatively and qualitatively compared with 3D reconstruction from MDCT. Ad hoc ratios describing the morphology of the aortic root in MDCT and in the 3D model were used for comparison. In 12 patients with aortic root dilatation, the ratios obtained with our model are in good agreement with those from MDCT. Linear correlation for both long axis and short axis ratios was strong. The 3D modeling software can be easily adopted by cardiologists routinely involved in clinical evaluation of the pathology of the aortic root. The tool is easy to apply, does not require additional costs, and may be used to generate a set of data images for monitoring the evolution of the morphology and dimension of the aortic root, flanking the 3D MDCT and MR that remain the gold standard tools.
Spatial alignment of image data is a common task in computer vision and medical imaging. This should preferentially be done with minimal intervention of an operator. Similarity measures with origin in the information theory such as mutual information (MI) have proven to be robust registration criteria for this purpose. Intra-oral radiographs can be considered images of piecewise rigid objects. Teeth and jaws are rigid but can be displaced with respect to each other. Therefore MI criteria combined with affine deformations tend to fail, when teeth and jaws move with respect to each other between image acquisitions. In this paper, we consider a focused weighing of pixels in the reference image. The resulting criterion, focused mutual information (FMI) is an adequate tool for the registration of rigid parts of a scene. We also show that the use of FMI is more robust for the subtraction of lateral radiographs of teeth, than MI confined to a region of interest. Furthermore, the criterion allows the follow-up of small carious lesions when upper and lower jaw moved between the acquisition of test and reference image.
Occlusions introduced by medical instruments affect the accuracy and robustness of existing intensity-based medical image registration algorithms. In this paper, we present disocclusion-based 2D-3D registration handling occlusion and dissimilarity during registration. Therefore, we introduce two disocclusion techniques, Spline Interpolation and Stent-editing, and two robust similarity measures, Huber and Tukey Gradient Correlation. Our techniques are validated on synthetic and real interventional data and compared with well-known approaches. Results prove that an integration of disocclusion into the registration procedure yield higher accuracy and robustness. It is also shown that the robust measures have different effects depending on the type of occluding structure.
Automated protocols have been developed which guide minimally trained aides in collecting clinical data from ambulatory patients. Each protocol is keyed to a frequently occurring reason for patient visits. The protocols have been developed to save physician time and, in some cases, physician visits.
An efficient computational method for near real-time simulation of thermal ablation of tumors via radio frequencies is proposed. Model simulations of the temperature field in a 3D portion of tissue containing the tumoral mass for different patterns of source heating can be used to design the ablation procedure. The availability of a very efficient computational scheme makes it possible to update the predicted outcome of the procedure in real time. In the algorithms proposed here a discretization in space of the governing equations is followed by an adaptive time integration based on implicit multistep formulas. A modification of the ode15s MATLAB function which uses Krylov space iterative methods for the solution of the linear systems arising at each integration step makes it possible to perform the simulations on standard desktop for much finer grids than using the built-in ode15s. The proposed algorithm can be applied to a wide class of nonlinear parabolic differential equations.
Strain distribution in compressed tissues gives information about elasticity of the tissues. We have measured strain from two sets of 3D micro-CT images of a breast-mimicking phantom; one obtained without compressing the phantom and the other with compressing it. To measure strain, we first calculated compression-induced displacements of high-intensity feature patterns in the image. In measuring displacement of a pixel of interest, we searched the pixel in the compressed-phantom image, whose surrounding resembles the uncompressed-phantom image most closely, using the image correlation technique. From the displacement data, we calculated average strain at a region of interest. With the calculated average strains, we could distinguish the hard inclusion in the phantom which was not distinguishable from the background body of the phantom in the ordinary micro-CT images. The calculated strains account for stiffness of the tissue of interest, one of the important parameters for diagnosing malignant tissues. We present experimental results of the displacement and strain measurement along with FEM analysis results.
We present a set of techniques that enable us to segment objects from 3D cell membrane images. Particularly, we propose methods for detection of approximate cell nuclei centers, extraction of the inner cell boundaries, the surface of the organism and the intercellular borders--the so called intercellular skeleton. All methods are based on numerical solution of partial differential equations. The center detection problem is represented by a level set equation for advective motion in normal direction with curvature term. In case of the inner cell boundaries and the global surface, we use the generalized subjective surface model. The intercellular borders are segmented by the advective level set equation where the velocity field is given by the gradient of the signed distance function to the segmented inner cell boundaries. The distance function is computed by solving the time relaxed eikonal equation. We describe the mathematical models, explain their numerical approximation and finally we present various possible practical applications on the images of zebrafish embryogenesis--computation of important quantitative characteristics, evaluation of the cell shape, detection of cell divisions and others.
An advanced stochastic model is described which enables the generation of three-dimensional particle deposition patterns in the human lung. While particle trajectories are represented as a combination of randomly oriented vectors in a coordinate system with the trachea defining the z direction, deposition sites of single particles are determined by using a grid of specific volume elements (voxels). After storage in an array, the spatial coordinates are visualized with an appropriate graphic editor, enabling the combination of respective deposition images with lung outlines and the creation of two-dimensional distributions by sectioning the three-dimensional structures at pre-defined positions.
Recent advances in graphics processing unit (GPU) have enabled direct volume rendering at interactive rates. However, although perspective volume rendering for opaque isosurface is rapidly performed using conventional GPU-based method, perspective volume rendering for non-opaque volume such as translucency rendering is still slow. In this paper, we propose an efficient GPU-based acceleration technique of fast perspective volume ray casting for translucency rendering in computed tomography (CT) colonography. The empty space searching step is separated from the shading and compositing steps, and they are divided into separate processing passes in the GPU. Using this multi-pass acceleration, empty space leaping is performed exactly at the voxel level rather than at the block level, so that the efficiency of empty space leaping is maximized for colon data set, which has many curved or narrow regions. In addition, the numbers of shading and compositing steps are fixed, and additional empty space leapings between colon walls are performed to increase computational efficiency further near the haustral folds. Experiments were performed to illustrate the efficiency of the proposed scheme compared with the conventional GPU-based method, which has been known to be the fastest algorithm. The experimental results showed that the rendering speed of our method was 7.72fps for translucency rendering of 1024x1024 colonoscopy image, which was about 3.54 times faster than that of the conventional method. Since our method performed the fully optimized empty space leaping for any kind of colon inner shapes, the frame-rate variations of our method were about two times smaller than that of the conventional method to guarantee smooth navigation. The proposed method could be successfully applied to help diagnose colon cancer using translucency rendering in virtual colonoscopy.
One of the major concerns of scoliosis patients undergoing surgical treatment is the aesthetic aspect of the surgery outcome. It would be useful to predict the postoperative appearance of the patient trunk in the course of a surgery planning process in order to take into account the expectations of the patient. In this paper, we propose to use least squares support vector regression for the prediction of the postoperative trunk 3D shape after spine surgery for adolescent idiopathic scoliosis. Five dimensionality reduction techniques used in conjunction with the support vector machine are compared. The methods are evaluated in terms of their accuracy, based on the leave-one-out cross-validation performed on a database of 141 cases. The results indicate that the 3D shape predictions using a dimensionality reduction obtained by simultaneous decomposition of the predictors and response variables have the best accuracy.
Accurate simulation and evaluation of mandibular movement is fundamental for the analysis of functional changes and effects of the mandible and maxilla before and after surgical treatments. We applied principal axes of inertia to the three-dimensional (3D) trajectories generated by patient-specific simulations of TMJ movements for the functional evaluations of mandible movement. Three-dimensional movements of the mandible and the maxilla were tracked based on a patient-specific splint and an optical tracking system. The dental occlusion recorded on the sprint provided synchronization for initial movement in the tracking and the simulation phases. The translation and rotation recorded during movement tracking was applied sequentially to the mandibular model in relation to a fixed maxilla model. The sequential 3D positions of selected landmarks on the mandible were calculated based on the reference coordinate system. The landmarks selected for analysis were bilateral condyles and pogonion points. The moment of inertia tensor was calculated with respect to the 3D trajectory points. Using the unit vectors along the principal axes derived from the tensor matrix, α, β and γ rotations around z-, y- and x-axes were determined to represent the principal directions as principal rotations respectively. The γ direction showed the higher standard deviation, variation of directions, than other directions at all the landmarks. The mandible movement has larger kinematic redundancy in the γ direction than α and β during mouth opening and closing. Principal directions of inertia would be applied to analyzing the changes in angular motion of trajectories introduced by mandibular shape changes from surgical treatments and also to the analysis of the influence of skeletal deformities on mandibular movement asymmetry.
While a number of methods have been proposed to reconstruct geometrically and topologically accurate 3D vascular models from medical images, little attention has been paid to constantly maintain high mesh quality of these models during the reconstruction procedure, which is essential for many subsequent applications such as simulation-based surgical training and planning. We propose a set of methods to bridge this gap based on parallel transport frame. An improved bifurcation modeling method and two novel trifurcation modeling methods are developed based on 3D Bézier curve segments in order to ensure the continuous surface transition at furcations. In addition, a frame blending scheme is implemented to solve the twisting problem caused by frame mismatch of two successive furcations. A curvature based adaptive sampling scheme combined with a mesh quality guided frame tilting algorithm is developed to construct an evenly distributed, non-concave and self-intersection free surface mesh for vessels with distinct radius and high curvature. Extensive experiments demonstrate that our methodology can generate vascular models with better mesh quality than previous methods in terms of surface mesh quality criteria.
Central-chest lymph nodes play a vital role in lung-cancer staging. The definition of lymph nodes from three-dimensional (3D) multidetector computed-tomography (MDCT) images, however, remains an open problem. We propose two methods for computer-based segmentation of the central-chest lymph nodes from a 3D MDCT scan: the single-section live wire and the single-click live wire. For the single-section live wire, the user first applies the standard live wire to a single two-dimensional (2D) section after which automated analysis completes the segmentation process. The single-click live wire is similar but is almost completely automatic. Ground-truth studies involving human 3D MDCT scans demonstrate the robustness, efficiency, and intra-observer and inter-observer reproducibility of the methods.
The 3D ultrasound systems produce much better reproductions than 2D ultrasound, but their prohibitively high cost deprives many less affluent organization this benefit. This paper proposes using the conventional 2D ultrasound equipment readily available in most hospitals, along with a single conventional digital camera, to construct 3D ultrasound images. The proposed system applies computer vision to extract position information of the ultrasound probe while the scanning takes place. The probe, calibrated in order to calculate the offset of the ultrasound scan from the position of the marker attached to it, is used to scan a number of geometrical objects. Using the proposed system, the 3D volumes of the objects were successfully reconstructed. The system was tested in clinical situations where human body parts were scanned. The results presented, and confirmed by medical staff, are very encouraging for cost-effective implementation of computer-aided 3D ultrasound using a simple setup with 2D ultrasound equipment and a conventional digital camera.
A 3D computational fluid dynamic (CFD) model is presented to simulate transient rolling adhesion and deformation of leukocytes over a P-selectin coated surface in shear flow. The computational model is based on immersed boundary method for cell deformation, and stochastic Monte Carlo simulation for receptor/ligand interaction. The model is shown to predict the characteristic 'stop-and-go' motion of rolling leukocytes. Here we examine the effect of cell deformation, shear rate, and microvilli distribution on the rolling characteristics. Comparison with experimental measurements is presented throughout the article. We observe that compliant cells roll more stably, and have longer pause times due to reduced bond force and increased bond lifetime. Microvilli presentation is shown to affect rolling characteristics by altering the step size, but not pause times. Our simulations predict a significant sideway motion of the cell arising purely due to receptor/ligand interaction, and discrete nature of microvilli distribution. Adhesion is seen to occur via multiple tethers, each of which forms multiple selectin bonds, but often one tether is sufficient to support rolling. The adhesion force is concentrated in only 1-3 tethered microvilli in the rear-most part of a cell. We also observe that the number of selectin bonds that hold the cell effectively against hydrodynamic shear is significantly less than the total adhesion bonds formed between a cell and the substrate. The force loading on individual microvillus and selectin bond is not continuous, rather occurs in steps. Further, we find that the peak force on a tethered microvillus is much higher than that measured to cause tether extrusion.
For preoperative planning in minimal invasive neurosurgery, arterial aneurysms and tumors at the cranial base are imaged by spiral CT and high resolution MR sequences and post-processed by segmentation and 3D-reconstruction.
For a satisfactory computer simulation, a model, which imitates a natural situation, is needed. The Human heart is an irregular 3D object and thus difficult to reproduce. Basic data was taken from Visible Human Dataset (VHD), National Library of Medicine. The heart area was cut out of the original cross-sections and different tissues segmented. All the slices also had to be aligned to assure precise overlapping of the structures. A 3D computer heart model with the resolution of 1mm was designed. The heart model was dedicated to simulations of heat transfer during heart surgery however, it is applicable also to other medical simulations.
Micro-CT scanners can generate large high-resolution three-dimensional (3D) digital images of small-animal organs, such as rat hearts. Such images enable studies of basic physiologic questions on coronary branching geometry and fluid transport. Performing such an analysis requires three steps: (1) extract the arterial tree from the image; (2) compute quantitative geometric data from the extracted tree; and (3) perform a numerical analysis of the computed data. Because a typical coronary arterial tree consists of hundreds of branches and many generations, it is impractical to perform such an integrated study manually. An automatic method exists for performing step (1), extracting the tree, but little effort has been made on the other two steps. We propose an environment for performing a complete study. Quantitative measures for arterial-lumen cross-sectional area, inter-branch segment length, branch surface area and others at the generation, inter-branch, and intra-branch levels are computed. A human user can then work with the quantitative data in an interactive visualization system. The system provides various forms of viewing and permits interactive tree editing for "on the fly" correction of the quantitative data. We illustrate the methodology for 3D micro-CT rat heart images.
In this paper we present a new 3D discrete dynamic surface model. The model consists of vertices and edges, which connect adjacent vertices. Basic geometry of the model surface is generated by triangle patches. The model deforms by internal and external forces. Internal forces are obtained from local geometry of the model and are related to the local curvature of the surface. External forces, on the other hand, are based on the image data and are calculated from desired image features. We also present a method for generating an initial volume for the model from a stack of initial contours, drawn by the user on cross sections of the volumetric data.
A suitable dynamic 3D model that allows the simulation of the inguinal region with real-time performance on a personal computer was developed. A geometric model adjusted to real data was created by means of semiautomatic contour segmentation of anatomic units from the visible human project and data generated from classical anatomic information. A dynamic model included converting muscular units from their continuous geometric representation into a set of voxels and then real-time interaction and performance. The current implementation enables deformation of the realistic model associated with pushing and stretching interaction, allowing immersion in the anatomy of the inguinal structures. The model does not allow simulation of surgical interventions.
A novel fully automated system is introduced to facilitate lesion detection in dynamic contrast-enhanced, magnetic resonance mammography (DCE-MRM). The system extracts breast regions from pre-contrast images using a cellular neural network, generates normalized maximum intensity-time ratio (nMITR) maps and performs 3D template matching with three layers of 12x12 cells to detect lesions. A breast is considered to be properly segmented when relative overlap >0.85 and misclassification rate <0.10. Sensitivity, false-positive rate per slice and per lesion are used to assess detection performance. The system was tested with a dataset of 2064 breast MR images (344slicesx6 acquisitions over time) from 19 women containing 39 marked lesions. Ninety-seven percent of the breasts were segmented properly and all the lesions were detected correctly (detection sensitivity=100%), however, there were some false-positive detections (31%/lesion, 10%/slice).
We address the problem of 3D medical volume reconstruction using web services. The use of proposed web services is motivated by the fact that the problem of 3D medical volume reconstruction requires significant computer resources and human expertise in medical and computer science areas. Web services are implemented as an additional layer to a dataflow framework called data to knowledge. In the collaboration between UIC and NCSA, pre-processed input images at NCSA are made accessible to medical collaborators for registration. Every time UIC medical collaborators inspected images and selected corresponding features for registration, the web service at NCSA is contacted and the registration processing query is executed using the image to knowledge library of registration methods. Co-registered frames are returned for verification by medical collaborators in a new window. In this paper, we present 3D volume reconstruction problem requirements and the architecture of the developed prototype system at We also explain the tradeoffs of our system design and provide experimental data to support our system implementation. The prototype system has been used for multiple 3D volume reconstructions of blood vessels and vasculogenic mimicry patterns in histological sections of uveal melanoma studied by fluorescent confocal laser scanning microscope.
Fast bone segmentation is often important in computer-aided medical systems. Thresholding-based techniques have been widely used to identify the object of interest (bone) against dark backgrounds. However, the darker areas that are often present in bone tissue may adversely affect the results obtained using existing thresholding-based segmentation methods. We propose an automatic, fast, robust and accurate method for the segmentation of bone using 3D adaptive thresholding. An initial segmentation is first performed to partition the image into bone and non-bone classes, followed by an iterative process of 3D correlation to update voxel classification. This iterative process significantly improves the thresholding performance. A post-processing step of 3D region growing is used to extract the required bone region. The proposed algorithm can achieve sub-voxel accuracy very rapidly. In our experiments, the segmentation of a CT image set required on average less than 10s per slice. This execution time can be further reduced by optimizing the iterative convergence process.
MRI has become an effective tool for anatomical mice studies. Currently, embryologists study the development of mouse embryos in order to understand the mechanisms of human development. The aim of the research presented in this paper, is to develop a semi-automatic image segmentation framework based 3D deformable models to identify cardiac malformations which are a major cause of death in children. The segmentation systems have been used to segment 3D mouse embryos heart structures. Results on the ventricles and on the heart muscle are presented and compared with manually segmented models.
In this paper, to utilize the third dimension of Computed Tomography, regions of interest (ROI) slices were combined to form 3D ROI image and a 3D template was determined to find the structures with similar properties of nodules. Convolution of 3D ROI image with the proposed template strengthens the shapes similar to the template and weakens the other ones. False-positive (FP) per nodule and per slice versus diagnosis sensitivity were obtained. The Computer Aided Diagnosis system achieved 100% sensitivity with 0.83 FP per nodule and 0.46 FP per slice, when the nodule thickness was greater than or equal to 5.625 mm.
Although computer-based simulations, such as structural finite element analysis, have proven their usefulness to support procedural planning of coronary stenting, the link between the clinical practice and these engineering techniques is still limited to research test-cases. A key point to further promote such an interaction is to generate in a fast and effective manner the computational grids from the medical images. Hence, the present study proposes a simple framework to generate 3D meshes of coronary bifurcations from a pair of planar angiographic images obtained by X-ray angiography, which is the gold standard technique for the diagnosis of coronary artery stenosis.
This paper presents a method to reconstruct the 3D surface of a tooth given partial information about its shape. A statistical model comprising a mean shape and a series of deformation modes is obtained offline using a set of specimens. During reconstruction, rigid registration is performed to align the mean shape with the target. The mean shape is then deformed to approximate the target by minimizing the sum of squared distances between the two surfaces according to the deformation modes. The method is shown to be efficient for the recovery of tooth shape given crown information.
The diagnosis and staging of lung cancer often begins with the assessment of a suspect peripheral chest site. Such suspicious peripheral sites may be solitary pulmonary nodules or other abnormally appearing regions of interest (ROIs). The state-of-the-art process for assessing such peripheral ROIs involves off-line procedure planning using a three-dimensional (3D) multidetector computed tomography (MDCT) chest scan followed by bronchoscopy with an ultrathin bronchoscope. We present an integrated computer-based system for planning peripheral bronchoscopic procedures. The system takes a 3D MDCT chest image as input and performs nearly all operations automatically. The only interaction required by the physician is the selection of ROI locations. The system is computationally efficient and fits smoothly within the clinical work flow. Integrated into the system and described in detail in the paper is a new surface-definition method, which is vital for effective analysis and planning to peripheral sites. Results demonstrate the efficacy of the system and its usage for the live guidance of ultrathin bronchoscopy to the periphery.
Top-cited authors
U Rajendra Acharya
Özal Yildirim
  • Firat University
Shu Lih Oh
  • Ngee Ann Polytechnic
Ru San Tan
  • National Heart Centre Singapore
Jen Hong Tan
  • National University of Singapore