Chord-based algorithms can eliminate cone-beam artifacts in images reconstructed from a clinical computed
tomography (CT) scanner. The feasibility of using chord-based reconstruction algorithms was evaluated with
three clinical CT projection data sets.
The first projection data set was acquired using a clinical
64-channel CT scanner (Philips Brilliance 64) that
consisted of an axial scan from a quality assurance phantom. Images were reconstructed using (1) a full-scan
FDK algorithm, (2) a short-scan FDK algorithm, and (3) the
chord-based backprojection filtration algorithm
(BPF) using full-scan data. The BPF algorithm was capable of reproducing the morphology of the phantom
quite well, but exhibited significantly less noise than the two FDK reconstructions as well as the reconstruction
obtained from the clinical scanner.
The second and third data sets were obtained from scans of a head phantom and a patient's thorax. For both
of these data sets, the BPF reconstructions were comparable to the short-scan FDK reconstructions in terms of
image quality, although sharper features were indistinct in the BPF reconstructions.
This research demonstrates the feasibility of chord-based algorithms for reconstructing images from clinical
CT projection data sets and provides a framework for implementing and testing algorithmic innovations.
Motion artifacts in cardiac CT are an obstacle to obtaining diagnostically usable images. Although phase-specific
reconstruction can produce images with improved assessability (image quality), this requires that the radiologist spend
time and effort evaluating multiple image sets from reconstructions at different phases. In this study, ordinal logistic
regression (OLR) and artificial neural network (ANN) models were used to automatically assign assessability to images
of coronary calcified plaques obtained using a physical, dynamic cardiac phantom. 350 plaque images of 7 plaques from
five data sets (heart rates 60, 60, 70, 80, 90) and ten phases of reconstruction were obtained using standard cardiac CT
scanning parameters on a Phillips Brilliance 64-channel clinical CT scanner. Six features of the plaques (velocity,
acceleration, edge-based volume, threshold-based volume, sphericity, and standard deviation of intensity) as well as
mean feature values and heart rate were used for training the OLR and ANN in a round-robin re-sampling scheme based
on training and testing groups with independent plaques. For each image, an ordinal assessability index rating on a 1-5
scale was assigned by a cardiac radiologist (D.B.) for use as a "truth" in training the OLR and ANN. The mean
difference between the assessability index truth and model-predicted assessability index values was +0.111 with
SD=0.942 for the OLR and +0.143 with SD=0.916 for the ANN. Comparing images from the repeat 60 bpm scans gave
concordance correlation coefficients (CCCs) of 0.794 [0.743, 0.837] (value, 95% CI) for the radiologist assigned values,
0.894 [0.856, 0.922] for the OLR, and 0.861 [0.818, 0.895] for the ANN. Thus, the variability of the OLR and ANN
assessability index values appear to lie within the variability of the radiologist assigned values.
The Human Genome has been defined, giving us one part of the equation that stems from the central dogma of
molecular biology. Despite this awesome scientific achievement, the correspondence between genomics and imaging is
weak, since we cannot predict an organism's phenotype from even perfect knowledge of its genetic complement.
Biological knowledge comes in several forms, and the genome is perhaps the best known and most completely
understood type. Imaging creates another form of biological information, providing the ability to study morphology,
growth and development, metabolic processes, and diseases in vitro and in vivo at many levels of scale.
The principal challenge in biomedical imaging for the future lies in the need to reconcile the data provided by one or
multiple modalities with other forms of biological knowledge, most importantly the genome, proteome, physiome, and
To date, the imaging science community has not set a high priority on the unification of their results with genomics,
proteomics, and physiological functions in most published work. Images are relatively isolated from other forms of
biological data, impairing our ability to conceive and address many fundamental questions in research and clinical
This presentation will explain the challenge of biological knowledge integration in basic research and clinical
applications from the standpoint of imaging and image processing. The impediments to progress, isolation of the
imaging community, and mainstream of new and future biological science will be identified, so the critical and
immediate need for change can be highlighted.
Establishing the average shape and spatial variability for a set of similar anatomical objects is important for detecting and discriminating morphological differences between populations. This may be done using deformable templates to synthesize a 3D CT/MRI image of the average anatomy from a set of CT/MRI images collected from a population of similar anatomical objects. This paper investigates the error associated with the choice of template selected from the population used to synthesize the average population shape. Population averages were synthesized for a population of five infant skulls with sagittal synostosis and a population of six normal adult brains using a consistent linear-elastic image registration algorithm. Each data set from the populations was used as the template to synthesize a population average. This resulted in five different population averages for the skull population and six different population averages for the brain population. The displacement variance distance from a skull within the population to the other skulls in the population ranged from 5.5 to 9.9 mm2 while the displacement variance distance from the synthesized average skulls to the population ranged from 2.2 to 2.7 mm2. The displacement variance distance from a brain within the population to the other brains in the population ranged from 9.3 to 14.2 mm2 while the displacement variance distance from the synthesized average brains to the population ranged from 3.2 to 3.6 mm2. These results suggest that there was no significant difference between the choice of template with respect to the shape of the synthesized average data set for these two populations.
Registration of anatomical images is useful for many applications including image segmentation, characterization of normal and abnormal shape, and creating deformable anatomical shape atlases. The usefulness of the information derived from image registration depends on the degree of anatomically meaningful correspondence between the images. We assume that an ideal image registration algorithm can determine an unique correspondence mapping between any two image volumes imaged from a homogeneous population of anatomies; and that these transformations have the properties of invertibility and transitivity. Unfortunately, current image registration algorithms are far from ideal. In this paper we test the invertibility and transitivity of transformations computed from a 'traditional' and a consistent linear-elastic registration algorithm. Invertibility of the transformations was evaluated by comparing the composition of transformations from image A-to-B and B-to-A to the identity mapping. Transitivity of the transformations was evaluated by measuring the difference between the identity mapping and the composition the transformations from image A-to-B, B-to-C, and C-to-A. Transformations were generated by matching computer generated phantoms, CT data of infant heads, and MRI data of adult brains. The consistent algorithm out performed the 'traditional' algorithm by 8 to 16 times for the invertibility test and 2 to 5 times for the transitivity test.
Three-dimensional geometric modeling of the human cochlea not only provides a basis for preoperative planning and postoperative evaluation of cochlear implantation, but also facilitates medical education and training. In this paper, the three-dimensional geometric modeling method of the cochlea has been developed. The central path of the cochlea is extracted from a spiral CT image volume by segmenting the cochlea and tracking through the cochlear canal. The central path is modeled by a helico-spiral. The first component in the helico- spiral model represents the projected central path onto a plane perpendicular to the modiolar axis, while the second component depicts the longitudinal stretching of the central path. A non-linear least square minimization based algorithm is devised for the identification of intrinsic and extrinsic parameters of the helico-spiral representation of the cochlea. Numerical phantoms with added different noise levels up to standard deviation of 2 mm are synthesized according to the average parameters of the human cochlea to evaluate the accuracy. In real human cochlear studies, our model fits into the modiolar axis and the central path very well, allowing the calculation of length, height and angular positions needed for frequency mapping of multi-channel cochlear implant electrodes.
Synchronization of contrast administration and CT imaging can maximize the signal differences between arteries and background in first pass studies. In this paper, a bolus propagation model is developed for tomographic angiography, especially CT angiography that relies on bolus peak prediction, real-time CT observation and adaptive table transport. The bolus propagation model is configured as a network of vessels and organs, each of which is described based on the vascular transport operator theory. The traditional vascular operator is augmented by introducing a longitudinal length parameter to depict the bolus propagation along a vessel. A parameter adjustment algorithm is also designed for the extended vascular operator, assuming real- time measurements of concentration-time curves are available at multiple locations along the vessel. As a result, the bolus concentration can be computed with respective to both the time since bolus injection and the location along the vessel. Numerical simulation and patient studies with CT and MRI are performed to evaluate the feasibility and utility of the bolus propagation model. Individualization of the bolus propagation model are tested. Theoretical and practical values are in excellent agreement. This bolus propagation model has a significant potential for optimization of tomographic angiography. In particular, this model can be applied to CT angiography so that the intravenous bolus peak and the X-ray imaging aperture are matched with an adaptive table transport.
To understand the effect of pitch on raw data interpolation in multi-slice spiral/helical CT, and provide guidelines for scanner design and protocol optimization. Multi-slice spiral CT is mainly characterized by the three parameters: the number of detector arrays, the detector collimation, and the table increment per X-ray source rotation. The pitch in multi-slice spiral CT is defined as the ratio of the table increment over the detector collimation. In parallel to the current framework for studying longitudinal image resolution, the central fan- beam rays of direct and opposite directions are considered, assuming a narrow cone-beam angle. Generally speaking, sampling in the Radon domain by the direct and opposite central rays is non-uniform along the longitudinal axis. Using a recently developed methodology for quantifying the sensitivity of signal reconstruction from non-uniformly sampled finite points, the effect of pitch on raw data interpolation is analyzed in multi-slice spiral CT. Unlike single-slice spiral CT, in which image quality deceases monotonically as the pitch increases, the sensitivity of raw data interpolation in multi-slice spiral CT increases in an alternating way as the pitch increases, suggesting that image quality does not decrease monotonically in this case. The most favorable pitch can be found from the sensitivity-pitch plot for any given set of multi-slice spiral CT parameters. An example for four-slice spiral CT is provided. The study on the pitch effect using the sensitivity analysis approach reveals the fundamental characteristics of raw data interpolation in multi-slice spiral CT, and gives insights into interaction between pitch and image quality. These results may be valuable for design of multi-slice spiral CT scanners and imaging protocol optimization in clinical applications.
A major task in diagnostic medicine is to determine whether or not an individual has a normal or abnormal anatomy by examining medical images such as MRI, CT, etc. Unfortunately, there are few quantitative measures that a physician can use to discriminate between normal and abnormal besides a couple of length, width, height, and volume measurements. In fact, there is no definition/picture of what normal anatomical structures--such as the brain-- look like let alone normal anatomical variation. The goal of this work is to synthesize average 3D anatomical shapes using deformable templates. We present a method for empirically estimating the average shape and variation of a set of 3D medical image data sets collected from a homogeneous population of topologically similar anatomies. Results are shown for synthesizing the average brain image volume from a set of six normal adults and synthesizing the average skull/head image volume from a set of five 3 - 4 month old infants with sagittal synostosis.
CT colonography (CTC) is a new technology, which permits endoscopic-like evaluation of the mucosal surface. Recently, an electrical field based approach was developed to unravel the colon in spiral CT image volumes, that is to digitally straighten then flatten the colon using curved cross-sections. In this paper, we report (1) an exact and computation- intensive algorithm for straightening the colon using curved cross-sections, and (2) an approximate but computationally efficient straightening algorithm. In the direct straightening algorithm, each curved cross-section of the colon is defined by electrical force lines due to charges distributed along the colon path, and constructed by directly tracing the force lines. In the fast straightening algorithm, only representative force lines are traced that originate equiangularly from the current colon path position, while other force lines are interpolated from the traced force lines. The experiments are performed with both phantom and patient data. It is demonstrated that straightening the colon with curved cross-sections facilitates visualization and analysis, has potential for use in CTC; and the speed of the interpolation based straightening algorithm is practically acceptable, which is about 40 times faster than that of the direct algorithm.
Purpose: The purpose of this study is to compare the accuracy of facial linear measurements obtained from volumetric spiral CT using 2D versus 3D reconstruction, and test the repeatability of these measurements. Material and Methods: The population consisted of 5 cadaver heads that were scanned to a Spiral CT scanner (120 Kvp and 200 mA, Toshiba Xpress S/X Toshiba-America, Medical System Inc., Tustin, CA) with high- resolution contiguous slices. Heads were scanned with 3 mm thick axial slices and a 2 mm/sec table feed. The CT data were archived on optical disks, and then transferred to a networked computer workstation (Sun Microsystems with Cemax version 1.4 software, Fremont, CA), to generate 2D and 3D images for manipulation and analyses. Repeated measurements were done on 2D and 3D images reconstructed from spiral CT scans on the workstation. Linear measurements were done by 2 observers with 2 sessions each, using several unique and conventional craniometric anatomic landmarks. The soft tissues were then partially removed and physical measurements of the same landmarks were repeated by an electromagnetic (3 space) digitizer (Polhemus Navigation Sciences Division, Mc Donnell Douglas Electronic Company, Colchester, VE). Analyses of variance were done to compare 2D versus 3D methods, and the accuracy of measurements between both imaging techniques. Results: The results showed statistically significant differences between 2D and 3D images for the majority of measurements. The 3D image measurements were not statistically different from the physical measurements. However, some of the 2D image landmarks differed from physical measurements. The repeatability of measurements was high by spiral CT-based craniofacial imaging. Conclusion: New computer graphics technology combined with 3D volumetric imaging by spiral CT can distinguish the craniofacial anatomy with greater accuracy than previously reported measurements and with greater accuracy than measurements from 2DCT images. These 3D measurements are essential to diagnostic and treatment planning of craniofacial injuries, anomalies and for craniofacial identification.
Purpose: To evaluate measurement accuracy of 3D volumetric medical imaging from Spiral CT for craniofacial surgical planing. Material and methods: The study population consisted of 5 cadaver heads that were imaged on a spiral CT scanner with volumetric technique high-resolution contiguous axial slices 3mm thickness and 2mm/sec table feed, with 120Kvp and 200 mA. The archived CT data were stored on optical disks to allow full retrospective review of any image. The data sets were transferred to a networked computer workstation, to generated 3D volumetric images for subsequent manipulation and analyses. The computer graphics workstation allowed to do measurements, based on conventional craniometric anatomic landmarks, by 2 observers with 2 sessions each. The specimens were then submitted to a dynamic blunt force, in an effort to simulate craniofacial fractures, scanned and measured again. The soft tissues were then partially subsequently removed and the measurements were repeated by electromagnetic digitizer. Statistical analysis was done using analysis of variance. Results: Measurements from 3D spiral CT scans can be precise with high repeatability and sufficient accuracy for surgical planing. Conclusion: 3D computer graphics by spiral CT allowed, in vitro, sufficient precision for assessment of surgical management. Digital volumetric spiral CT imaging is valid quantitatively and qualitatively for craniofacial surgical planning and evaluation.
In x-ray computed tomography (CT) spiral/helical scanning is achieved by continuous and simultaneous source rotation, object translation and data acquisition. In medical imaging, fan-beam spiral CT has replaced conventional incremental CT. Also, cone-beam spiral CT is feasible and advantageous is important applications. In this paper, resolution characteristics, protocol optimization, and image restoration are discussed in fan-beam spiral CT. Then, generalized Feldkamp cone-beam reconstruction is described is spiral geometry. Based on Snyder's iterative deblurring theory, a unified iterative algorithm is reported to handle incomplete cone-beam data. Finally, several future possibilities in spiral CT are mentioned.
This paper describes a new method to register serial, volumetric x-ray computed tomography (CT) data sets for tracking soft-tissue deformation caused by insertion of intracavity brachytherapy applicators to treat cervical cancer. 3D CT scans collected from the same patient with and without a brachytherapy applicator are registered to aid in computation of the radiation dose to tumor and normal tissue. The 3D CT image volume of pelvic anatomy with the applicator. Initial registration is accomplished by rigid alignment of the pelvic bones and non-rigid alignment of gray scale CT data and hand segmentations of the vagina, cervix, bladder, and rectum. A viscous fluid transformation model is used for non-rigid registration to allow for local, non-linear registration of the vagina, cervix, bladder, and rectum without disturbing the rigid registration of the bony pelvis and adjacent structures. Results are presented in which two 3D CT data sets of the same patient - imaged with and without a brachytherapy applicator - are registered.
The emerging techniques of 3D spiral CT for 'virtual colonoscopy' show promise as a noninvasive screening modality for the detection of polyps. Our purpose was to evaluate three key post-processing parameters required for depiction of colonic polyps using perspective volume rendering (PVR): image reconstruction, window setting, and opacity map assignment of the attenuation histogram. Spiral CT scans of two different patients with known polyps confirmed by colonoscopy were performed. First, image quality was compared between images generated after interpolation of raw projection data and interpolation of reconstructed image data for longitudinal voxel dimensions of 1x, 2x, 4x, 6x and 8x in-plane voxel dimensions. Second, the dimensions of colonic polyps relative to haustral folds were measured on PVR images for various window settings and compared to similar measures performed on photography performed at colonoscopy. Third, a double sigmoidal and a stair-step opacity function were each applied to a 3D PVR image of a polyp, and quantitative differences in image smoothness were compared using a texture analysis method. In conclusion, spiral CT images reconstructed with 50 percent overlap and displayed with a standard display window permit accurate depiction of polyp dimensions relative to surrounding structures on PVR windows. Image artifacts may be suppressed with use of a double sigmoidal opacity map.
Clinical signs of radiotherapy failure are often not present until well after treatment has been completed. Methods which could predict the response of tumors either before or early into the radiotherapy schedule would have important implications for patient management. Recent studies performed at our institution suggest that MR perfusion imaging maya be useful in distinguishing between individuals who are likely to benefit from radiation therapy and those who are not. Because MR perfusion imaging reflects tissue vascularity as well as perfusion, quantitative positron emission tomographic (PET) blood flow studies were performed to obtain an independent assessment of tumor perfusion. MR perfusion and PET quantitative blood flow studies were acquired on four women diagnosed with advanced cervical cancer. The MR perfusion studies were acquired on a 1 cm sagittal slice through the epicenter of the tumor mass. Quantitative PET blood flow studies were performed using an autoradiographic technique. The PET and MRI were registered using a manual interactive routine and the mean blood flow in the tumor was compared to the relative signal intensity in a corresponding region on the MR image. The mean blood flow in the cervical tumors ranged form 30-48 ml/min/100 grams. The observed blood flow values are consistent with the assumed relationship between MR contrast enhancement and the distribution of tissue perfusion. The information offered by these studies provides an additional window into the evaluation of the response of cervical tumors to radiation therapy.
Accurate and reproducible geometric measurement of lower extremity residua is required for custom prosthetic socket design. We compared spiral x-ray computed tomography (SXCT) and 3D optical surface scanning (OSS) with caliper measurements and evaluated the precision and accuracy of each system. Spiral volumetric CT scanned surface and subsurface information was used to make external and internal measurements, and finite element models (FEMs). SXCT and OSS were used to measure lower limb residuum geometry of 13 below knee (BK) adult amputees. Six markers were placed on each subject's BK residuum and corresponding plaster casts and distance measurements were taken to determine precision and accuracy for each system. Solid models were created from spiral CT scan data sets with the prosthesis in situ under different loads using p-version finite element analysis (FEA). Tissue properties of the residuum were estimated iteratively and compared with values taken from the biomechanics literature. The OSS and SXCT measurements were precise within 1% in vivo and 0.5% on plaster casts, and accuracy was within 3.5% in vivo and 1% on plaster casts compared with caliper measures. Three-dimensional optical surface and SXCT imaging systems are feasible for capturing the comprehensive 3D surface geometry of BK residua, and provide distance measurements statistically equivalent to calipers. In addition, SXCT can readily distinguish internal soft tissue and bony structure of the residuum. FEM can be applied to determine tissue material properties interactively using inverse methods.
The precision and accuracy of area estimates from magnetic resonance (MR) brain images and using manual and automated segmentation methods are determined. Areas of the human hippocampus were measured to compare a new automatic method of segmentation with regions of interest drawn by an expert. MR images of nine normal subjects and nine schizophrenic patients were acquired with a 1.5-T unit (Siemens Medical Systems, Inc., Iselin, New Jersey). From each individual MPRAGE 3D volume image a single comparable 2-D slice (matrix equals 256 X 256) was chosen which corresponds to the same coronal slice of the hippocampus. The hippocampus was first manually segmented, then segmented using high dimensional transformations of a digital brain atlas to individual brain MR images. The repeatability of a trained rater was assessed by comparing two measurements from each individual subject. Variability was also compared within and between subject groups of schizophrenics and normal subjects. Finally, the precision and accuracy of automated segmentation of hippocampal areas were determined by comparing automated measurements to manual segmentation measurements made by the trained rater on MR and brain slice images. The results demonstrate the high repeatability of area measurement from MR images of the human hippocampus. Automated segmentation using high dimensional transformations from a digital brain atlas provides repeatability superior to that of manual segmentation. Furthermore, the validity of automated measurements was demonstrated by a high correlation with manual segmentation measurements made by a trained rater. Quantitative morphometry of brain substructures (e.g. hippocampus) is feasible by use of a high dimensional transformation of a digital brain atlas to an individual MR image. This method automates the search for neuromorphological correlates of schizophrenia by a new mathematically robust method with unprecedented sensitivity to small local and regional differences.
Spiral x-ray computed tomography (SXCT) volumetric imaging was applied to in situ goodness of fit evaluation for lower extremity (LE) prostheses with and without axial loading. SXCT data was obtained (Siemens Somatom PLUS-S) with and without the prosthesis in place. An algorithm was developed to map and measure the residuum bony and soft tissue structure and their relationship to the rigid prosthesis socket. A transform was applied along the main axis of the structure to estimate the local soft tissue thickness relative to bone and map it from a Cartesian coordinate voxel array into cylindrical and spherical (Lambert projection) maps. Interval changes in the soft tissue envelope relative to the underlying skeleton were measured by comparing maps obtained from serial examinations. The test-retest repeatability and validity of SXCT methods was assessed using cadaver parts, phantom test objects, and human volunteers. The soft tissue envelope of lower limb residua were successfully determined, and the precision (repeatability) of SXCT was consistently better than 90%. Soft tissue SXCT mapping of a lower limb residuum is feasible with the prosthesis in situ and provides comprehensive information on the geometry and tissue characteristics for static evaluation of prosthesis fit.
The GI tract examination with CT and MRI is currently performed by slice-based inspection despite the volumetric nature of the problem. With this paper we propose to unravel the GI tract digitally to facilitate, quantify and automate the process. To demonstrate the feasibility, an algorithm was developed to unravel and measure convoluted curvilinear structures. In the algorithm, a local K-L transform was applied along the main axis of the structure to estimate the local orientation as determined by the principal eigenvector. An adult dog bowel piece was spirally scanned in vitro and reconstructed. A digital GI tract phantom was designed and numerically synthesized. In both cases, the structures were successfully followed using our unraveling algorithm, the lengths of the structures measured with less than 5% error, and cross-sectional features of the GI tract phantom were defined, computed and plotted.
Prefrontal cortex volumetry by brain magnetic resonance (MR) is required to estimate changes postulated to occur in certain psychiatric and neurologic disorders. A semiautomated method with quantitative characterization of its performance is sought to reliably distinguish small prefrontal cortex volume changes within individuals and between groups. Stereological methods were tested by a blinded comparison of measurements applied to 3D MR scans obtained using an MPRAGE protocol. Fixed grid stereologic methods were used to estimate prefrontal cortex volumes on a graphic workstation, after the images are scaled from 16 to 8 bits using a histogram method. In addition images were resliced into coronal sections perpendicular to the bicommissural plane. Prefrontal cortex volumes were defined as all sections of the frontal lobe anterior to the anterior commissure. Ventricular volumes were excluded. Stereological measurement yielded high repeatability and precision, and was time efficient for the raters. The coefficient of error was <EQ 0.03. The overall 3-way inter- rater ICC equals 0.95; intra-rater ICCs equals 0.95 - 0.98. The use of specific internal landmarks to define prefrontal cortex boundaries on 3D images was critical to obtaining accurate measurements. MR prefrontal cortex volumetry by stereology can yield accurate and repeatable measurements. Small frontal lobe volume reductions in patients with brain disorders such as depression and schizophrenia can be efficiently assessed using this method.
Three-dimensional image acquisition, display, and analysis of dental structures was performed and validated using spiral computed tomography (SCT) with metal artifact suppression. Isolated extracted teeth, a dry mandible, cadaver mandible, and cadaver head were scanned and reconstructed using a spiral CT scanner (Siemens Somatom PLUS-S) with 1 mm detector collimation, 1-mm table feed, and 0.1 - 1 mm reconstruction interval using specially developed software. Algorithms for metal artifact reduction including extended attenuation range and interpolation of missing projections were applied. Volumetric rendering of voxel sum images was performed to synthesize images comparable to conventional intraoral dental radiographs. Direct comparison of voxel-based synthetic and digitized film images was made. Several isolated, extracted teeth were sectioned with a diamond saw and submitted for histomorphometric analysis to aid in direct comparison with CT slice images obtained by multiplanar reconstruction. Metal artifact reduction was successful in markedly reducing the streaks and star patterns that usually accompany metallic restorations and intraoral appliances. Individual teeth were comparable to CT slice images. Voxel sum images were comparable to dental radiographs; however, for the SCT images, the spatial resolution was higher within the plane of section than it was orthogonal to the plane of section. Serial examinations were obtained by SCT, registered by surface matching, and interval change measured by 3D subtraction. Simulated lesions and restorations were introduced and quantitatively evaluated pre- and post-interventionally to assess imaging method performance.
A reconfigurable, optical, 3D scanning system with sub-second acquisition of human body surface data was designed and simulated. Sensor elements (digital cameras/light beam projectors) that meet resolution, accuracy, and speed requirements are included in the system design. The sensors are interfaced to video frame grabber(s) under computer control resulting in a modular, low cost system. System operation and data processing are performed using a desktop graphics workstation. Surface data collected with this system can be oversampled to improve resolution and accuracy (viewed by overlapping camera/projector pairs). Multi- resolution data can be collected for different surfaces simultaneously or separately. Modeling and calibration of this reconfigurable system are achieved via a robust optimal estimation technique. Reconstruction software that allows seamless merging of a range data from multiple sensors has been implemented. Laser scanners that acquire body surface range data using one or two sensors require several seconds for data collection. Surface digitization of inaminate objects is feasible with such devices, but their use in human surface metrology is limited due to motion artifacts and occluded surfaces. Use of multiple, independent active sensors providing rapid collection and multi-resolution data enable sampling of complex human surface morphology not otherwise practical. 3D facial surface data has provided accurate measurements used in facial/craniofacial plastic surgery and modern personal protective equipment systems. Whole body data obtained with this new system is applicable to human factors research, medical diagnosis/treatment, and industrial design.
A method for spatial registration of 3D surfaces was developed for range data acquired by a multi-sensor optical surface scanner. Registration of 3D shapes is important for change detection and inspection. The requirement for an automatic and robust registration method stems from the need to compare digitized human anatomy surfaces obtained over extended periods of time. A typical example is comparison of pre-operative, post-operative, and recovered facial morphology of a face-lift patient. An iterative algorithm that handles six degrees of freedom (three rotations, and three translations) and does not require point to point correspondence of surfaces was developed. The method assumes that the surfaces are in near registration, otherwise, with surfaces having spherical symmetry, many iterations may be required before a successful outcome is achieved. Coarse registration can be obtained by visual transformations or by use of a principal axis transformation. First, points are identified on the second surface that lie on surface normals of points on the first surface. A divide and conquer technique is used to accelerate this process. Any points on the first surface that do not yield points on the second surface are ignored. The two sets of corresponding points (one set on each surface patch) is used in a least squares estimation scheme to minimize their distance. The estimate yields a transformation vector (consisting of rotations and translations) used to resample the second surface patch into a common coordinate system. This iterative process continues until the errors reduce below a set threshold or convergence is reached. Error statistics are reported. Testing and validation of the algorithm shows the method is feasible and efficient.
An optical surface scanner was used to digitize and model the torso of an adult female. This 3D surface scanner employs structured light and has an acquisition time of less than one second for a 0.4 X 0.4 X 0.4 meter sample volume. A female volunteer was digitized in three parts using this surface scanner: head, upper torso, and lower torso. External fiducials were used to aid in registration of the three data sets to create a complete body surface model. The fiducial point loci were sampled and entered in a least squares optimization scheme to rigidly transform (rotate and translate) the three data sets into alignment. The digitized data of each scan was converted into spline surfaces and imported into a computer graphics surface modeling package (Studio, Alias Research, Inc. Toronto, Canada). The results demonstrate whole body surface modeling with an optical surface scanner to achieve rapid complex 3D surface coverage.
Goal: To estimate hippocampal volumes from in vivo 3D magnetic resonance (MR) brain images and determine inter-rater and intra- rater repeatability. Objective: The precision and repeatability of hippocampal volume estimates using stereologic measurement methods is sought. Design: Five normal control and five schizophrenic subjects were MR scanned using a MPRAGE protocol. Fixed grid stereologic methods were used to estimate hippocampal volumes on a graphics workstation. The images were preprocessed using histogram analysis to standardize 3D MR image scaling from 16 to 8 bits and image volumes were interpolated to 0.5 mm3 isotropic voxels. The following variables were constant for the repeated stereologic measures: grid size, inter-slice distance (1.5 mm), voxel dimensions (0.5 mm3), number of hippocampi measured (10), total number of measurements per rater (40), and number of raters (5). Two grid sizes were tested to determine the coefficient of error associated with the number of sampled 'hits' (approximately 140 and 280) on the hippocampus. Starting slice and grid position were randomly varied to assure unbiased volume estimates. Raters were blind to subject identity, diagnosis, and side of the brain from which the image volumes were extracted and the order of subject presentation was randomized for each of the raters. Inter- and intra-rater intraclass correlation coefficients (ICC) were determined. Results: The data indicate excellent repeatability of fixed grid stereologic hippocampal volume measures when using an inter-slice distance of 1.5 mm and a 6.25 mm2 grid (inter-rater ICCs equals 0.86 - 0.97, intra- rater ICCs equals 0.85 - 0.97). One major advantage of the current study was the use of 3D MR data which significantly improved visualization of hippocampal boundaries by providing the ability to access simultaneous orthogonal views while counting stereological marks within the hippocampus. Conclusion: Stereological estimates of 3D volumes from 2D MR sections provide an inexpensive, unbiased and efficient way of determining brain structural volumes. The high precision and repeatability demonstrated with stereological MR volumetry suggest that these methods may be efficiently used to measure small volume reductions associated with schizophrenia and other brain disorders.
The design of lower limb prostheses requires definitive geometric data to customize socket shape. Optical surface imaging and spiral x-ray computed tomography were applied to geometric analysis of limb residua in below knee (BK) amputees. Residua (limb remnants after amputation) of BK amputees were digitized and measured. Surface (optical) and volumetric (CT) data of the residuum were used to generate solid models and specify socket shape in (SDRC I-DEAS) CAD software. Volume measurements on the solid models were found to correspond within 2% of surface models and direct determinations made using Archimedean weighing. Anatomic 3D reconstruction of the residuum by optical surface and spiral x-ray computed tomography imaging are feasible modalities for prosthesis design.
An optical noncontact 3-D range digitizer based on projection of 2-D structured light patterns and multiplexed charge injection device (CID) camera sensors has been developed. The system acquires digitized data in 0.75 5 and allows 360-deg examination of the subject's head and facial surface features in less than 1 s, making it suitable for digitizing children as well as adults. The resultant 3-D surface data is suitable for computer graphics display and manipulation, numerically controlled replication, and further processing such as surface measurement extraction. The digitizer uses a set of six stationary sensors positioned about the subject. A sensor consists of a pattern projector and a solid state video camera. This device allows quantitative volume measurements and employs no harmful ionizing radiation. The cost of a scan with this technology is substantially less than that of alternative means of collecting 3-D surface data sets, such as by stereometric, moire fringe, and single-point digitization. This system was geometrically designed such that any surlace of the head or facial area was independently digitized by a minimum of two sensors and to capture areas normally occluded with other techniques. The dimensions of the structure were derived to satisfy physical constraints placed on its overall size. The camera and projector orientations in space, the distance from the lens centers to the center of the digitizing volume, and the lens focal lengths were determined analytically. To reduce cost, a standard lens nearest the analytical value was used. Based on the standard size lens, the field of view was calculated.
An optical noncontact 3-D range scanner based on projection of 2-D structured light patterns and multiplexed charge injection device (OlD) camera sensors is developed. The system acquires scan data in 0.75 s and allows 360-deg examination of the object. The resultant 3-D surface data is suitable for computer graphics display and manipulation, numerically controlled replication, and for further processing such as surface measurement extraction. The scanner uses a set of six stationary sensors placed around the object to be scanned. A sensor consists of a pattern projector and a solid state video camera. The projectors are sequenced by a module called the video acquisition and control unit (VAU). This complex system must be accurately calibrated for seamless merging of overlapped surfaces obtained from different cameras. The calibration considerations in such a system are discussed. The calibration is accomplished using statistical parameter estimation algorithms. Known reference objects are used in the calibration procedure.
The Human Engineering Division of the Armstrong Laboratory (USAF); the Mallinckrodt Institute of Radiology; the Washington University School of Medicine; and the Lister-Hill National Center for Biomedical Communication, National Library of Medicine are sponsoring a working group on electronic imaging of the human body. Electronic imaging of the surface of the human body has been pursued and developed by a number of disciplines including radiology, forensics, surgery, engineering, medical education, and anthropometry. The applications range from reconstructive surgery to computer-aided design (CAD) of protective equipment. Although these areas appear unrelated, they have a great deal of commonality. All the organizations working in this area are faced with the challenges of collecting, reducing, and formatting the data in an efficient and standard manner; storing this data in a computerized database to make it readily accessible; and developing software applications that can visualize, manipulate, and analyze the data. This working group is being established to encourage effective use of the resources of all the various groups and disciplines involved in electronic imaging of the human body surface by providing a forum for discussing progress and challenges with these types of data.
The estimation of fiducial point locations on surfaces is important in many close range photogrammetric applications, including biostereometrics, non-contact stress analysis, industrial metrology, and others. We have developed various methods for estimation of surface fiducial points based on optically sensed range maps obtained with a multisensor 3-D scanner originally designed for portrait sculpture. We previously described an algorithm based on a Kalman filter, a recursive spatially variant optimal estimator. The results demonstrated that accurate localization of surface landmarks can be readily achieved. Two new methods for estimation of fiducial point locations on surfaces were devised for the 3-D scanner. This high- speed non-contact 3-D scanner uses 6 CID cameras and 6 pattern projectors. Each projector incorporates coded bar patterns which are projected onto the object to be scanned. These patterns are captured in the camera image, mensurated, and tagged to identify corresponding projector profiles for each profile observed in the camera. The set of points belonging to a profile on the image plane are entered into a 2-D to 3-D solution, an analytical procedure where each image point (2-D point) is mapped to a point in space (3-D point). Three- dimensional surface points from all views are resampled onto a global cylindrical grid. Both range and texture maps are computed and stored. The range and texture information from all views is averaged and displayed on a 3-D graphics workstation (Silicon Graphics 4-D/340). Fiducial point localization achieved via the two new methods employing variations of Kalman filtering.
A semiautomated, radiograph-based classifier of alveolar bone quality for dry skulls was developed Bone quality was based on the assessment of surface features, such as the resorption of cortical bone and the presence of vertical defects. The consensus of two trained observers was used to rate 50 mandibularquadrants of 29 skulls as having normal or poor alveolar bone quality. Bitewing radiographs were taken of the mandibles and digitized with a 35-mm, solid-state slide scanner at 1024 x 1520 x 8 bits. Regions of interest (ROl) of alveolar bone between the mandibular first and second molars were chosen. For these ROTs, Gray-scale values were plotted as histograms. Nonzero portions of the histogram were mapped to a 100-cell scale and cumulative percentage frequency curves of these were calculated. Average cumulative frequency distributions were calculated for 14 cases with normal bone quality and 1 1 cases with poor bone quality. These distributions were used to develop an automatic classifier based on differences between the cumulative frequency curve for each case and the average cumulative frequency curves for normal and poor quality bone. The bone quality of 43 of the 50quadrantswas successfully determined with this classifier. Of the seven misses, two were from one skull with severely tilted teeth; three were associated with bleached museum specimens; and the remaining two appeared to be a failure of the classifier. These preliminary results are encouraging. This classifier will be applied to a longitudinal series of bitewings of patients to predict alveolar bone loss.
Optical, non-contact three-dimensional range surface digitizers are employed in the 360-degree examination of object surfaces, especially the heads and faces of individuals. The resultant 3- D surface data is suitable for computer graphics display and manipulation, for numerically controlled object replications, or for further processing such as surface measurement extraction. We employed a scanner with a basic active sensor element consisting of a synchronized pattern projector employing flashtubes that illuminate a surface, with a CID camera to detect, digitize, and transmit the sequence of 24 images (per camera) to a digital image processor for surface triangulation, calibration, and fusion into a single surface description of the headform. A major feature of this unit is its use of multiple (typically 6) stationary active sensor elements, with efficient calibration algorithms that achieve nearly seamless superposition of overlapping surface segments seen by individual cameras. The result is accurate and complete coverage of complex contoured surfaces. Application of this system to digitization of the human head in the planning and evaluation of facial plastic surgery is presented.
A digital video-based system was designed and implemented to assess imaging workstation human-user interfaces through time and motion studies in diagnostic radiology and radiotherapy treatment planning. This system provides a means for recording and analyzing the activities which take place at imaging workstations during initial training and active clinical use in radiology. On time-synchronized and event-stamped video tapes, the system simultaneously records the soft copy display images and workstation environment.