Automatic detection and segmentation of bovine corpora lutea in ultrasonographic ovarian images using genetic programming and rotation invariant local binary patterns

In this study, we propose a fully automatic algorithm to detect and segment corpora lutea (CL) using genetic programming and rotationally invariant local binary patterns. Detection and segmentation experiments were conducted and evaluated on 30 images containing a CL and 30 images with no CL. The detection algorithm correctly determined the presence or absence of a CL in 93.33 % of the images. The segmentation algorithm achieved a mean (±standard deviation) sensitivity and specificity of 0.8693 ± 0.1371 and 0.9136 ± 0.0503, respectively, over the 30 CL images. The mean root mean squared distance of the segmented boundary from the true boundary was 1.12 ± 0.463 mm and the mean maximum deviation (Hausdorff distance) was 3.39 ± 2.00 mm. The success of these algorithms demonstrates that similar algorithms designed for the analysis of in vivo human ovaries are likely viable.     

Gravity Compensation Method for Combined Accelerometer and Gyro Sensors Used in Cardiac Motion Measurements

A miniaturized accelerometer fixed to the heart can be used for monitoring of cardiac function. However, an accelerometer cannot differentiate between acceleration caused by motion and acceleration due to gravity. The accuracy of motion measurements is therefore dependent on how well the gravity component can be estimated and filtered from the measured signal. In this study we propose a new method for estimating the gravity, based on strapdown inertial navigation, using a combined accelerometer and gyro. The gyro was used to estimate the orientation of the gravity field and thereby remove it. We compared this method with two previously proposed gravity filtering methods in three experimental models using: (1) in silico computer simulated heart motion; (2) robot mimicked heart motion; and (3) in vivo measured motion on the heart in an animal model. The new method correlated excellently with the reference (r ² > 0.93) and had a deviation from reference peak systolic displacement (6.3 ± 3.9 mm) below 0.2 ± 0.5 mm for the robot experiment model. The new method performed significantly better than the two previously proposed methods (p < 0.001). The results show that the proposed method using gyro can measure cardiac motion with high accuracy and performs better than existing methods for filtering the gravity component from the accelerometer signal.     

Effect of improved navigation performance on the accuracy of implant placement in total hip arthroplasty with a CT-based navigation system

A computed tomography (CT)-based navigation system is one of the support tools to place implant with appropriate alignment and position in total hip arthroplasty (THA). To determine whether the higher performance of the navigation would further improve the accuracy of implant placement in the clinical setting, we retrospectively compared the navigation accuracy of two different versions of a navigation system. The newer version of the navigation system had an upgraded optical sensor with superior positional accuracy. Navigation accuracy, defined as differences between postoperative measurements on CT images and intraoperative records on the navigation system, of 49 THAs performed with the newer version of the navigation system was compared with that of 49 THAs performed with the older version. With the newer version, the mean absolute accuracy (95% limits of agreement) of implant alignment was 1.2° (±?3.3°) for cup inclination, 1.0° (±?2.4°) for cup anteversion, 2.0° (±?4.9°) for stem anteversion, and 1.1° (±?2.4°) for stem valgus angle. The accuracy of the implant position was 1.5 mm (±?3.1 mm), 1.3 mm (±?3.0 mm), and 1.5 mm (±?3.1 mm) for cup x-, y-, and z-axes, respectively, 1.6 mm (±?3.2 mm), 1.4 mm (±?2.9 mm), and 1.5 mm (±?2.7 mm) for stem x-, y-, and z-axes, respectively, and 2.4 mm (±?4.5 mm) for leg length discrepancy. The values for the newer version were significantly more accurate with less variation compared to those of the older version. With upgraded navigation performance, more accurate implant placement was demonstrated in the clinical setting.     

2D to 3D fusion of echocardiography and cardiac CT for TAVR and TAVI image guidance

This study proposed a registration framework to fuse 2D echocardiography images of the aortic valve with preoperative cardiac CT volume. The registration facilitates the fusion of CT and echocardiography to aid the diagnosis of aortic valve diseases and provide surgical guidance during transcatheter aortic valve replacement and implantation. The image registration framework consists of two major steps: temporal synchronization and spatial registration. Temporal synchronization allows time stamping of echocardiography time series data to identify frames that are at similar cardiac phase as the CT volume. Spatial registration is an intensity-based normalized mutual information method applied with pattern search optimization algorithm to produce an interpolated cardiac CT image that matches the echocardiography image. Our proposed registration method has been applied on the short-axis “Mercedes Benz” sign view of the aortic valve and long-axis parasternal view of echocardiography images from ten patients. The accuracy of our fully automated registration method was 0.81 ± 0.08 and 1.30 ± 0.13 mm in terms of Dice coefficient and Hausdorff distance for short-axis aortic valve view registration, whereas for long-axis parasternal view registration it was 0.79 ± 0.02 and 1.19 ± 0.11 mm, respectively. This accuracy is comparable to gold standard manual registration by expert. There was no significant difference in aortic annulus diameter measurement between the automatically and manually registered CT images. Without the use of optical tracking, we have shown the applicability of this technique for effective fusion of echocardiography with preoperative CT volume to potentially facilitate catheter-based surgery.     

A Semi-automated Approach to Improve the Efficiency of Medical Imaging Segmentation for Haptic Rendering

The Sensimmer platform represents our ongoing research on simultaneous haptics and graphics rendering of 3D models. For simulation of medical and surgical procedures using Sensimmer, 3D models must be obtained from medical imaging data, such as magnetic resonance imaging (MRI) or computed tomography (CT). Image segmentation techniques are used to determine the anatomies of interest from the images. 3D models are obtained from segmentation and their triangle reduction is required for graphics and haptics rendering. This paper focuses on creating 3D models by automating the segmentation of CT images based on the pixel contrast for integrating the interface between Sensimmer and medical imaging devices, using the volumetric approach, Hough transform method, and manual centering method. Hence, automating the process has reduced the segmentation time by 56.35% while maintaining the same accuracy of the output at ±2 voxels.     

Automatic segmentation of left ventricle cavity from short-axis cardiac magnetic resonance images

In this paper, a computational framework is proposed to perform a fully automatic segmentation of the left ventricle (LV) cavity from short-axis cardiac magnetic resonance (CMR) images. In the initial phase, the region of interest (ROI) is automatically identified on the first image frame of the CMR slices. This is done by partitioning the image into different regions using a standard fuzzy c-means (FCM) clustering algorithm where the LV region is identified according to its intensity, size and circularity in the image. Next, LV segmentation is performed within the identified ROI by using a novel clustering method that utilizes an objective functional with a dissimilarity measure that incorporates a circular shape function. This circular shape-constrained FCM algorithm is able to differentiate pixels with similar intensity but are located in different regions (e.g. LV cavity and non-LV cavity), thus improving the accuracy of the segmentation even in the presence of papillary muscles. In the final step, the segmented LV cavity is propagated to the adjacent image frame to act as the ROI. The segmentation and ROI propagation are then iteratively executed until the segmentation has been performed for the whole cardiac sequence. Experiment results using the LV Segmentation Challenge validation datasets show that our proposed framework can achieve an average perpendicular distance (APD) shift of 2.23 ± 0.50 mm and the Dice metric (DM) index of 0.89 ± 0.03, which is comparable to the existing cutting edge methods. The added advantage over state of the art is that our approach is fully automatic, does not need manual initialization and does not require a prior trained model.     

An acoustical respiratory phase segmentation algorithm using genetic approach

This paper proposes a robust and fully automated respiratory phase segmentation method using single channel tracheal breath sounds (TBS) recordings of different types. The estimated number of respiratory segments in a TBS signal is firstly obtained based on noise estimation and nonlinear mapping. Respiratory phase boundaries are then located through the generations of multi-population genetic algorithm by introducing a new evaluation function based on sample entropy (SampEn) and a heterogeneity measure. The performance of the proposed method is analyzed for single channel TBS recordings of various types. An overall respiratory phase segmentation accuracy is found to be 12 ± 5 ms for normal TBS and 21 ± 9 ms for adventitious sounds. The results show the robustness and effectiveness of the proposed segmentation method. The proposed method has been a successful attempt to solve the clinical application challenge faced by the existing phase segmentation methods in terms of respiratory dysfunctions.     

In vitro quantification of the performance of model-based mono-planar and bi-planar fluoroscopy for 3D joint kinematics estimation

Model-based mono-planar and bi-planar 3D fluoroscopy methods can quantify intact joints kinematics with performance/cost trade-off. The aim of this study was to compare the performances of mono- and bi-planar setups to a marker-based gold-standard, during dynamic phantom knee acquisitions. Absolute pose errors for in-plane parameters were lower than 0.6 mm or 0.6° for both mono- and bi-planar setups. Mono-planar setups resulted critical in quantifying the out-of-plane translation (error < 6.5 mm), and bi-planar in quantifying the rotation along bone longitudinal axis (error < 1.3°). These errors propagated to joint angles and translations differently depending on the alignment of the anatomical axes and the fluoroscopic reference frames. Internal-external rotation was the least accurate angle both with mono- (error < 4.4°) and bi-planar (error < 1.7°) setups, due to bone longitudinal symmetries. Results highlighted that accuracy for mono-planar in-plane pose parameters is comparable to bi-planar, but with halved computational costs, halved segmentation time and halved ionizing radiation dose. Bi-planar analysis better compensated for the out-of-plane uncertainty that is differently propagated to relative kinematics depending on the setup. To take its full benefits, the motion task to be investigated should be designed to maintain the joint inside the visible volume introducing constraints with respect to mono-planar analysis.     

A computerized volumetric segmentation method applicable to multi-centre MRI data to support computer-aided breast tissue analysis,density assessment and lesion localization

Density assessment and lesion localization in breast MRI require accurate segmentation of breast tissues. A fast, computerized algorithm for volumetric breast segmentation, suitable for multi-centre data, has been developed, employing 3D bias-corrected fuzzy c-means clustering and morphological operations. The full breast extent is determined on T1-weighted images without prior information concerning breast anatomy. Left and right breasts are identified separately using automatic detection of the midsternum. Statistical analysis of breast volumes from eighty-two women scanned in a UK multi-centre study of MRI screening shows that the segmentation algorithm performs well when compared with manually corrected segmentation, with high relative overlap (RO), high true-positive volume fraction (TPVF) and low false-positive volume fraction (FPVF), and has an overall performance of RO 0.94 ± 0.05, TPVF 0.97 ± 0.03 and FPVF 0.04 ± 0.06, respectively (training: 0.93 ± 0.05, 0.97 ± 0.03 and 0.04 ± 0.06; test: 0.94 ± 0.05, 0.98 ± 0.02 and 0.05 ± 0.07).     

<Emphasis Type="Italic">Ex Vivo</Emphasis> Methods for Informing Computational Models of the Mitral Valve

Computational modeling of the mitral valve (MV) has potential applications for determining optimal MV repair techniques and risk of recurrent mitral regurgitation. Two key concerns for informing these models are (1) sensitivity of model performance to the accuracy of the input geometry, and, (2) acquisition of comprehensive data sets against which the simulation can be validated across clinically relevant geometries. Addressing the first concern, ex vivo micro-computed tomography (microCT) was used to image MVs at high resolution (~40 micron voxel size). Because MVs distorted substantially during static imaging, glutaraldehyde fixation was used prior to microCT. After fixation, MV leaflet distortions were significantly smaller (p < 0.005), and detail of the chordal tree was appreciably greater. Addressing the second concern, a left heart simulator was designed to reproduce MV geometric perturbations seen in vivo in functional mitral regurgitation and after subsequent repair, and maintain compatibility with microCT. By permuting individual excised ovine MVs (n = 5) through each state (healthy, diseased and repaired), and imaging with microCT in each state, a comprehensive data set was produced. Using this data set, work is ongoing to construct and validate high-fidelity MV biomechanical models. These models will seek to link MV function across clinically relevant states.     

Age-Dependent Ascending Aorta Mechanics Assessed Through Multiphase CT

Quantification of the age- and gender-specific in vivo mechanical characteristics of the ascending aorta (AA) will allow for identification of abnormalities aside from changes brought on by aging alone. Multiphase clinical CT scans of 45 male patients between the ages of 30 and 79 years were analyzed to assess age-dependent in vivo AA characteristics. The three-dimensional AA geometry for each patient was reconstructed from the CT scans for 9–10 phases throughout the cardiac cycle. The AA circumference was measured during each phase and was used to determine the corresponding diameter, circumferential strain, and wall tension at each phase. The pressure-strain modulus was also determined for each patient. The mean diastolic AA diameter was significantly smaller among young (42.6 ± 5.2 years) at 29.9 ± 2.8 mm than old patients (69.0 ± 5.2 years) at 33.2 ± 3.2 mm. The circumferential AA strain from end-diastole to peak-systole decreased from 0.092 ± 0.03 in young to 0.056 ± 0.03 in old patients. The pressure–strain modulus increased two-fold from 68.4 ± 30.5 kPa in young to 162.0 ± 93.5 kPa in old patients, and the systolic AA wall tension increased from 268.5 ± 31.3 kPa in young to 304.9 ± 49.2 kPa in old patients. The AA dilates and stiffens with aging which increases the vessel wall tension, likely predisposing aneurysm and dissection.     

Automatic segmentation of the aortic root in CT angiography of candidate patients for transcatheter aortic valve implantation

Transcatheter aortic valve implantation is a minimal-invasive intervention for implanting prosthetic valves in patients with aortic stenosis. Accurate automated sizing for planning and patient selection is expected to reduce adverse effects such as paravalvular leakage and stroke. Segmentation of the aortic root in CTA is pivotal to enable automated sizing and planning. We present a fully automated segmentation algorithm to extract the aortic root from CTA volumes consisting of a number of steps: first, the volume of interest is automatically detected, and the centerline through the ascending aorta and aortic root centerline are determined. Subsequently, high intensities due to calcifications are masked. Next, the aortic root is represented in cylindrical coordinates. Finally, the aortic root is segmented using 3D normalized cuts. The method was validated against manual delineations by calculating Dice coefficients and average distance error in 20 patients. The method successfully segmented the aortic root in all 20 cases. The mean Dice coefficient was 0.95 ± 0.03, and the mean radial absolute error was 0.74 ± 0.39 mm, where the interobserver Dice coefficient was 0.95 ± 0.03 and the mean error was 0.68 ± 0.34?mm. The proposed algorithm showed accurate results compared to manual segmentations.     

Telomere length and adrenergic-induced left ventricular dilatation and systolic chamber dysfunction in rats

Purpose

The mechanisms responsible for telomere shortening in heart failure are uncertain. We evaluated whether left ventricular (LV) dilatation and systolic chamber dysfunction produced by chronic β-adrenergic receptor (β-AR) activation is associated with leukocyte or cardiac telomere shortening.

Methods

Following 6 months of daily injections of the β-AR agonist, isoproterenol (0.02 mg/kg/day) or the saline vehicle to rats, the extent of LV dilatation and LV systolic chamber dysfunction were determined using echocardiography and isolated perfused heart procedures, and relative telomere length of leukocyte (LTL) and cardiac (CTL) deoxyribonucleic acid were determined using a quantitative real-time polymerase chain reaction assay.

Results

β-AR activation resulted in LV dilatation as indexed by increased LV diastolic diameters (9.2 ± 0.6 vs. 8.4 ± 0.9 mm, P = 0.01) and increased diastolic volume intercepts at zero pressure of the LV diastolic pressure–volume relationship (isolated, perfused heart preparation) (0.40 ± 0.06 vs. 0.37 ± 0.08 ml, P = 0.03). Moreover, β-AR activation resulted in LV systolic chamber dysfunction as indexed by reductions in LV endocardial fractional shortening (0.40 ± 0.05 vs. 0.45 ± 0.06, P = 0.01) and the slope of the LV systolic pressure–volume relation (609 ± 176 vs. 901 ± 230, P = 0.01). Although LTL decreased with age in rats receiving either the β-AR agonist or the saline vehicle (P < 0.05), neither CTL (?0.10 ± 0.14 vs. ?0.15 ± 0.12, P = 0.3) nor LTL (?0.11 ± 0.19 vs. ?0.15 ± 0.18, P = 0.5) were modified by β-AR activation.

Conclusion

In conclusion, chronic β-AR activation sufficient to produce LV dilatation and systolic chamber dysfunction is not associated with alterations in leukocyte or cardiac telomere length. Telomere shortening in chronic heart failure is unlikely to be attributed to chronic β-AR activation.     

Automated Lung Segmentation from HRCT Scans with Diffuse Parenchymal Lung Diseases

Performing accurate and fully automated lung segmentation of high-resolution computed tomography (HRCT) images affected by dense abnormalities is a challenging problem. This paper presents a novel algorithm for automated segmentation of lungs based on modified convex hull algorithm and mathematical morphology techniques. Sixty randomly selected lung HRCT scans with different abnormalities are used to test the proposed algorithm, and experimental results show that the proposed approach can accurately segment the lungs even in the presence of disease patterns, with some limitations in the apices and bases of lungs. The algorithm demonstrates a high segmentation accuracy (dice similarity coefficient?=?98.62 and shape differentiation metrics d_mean?=?1.39 mm, and d_rms?=?2.76 mm). Therefore, the developed automated lung segmentation algorithm is a good candidate for the first stage of a computer-aided diagnosis system for diffuse lung diseases.     

To what extent can 3D model replicate dimensions of individual mitral valve prolapse?

Determining the complex geometry of mitral valve prolapse is often difficult. We constructed 3D models of six prolapsed mitral valves for surgical assessment, and evaluated how accurately the models could replicate individual valve dimensions. 3D polygon data were constructed based on an original segmentation method for computed tomography images. The model’s replication performance was confirmed via dimensional comparison between the actual hearts during surgery and those models. The results revealed that the prolapsed segments matched in all cases; however, torn chordae were replicated in four cases. The mean height differences were 0.0 mm (SD 1.6, range ??2 to +?2 mm) for the anterolateral side, 0.0 mm (SD 1.7, range ??2 to +?2 mm) for the prolapsed leaflet center, and ??1.5 mm (SD 0.6, range ??1 to ??2 mm) for the posteromedial side. Regression analysis showed a strong and positive correlation, and Bland–Altman plots indicated quantitative similarity of the models to the actual hearts. We concluded that our 3D valve models could replicate the actual mitral valve prolapses within acceptable dimensional differences. Our concepts are useful for better 3D valve creation and better surgical planning with reliable 3D valve models.     

Method for Segmentation of Knee Articular Cartilages Based on Contrast-Enhanced CT Images

Segmentation of contrast-enhanced computed tomography (CECT) images enables quantitative evaluation of morphology of articular cartilage as well as the significance of the lesions. Unfortunately, automatic segmentation methods for CECT images are currently lacking. Here, we introduce a semiautomated technique to segment articular cartilage from in vivo CECT images of human knee. The segmented cartilage geometries of nine knee joints, imaged using a clinical CT-scanner with an intra-articular contrast agent, were compared with manual segmentations from CT and magnetic resonance (MR) images. The Dice similarity coefficients (DSCs) between semiautomatic and manual CT segmentations were 0.79–0.83 and sensitivity and specificity values were also high (0.76–0.86). When comparing semiautomatic and manual CT segmentations, mean cartilage thicknesses agreed well (intraclass correlation coefficient?=?0.85–0.93); the difference in thickness (mean?±?SD) was 0.27?±?0.03 mm. Differences in DSC, when MR segmentations were compared with manual and semiautomated CT segmentations, were statistically insignificant. Similarly, differences in volume were not statistically significant between manual and semiautomatic CT segmentations. Semiautomation decreased the segmentation time from 450?±?190 to 42?±?10 min per joint. The results reveal that the proposed technique is fast and reliable for segmentation of cartilage. Importantly, this is the first study presenting semiautomated segmentation of cartilage from CECT images of human knee joint with minimal user interaction.     

A morphometric anatomical and comparative study of the foramen magnum region in a Greek population

Background

The foramen magnum (FM), a complex area in craniocervical surgery, poses a challenge for neurosurgeons. The knowledge of the detailed anatomy of the FM, occipital condyles (OC) and variations of the region is crucial for the safety of vital structures. This study focuses on the FM and OC morphometry, highlights anatomical variability and investigates correlations between the parameters studied.

Materials and methods

One hundred and forty-three Greek adult dry skulls were examined using a digital sliding calliper (accuracy, 0.01 mm).

Results

Mean FM width and length were found 30.31 ± 2.79 and 35.53 ± 3.06 mm, respectively. The commonest FM shape was two semicircles (25.9 %), whereas the most unusual was irregular (0.7 %). The OC minimum width, maximum width and length were 5.71 ± 1.61, 13.09 ± 1.99 and 25.60 ± 2.91 mm on the right, and 6.25 ± 1.76, 13.01 ± 1.98 and 25.60 ± 2.70 mm on the left side. The commonest OC shape was S-like and the most unusual was ring, bilaterally. The mean anterior and posterior intercondylar distances were 19.30 ± 3.25 and 51.61 ± 5.01 mm, respectively. The OC protruded into the FM in 86.7 % of the skulls. Variations such as a third OC existed in 5.6 % and basilar processes in 2.8 %. Posterior condylar foramina were present in 75.5 %. The gender was correlated with FM width and length, OC length, bilaterally, anterior intercondylar distance (AID) and posterior intercondylar distance (PID). The OC protrusion and existence of posterior condylar foramina were correlated. Bilateral asymmetry for OC shape was statistically significant.

Conclusion

Our results provide useful information that will enable effective and reliable surgical intervention in the FM region with the maximum safety and widest possible exposure.     

Morphometrics of the human thumb metacarpal bone: interest for developing an osseointegrated prosthesis

Introduction

Amputation of the thumb presents a serious insult to the hand and diminished quality of life for a patient physically, vocationally, and possibly psychologically. The aim of this study was to define the geometry of the thumb metacarpal in order to help create a standardized set of transcutaneous osseointegrated prostheses to treat patients who have suffered amputation of the thumb at the level of the metacarpophalangeal joint.

Materials and methods

A total of 80 metacarpals from 46 cadavers were studied. All soft tissues were removed and the thumb metacarpals were imaged using computed tomography. Three-dimensional models were constructed using images from the coronal, sagittal, and axial planes. Using HyperMesh? CAD software, the bones were analyzed for overall length, radius of curvature, medullary canal diameter, cortical thickness, and distance to the isthmus, defined as the narrowest portion of the intramedullary canal.

Results

The average length of the first metacarpal was 47.6 mm (±3.3 mm, 39.2–56.9 mm). The average radius of curvature was 55.5 mm (±10.7 mm, 33–78.9 mm). Inner bone diameter, measured in two axes, was 10.5 mm (±1.3 mm, 5.4–18.7 mm) for the major axis and 7.7 mm (±0.9 mm, 4.3–17.8 mm) for the minor axis. The average cortical thickness was 1.4 mm (±0.3 mm, 0.7–3.1 mm). The distance to the center of the isthmus from the distal end had an average length of 21.3 mm (±1.9 mm, 17–25 mm).

Conclusions

Using these findings a standardized set of intramedullary stems can be developed as a base for a transcutaneous osseointegrated prosthesis, helping to create a reliable method for treating patients with amputated thumbs.

     

Contralateral MRI scan can be used reliably for three-dimensional meniscus sizing — Retrospective analysis of 160 healthy menisci

BackgroundMeniscus allograft transplantation is a valuable surgical option for post-meniscectomy syndrome. For best results, the selected allograft should be as similar as possible to the original meniscus. Three-dimensional meniscus sizing could be a new approach to improve the accuracy of meniscus matching. The contralateral anatomy might therefore be a suitable reconstruction template. The purpose of this study was to compare the three-dimensional shape of the right and left menisci by bi-planar segmentation of magnetic resonance imaging (MRI) scans.MethodsThree-dimensional surface models of healthy menisci were created based on 40 bilateral MRI scans. Manual segmentation was performed on the MRI data in sagittal and coronal planes. For side-to-side comparison, each left meniscus model was mirrored and then superimposed to its corresponding right meniscus model. Differences between the meniscus pairs were assessed by width, length, height and surface distances. Inter-reader reliability, as well as accuracy of bi-planar segmentation was assessed by two different readers.ResultsThe meniscus pairs were not significantly different in terms of width, length and height (P = at least 0.138). Side difference of mean surface distances was 0.76 mm (± 0.13 standard deviation (SD)) for medial and 0.78 mm (± 0.15 SD) for lateral menisci. Inter-reader reliability was good to excellent (0.828–0.987).ConclusionThe three-dimensional shapes of the left and right menisci are very similar. Therefore, the contralateral meniscus can be used as a template for three-dimensional meniscus allograft sizing. Three-dimensional meniscus segmentation and sizing can be performed accurately by combination of sagittal and coronal planes.     

Morphometric evaluations of personalised 3D reconstructions and geometric models of the human spine

In the past, several techniques have been developed to study and analyse the 3D characteristics of the human spine: multi-view radiographic or biplanar 3D reconstructions, CT-scan 3D reconstructions and geometric models. Extensive evaluations of three of these techniques that are routinely used at Sainte-Justine Hospital (Montréal, Canada) are presented. The accuracy of these methods is assessed by comparing them with precise measurements made with a coordinate measuring machine on 17 thoracic and lumbar vertebrae (T1-L5) extracted from a normal cadaveric spine specimen. Multi-view radiographic 3D reconstructions are evaluated for different combinations of X-ray views: lateral (LAT), postero-anterior with normal incidence (PAO^o) and postero-anterior with 20^o angled down incidence (PA20^o). The following accuracies are found for these reconstructions obtained from different radiographic setups: 2.1±1.5 mm for the combination with PAO^o-LAT views, and 5.6±4.5 mm for the PAO^o-PA20^o stereopair. Higher errors are found in the postero-anterior direction, especially for the PAO^o-PA20^o view combination. Pedicles are found to be the most precise landmarks. Accuracy for CT-scan 3D reconstructions is about 1.1±0.8 mm. As for a geometric model built using a multiview radiographic reconstruction based on six landmarks per vertebra, accuracies of about 2.6±2.4 mm for landmarks and 2.3±2.0 mm for morphometric parameters are found. The geometric model and 3D reconstruction techniques give accurate information, at low X-ray dose. The accuracy assessment of the techniques used to study the 3D characteristics of the human spine is important, because it allows better and more efficient quantitative evaluations of spinal dysfunctions and their treatments, as well as biomechanical modelling of the spine.