Mean Distance Error Research Articles

SU-GG-I-99: Registration and Active Shape Model-Based Segmentation of Lymph Node Regions in Head and Neck CT Images

Purpose: To develop a robust automatic method to segment the level II , III and IV lymph node regions in CTimages for head and neck IMRTtreatment planning. We developed a technique whereby registration‐based methods initialize an active shape model (ASM). Method and Materials: An average atlas was first created from 15 H/N patient (training) volumes with minimally enlarged nodes. To build the ASM model the average atlas was registered with each of the training volumes and correspondence of mesh vertices of lymph node surfaces was determined. Once built, the atlas and ASM can be applied to any target patient image. A patient image is first registered to the atlas through global affine, then global non‐rigid, and finally local non‐rigid transformations. The two non‐rigid registrations produce displacements for vertices on the structure of interest and map them from the atlas onto the affinely aligned image. The ASM segmentation is initialized by constraining the displacements and then refined by iteratively adjusting the vertices through a local gray‐level model search followed by model fitting until convergence. Results: The algorithm was evaluated through a leave‐one‐out experiment. The model‐based and registration‐based segmentations were compared with the manual delineations via a Euclidean distance measure applied to their 3D surfaces. The mean distance errors were reduced from 2.60 mm for the registration‐based method to 2.36 mm for ASM‐based method, and the maximum distance errors were decreased for 13 cases out of 15 cases, with a reduction up to of 47.9%. Conclusion: We have found that purely registration‐based methods suffer gross under/over segmentation in areas of low CT contrast. The results show that an active shape model approach initialized by the registration result can reduce these deviations.

Extreme leg motion analysis of professional ballet dancers via MRI segmentation of multiple leg postures

Professional ballet dancers are subject to constant extreme motion which is known to be at the origin of many articular disorders. To analyze their extreme motion, we exploit a unique magnetic resonance imaging (MRI) protocol, denoted as 'dual-posture' MRI, which scans the subject in both the normal (supine) and extreme (split) postures. However, due to inhomogeneous tissue intensities and image artifacts in these scans, coupled with unique acquisition protocol (split posture), segmentation of these scans is difficult. We present a novel algorithm that exploits the correlation between scans (bone shape invariance, appearance similarity) in automatically segmenting the dancer MRI images. While validated segmentation algorithms are available for standard supine MRI, these algorithms cannot be applied to the split scan which exhibits a unique posture and strong inter-subject variations. In this study, the supine MRI is segmented with a deformable models method. The appearance and shape of the segmented supine models are then re-used to segment the split MRI of the same subject. Models are first registered to the split image using a novel constrained global optimization, before being refined with the deformable models technique. Experiments with 10 dual-posture MRI datasets in the segmentation of left and right femur bones reported accurate and robust results (mean distance error: 1.39 ± 0.31 mm). The use of segmented models from the supine posture to assist the split posture segmentation was found to be equally accurate and consistent to supine results. Our results suggest that dual-posture MRI can be efficiently and robustly segmented.

A path following algorithm for mobile robots

This paper considers path following control for a robotic platform. The vehicle used for the experiments is a specially designed robotic platform for performing autonomous weed control. The platform is four-wheel steered and four-wheel driven. A diesel engine powers the wheels via a hydraulic transmission. The robot uses a Real Time Kinematic Differential Global Positioning System to determine both position and orientation relative to the path. The deviation of the robot to the desired path is supplied to two high level controllers minimizing the orthogonal distance and orientation to the path. Wheel angle setpoints are determined from inversion of the kinematic model. At low level each wheel angle is controlled by a proportional controller combined with a Smith predictor. Results show the controller performance following different paths shapes including a step, a ramp, and a typical headland path. A refined tuning method calculates controller settings that let the robot drive as much as possible along the same path to its setpoint, but also limit the gains at higher speeds to prevent the closed loop system to become unstable due to the time delay in the system. Mean, minimum and maximum orthogonal distance errors while following a straight path on a paving at a speed of 0.5 m/s are 0.0, −2.4 and 3.0 cm respectively and the standard deviation is 1.2 cm. The control method for four wheel steered vehicles presented in this paper has the unique feature that it enables control of a user definable position relative to the robot frame and can deal with limitations on the wheel angles. The method is very well practical applicable for a manufacturer: all parameters needed are known by the manufacturer or can be determined easily, user settings have an easy interpretation and the only complex part can be supplied as a generic software module.

An Integrated Approach to Computer-Based Automated Tracing and Its Validation for 200 Common Carotid Arterial Wall Ultrasound Images

Most of the algorithms for the segmentation of the common carotid artery (CCA) wall require human interaction to locate the vessel in the ultrasound image. The aim of this article is to show an accurate algorithm for the computer-based automated tracing of the CCA in longitudinal B-mode ultrasound images. Two hundred images (100 normal CCAs, 50 CCAs with an increased intima-media thickness, 30 with fibrous plaques, and 20 with anechoic plaques) were processed to delineate the region of interest containing the CCA. The strategy is an integrated approach (carotid artery layer extraction using an integrated approach [CALEXia]) consisting of geometric feature extraction, line fitting, and classification. The output of the algorithm is the tracings of the proximal and distal adventitia layers. Performance of the algorithm was validated against human tracings considered the ground truth. The mean distance errors +/- SD using this integrated approach were 1.05 +/- 1.04 pixels (0.07 +/- 0.07 mm) for proximal or near adventitia and 2.68 +/- 3.94 pixels (0.17 +/- 0.24 mm) for distal or far adventitia. Sixteen of 200 images were not perfectly traced because of the presence of both plaques and blood backscattering. The computational cost ensures the possibility for near real-time detection. Conclusions. Although the CALEXia algorithm automatically detects the CCA, it is also robust and validated over a large database. This can constitute a general basis for a completely automated segmentation procedure widely applicable to other anatomies.

Automatic Segmentation of Calcifications in Intravascular Ultrasound Images Using Snakes and the Contourlet Transform

It is valuable to detect calcifications in intravascular ultrasound images for studies of coronary artery diseases. An image segmentation method based on snakes and the Contourlet transform is proposed to automatically and accurately detect calcifications. With the Contourlet transform, an original image is decomposed into low-pass bands and band-pass directional sub-bands. The 2-D Renyi's entropy is used to adaptively threshold the low-pass bands in a multiresolution hierarchy to determine regions-of-interest (ROIs). Then a mean intensity ratio, reflecting acoustic shadowing, is presented to classify calcifications from noncalcifications and obtain initial contours of calcifications. The anisotropic diffusion is used in bandpass directional sub-bands to suppress noise and preserve calcific edges. Finally, the contour deformation in the boundary vector field is used to obtain final contours of calcifications. The method was evaluated via 60 simulated images and 86 in vivo images. It outperformed a recently proposed method, the Santos Filho method, by 2.76% and 14.53%, in terms of the sensitivity and specificity of calcification detection, respectively. The area under the receiver operating characteristic curve increased by 0.041. The relative mean distance error, relative difference degree, relative arc difference, relative thickness difference and relative length difference were reduced by 5.73%, 19.79%, 11.62%, 12.06% and 20.51%, respectively. These results reveal that the proposed method can automatically and accurately detect calcifications and delineate their boundaries. (E-mail: yywang@fudan.edu.cn)

Illumination invariant seam line detection in real garments

PurposeThe purpose of this paper is to provide a robust method for automatic detection of seam lines based only on digital images of the garments.Design/methodology/approachA local standard deviation pre‐processing filter is applied to enhance the contrast between the seam line and the texture and the Prewitt operator extracts the edges of the enhanced image. The seam line is detected by a maximum at the Radon transform. The proposed method is invariant to the illumination intensity and it has been also tested with moving average and fast Fourier transform low‐pass filters used in the pre‐processing module. Extensive experiments are carried out in the presence of additive Gaussian and uniform noise.FindingsThe proposed method detects 109 out of 118 seams when the local standard deviation is used at the pre‐processing stage, giving a mean distance error between the real and the estimated line of 2 mm when the image is digitised at 97 dpi. However, in case the images are distorted by additive Gaussian noise at 20 dB signal‐to‐noise ratio, the moving average low‐pass filtering method gives the best results, detecting 104 noisy images.Research limitations/implicationsThe proposed method detects seam lines that can be approximated by a continuation of straight lines. The current work can be extended in the detection of the curved parts of seam lines.Practical implicationsSince the method addresses garments instead of seam specimens, the proposed approach can be imported in automatic systems for online quality control of seams.Originality/valueLocal standard deviation belongs to first‐order statistics, which makes it suitable for texture analysis and that is why it is mostly used in web defect detection. The novelty in the approach, however, is that by considering the seam as an abnormality of the texture, the authors applied that method at the pre‐processing stage to enhance the seam before the detection. Moreover, the presented method is illumination invariant, a property that has not been addressed in similar methods.

Enhancing Location Estimation and Reducing Computation using Adaptive Zone Based K-NNSS Algorithm

The purpose of this research is to accurately estimate the location of a device using the received signal strength indicator (RSSI) of IEEE 802.11 WLAN for location tracking in indoor environments. For the location estimation method, we adopted the calibration model. By applying the Adaptive Zone Based K-NNSS (AZ-NNSS) algorithm, which considers the velocity of devices, this paper presents a 9% improvement of accuracy compared to the existing K-NNSS-based research, with 37% of the K-NNSS computation load. The accuracy is further enhanced by using a Kalman filter; the improvement was about 24%. This research also shows the level of accuracy that can be achieved by replacing a subset of the calibration data with values computed by a numerical equation, and suggests a reasonable number of calibration points. In addition, we use both the mean error distance (MED) and hit ratio to evaluate the accuracy of location estimation, while avoiding a biased comparison.

An Evaluation of the Aurora System as a Flesh-Point Tracking Tool for Speech Production Research

Northern Digital Instruments (NDI; Waterloo, Ontario, Canada) manufactures a commercially available magnetometer device called Aurora that features real-time display of sensor position tracked in 3 dimensions. To test its potential for speech production research, data were collected to assess the measurement accuracy and reliability of the system. First, sensors affixed at a known distance on a rigid ruler were moved systematically through the measurement space. Second, sensors attached to the speech articulators of a human participant were tracked during various speech tasks. In the ruler task, results showed mean distance errors of less than 1 mm, with some sensitivity to location within the measurement field. In the speech tasks, Euclidean distance between jaw-mounted sensors showed comparable accuracy; however, a high incidence of missing samples was observed, positively correlated with sensor velocity. The real-time positional feedback provided by the system makes it potentially useful in speech therapy applications. The overall missing data rate observed during speech tasks makes use of the system in its current form problematic for the quantitative measurement of speech articulator movements; however, NDI is actively working to improve the Aurora system for use in this context.

An Integrated Vehicle‐Mounted Telemetry System for VHF Telemetry Applications

Abstract: We designed and developed a vehicle‐mounted very high frequency‐based telemetry system that integrated an on‐board antenna, receiver, electronic compass, Global Positioning System, computer, and Geographic Information System. The system allows users to accurately and quickly obtain fixes, estimate and confirm locations of radiomarked animals, and immediately record data into an electronic spreadsheet or database. The total cost of materials to build the system was $7,349 (United States currency). Mean error angle of 2.63 ± 12.1° (SD; range = −33.7–42.2°) and mean location error distance of 128 ± 91.3 m (SD; range = 0–408 m) suggested precision and accuracy of our system were comparable to other reported systems. Mean time to record 5 bearings/test transmitter was 6.28 ± 0.24 minutes (SE), which is the most efficient system reported to locate animals in the field. Vehicle‐mounted telemetry systems like ours provide additional value to studies that involve tracking highly mobile species because investigators need not take bearings from established receiving stations and because investigators can immediately recognize bounced signals and take additional bearings and optimize accuracy of location estimates.

The Effect of Peripheral Visual Field Loss on Representations of Space: Evidence for Distortion and Adaptation

To determine whether peripheral field loss (PFL) systematically distorts spatial representations and to determine whether persons with actual PFL show adaptation effects. Nine participants with PFL from retinitis pigmentosa (RP) learned the locations of statues in a virtual environment by walking a predetermined route. After this, the statues were removed and the participants were to walk to where they thought each statue had been located. Placement errors, defined as the differences between the actual and estimated locations, were calculated and decomposed into distance errors and angular offsets. Participants showed distortions in remembered statue locations, with mean placement errors increasing with decreasing field of view (FOV) size. A correlation was found between FOV size and mean distance error but not mean angular offsets. Compared with eye movements of normal-vision participants with simulated PFL from a previous study, the eye movements of the RP participants were shorter in duration, and smaller saccadic amplitudes were observed only for the RP participants with the smallest FOV sizes. The RP participants also made more fixations to the statues than the simulated PFL participants. Results from a real-world replication of the task showed no behavioral differences between simulated and naturally occurring PFL. PFL is associated with distortions in spatial representations that increase with decreasing FOV. The differences in eye movement and gaze patterns suggest possible adaptive changes on the part of the RP participants. However, the use of different sampling strategies did not aid the performance of the RP participants as FOV size decreased.

Automated measurement of proprioception following stroke

Background. Proprioception provides feedback which is essential for adequate motor control. Despite having detrimental functional implications, the assessment of proprioception deficits in current clinical practice is mostly qualitative and inadequate for diagnosis and longitudinal monitoring of subtle impairments and their effect on motor function.Purpose. To evaluate a novel quantitative approach to the assessment of proprioception deficits in stroke patients.Method. We designed and implemented an automated protocol where a magnetic motion tracking system and a sensor attached to each of the patient's hands, enables registration of trajectories in 3D coordinates. In this protocol the patient's affected and healthy hands are placed respectively below and above a square board. With vision blocked, the subject's affected hand is passively moved to one of four locations, and then the patient is instructed to actively position the healthy hand directly above his/her perceived location of the affected hand. The positional difference between the two hands is automatically recorded by the system. This procedure is repeated several times and the magnitude and direction of errors are used to quantify the proprioception deficit. The data for this pilot study was collected in a sample of 22 stroke patients and an age-matched group of neurologically intact subjects.Results. Stroke patients had significantly higher mean distance error compared with the control group (average values of 7.9 and 5.3 cm, respectively), and showed higher instability (variance) in repeated performance (average values of the standard deviation of errors 3.4 and 1.8 cm, respectively). Significant correlation was found between the mean distance error and the results of semi-quantitative clinical tests of proprioception.Conclusion. The system provides a reliable quantitative measure of upper limb proprioception, offering considerable advantage over the traditional means applied in the clinic.

In vitro validation of a 3-dimensional transrectal ultrasound system for prostate biopsiess

Introduction: Transrectal ultrasound (TRUS) prostate biopsy (Bx) is currently confined to 2D information to both target and record 3D Bx locations. Accurate placement of Bx needles cannot be verified without 3D information, and recording Bx sites in 2D does not provide sufficient information to accurately guide the high incidence of repeat Bx. We have designed a 3D TRUS prostate Bx system that augments the current 2D TRUS system and provides tools for biopsy-planning, needle guidance, and recording of the biopsy core locations entirely in 3D.
 Methods: Our Bx system displays a 3D model of the patient’s prostate, which is generated intra-procedure from a collection of 2D TRUS images, representative of the particular prostate shape. Bx targets are selected, needle guidance is facilitated, and 3D Bx sites are recorded within the 3D context of the prostate model. The complete 3D Bx system was validated, in vitro, by performing standard ten-core Bx on anatomical phantoms of two patient’s prostates. The accuracy of the needle-guidance, Bx location recording, and 3D model volume and surface topology were validated against a CT gold standard. 
 Results: The Bx system successfully reconstructed the 3D patient prostate models with a mean volume error of 3.2 ± 7.6%. Using the 3D system, needles were accurately guided to the pre-determined targets with a mean error of 2.26 ± 1.03 mm and the 3D locations of the Bx cores were accurately recorded with a mean distance error of 1.47 ± 0.79 mm. 
 Conclusion: We have successfully developed a 3D TRUS prostate biopsy system and validated the system in vitro. A pilot study has been initiated to apply the system clinically.

Prostate brachytherapy seed reconstruction using an adaptive grouping technique

Fluoroscopy-based three-dimensional seed localization as a component of intraoperative dosimetry for prostate brachytherapy is an active area of research. A novel adaptive-grouping-based reconstruction approach is developed. This approach can recover overlapped seeds that are not detected from the fluoroscopic images. Two versions of the adaptive-grouping-based reconstruction approach are implemented and compared to an epipolar geometry-based seed reconstruction technique. Simulations based on nine patient datasets are used to validate the algorithms. A total of 2259 reconstructions is performed in which different types of error such as random noise in seed image locations and ambiguities in projection geometry are incorporated. Among those reconstructions, nine of the cases with overlapping seeds and the different types of error are performed. It is demonstrated that the adaptive-grouping-based reconstruction method is more accurate than the epipolar geometry method and allows faster reconstruction. At a random noise level of 0.6 mm, the mean distance error in reconstructed seed locations is approximately 1.0 mm for one of the relevant cases examined in detail. The best adaptive-grouping-based approach successfully recovered overlapped seeds in the majority of simulated cases (89%), with the remainder of cases generating one false positive seed. Phantom validation is also performed, and overlapped seeds are successfully recovered with all 92 seeds correctly localized and reconstructed. The mean distance error between segmented seed images and projected seeds is 0.5 mm in the phantom study.

Non-parametric geodesic active regions: Method and evaluation for cerebral aneurysms segmentation in 3DRA and CTA

Segmentation of vascular structures is a difficult and challenging task. In this article, we present an algorithm devised for the segmentation of such structures. Our technique consists in a geometric deformable model with associated energy functional that incorporates high-order multiscale features in a non-parametric statistical framework. Although the proposed segmentation method is generic, it has been applied to the segmentation of cerebral aneurysms in 3DRA and CTA. An evaluation study over 10 clinical datasets indicate that the segmentations obtained by our method present a high overlap index with respect to the ground-truth (91.13% and 73.31%, respectively) and that the mean error distance from the surface to the ground truth is close to the in-plane resolution (0.40 and 0.38 mm, respectively). Besides, our technique favorably compares to other alternative techniques based on deformable models, namely parametric geodesic active regions and active contours without edges.

An abdominal aortic aneurysm segmentation method: Level set with region and statistical information

We present a system for segmenting the human aortic aneurysm in CT angiograms (CTA), which, in turn, allows measurements of volume and morphological aspects useful for treatment planning. The system estimates a rough "initial surface," and then refines it using a level set segmentation scheme augmented with two external analyzers: The global region analyzer, which incorporates a priori knowledge of the intensity, volume, and shape of the aorta and other structures, and the local feature analyzer, which uses voxel location, intensity, and texture features to train and drive a support vector machine classifier. Each analyzer outputs a value that corresponds to the likelihood that a given voxel is part of the aneurysm, which is used during level set iteration to control the evolution of the surface. We tested our system using a database of 20 CTA scans of patients with aortic aneurysms. The mean and worst case values of volume overlap, volume error, mean distance error, and maximum distance error relative to human tracing were 95.3% +/- 1.4% (s.d.); worst case = 92.9%, 3.5% +/- 2.5% (s.d.); worst case = 7.0%, 0.6 +/- 0.2 mm (s.d.); worst case = 1.0 mm, and 5.2 +/- 2.3 mm (s.d.); worst case = 9.6 mm, respectively. When implemented on a 2.8 GHz Pentium IV personal computer, the mean time required for segmentation was 7.4 +/- 3.6 min (s.d.). We also performed experiments that suggest that our method is insensitive to parameter changes within 10% of their experimentally determined values. This preliminary study proves feasibility for an accurate, precise, and robust system for segmentation of the abdominal aneurysm from CTA data, and may be of benefit to patients with aortic aneurysms.

An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest

In this study, we have assessed the validity and reliability of an automated labeling system that we have developed for subdividing the human cerebral cortex on magnetic resonance images into gyral based regions of interest (ROIs). Using a dataset of 40 MRI scans we manually identified 34 cortical ROIs in each of the individual hemispheres. This information was then encoded in the form of an atlas that was utilized to automatically label ROIs. To examine the validity, as well as the intra- and inter-rater reliability of the automated system, we used both intraclass correlation coefficients (ICC), and a new method known as mean distance maps, to assess the degree of mismatch between the manual and the automated sets of ROIs. When compared with the manual ROIs, the automated ROIs were highly accurate, with an average ICC of 0.835 across all of the ROIs, and a mean distance error of less than 1 mm. Intra- and inter-rater comparisons yielded little to no difference between the sets of ROIs. These findings suggest that the automated method we have developed for subdividing the human cerebral cortex into standard gyral-based neuroanatomical regions is both anatomically valid and reliable. This method may be useful for both morphometric and functional studies of the cerebral cortex as well as for clinical investigations aimed at tracking the evolution of disease-induced changes over time, including clinical trials in which MRI-based measures are used to examine response to treatment.

Three-dimensional extended field-of-view ultrasound

Three-dimensional (3-D) extended field-of-view ultrasound creates a mosaic view from a set of volumes acquired from a dedicated 3-D ultrasound machine combined with a position tracker. A simple compounding technique can be used to combine the volumes together using only the position measurements, but some misalignment remains. Two different registration methods were developed to correct these errors in the overlapping regions. The first method divides the overlap into smaller blocks and warps the blocks to best align the features. The second method is similar, but uses rigid body registration of the blocks. Experiments in vitro and in vivo showed that block-based registration with warping produced the most reproducible results and the greatest increase in similarity among the overlapping regions. It also produced the best reconstruction accuracy, with a mean distance error of 0.4 mm measured across 101.78 mm in a phantom, representing 0.4% error. (E-mail: rohling@ece.ubc.ca)

Alterations in Upper Extremity Motion after Scapular-Muscle Fatigue

Objective:To determine the effect of scapular fatigue on shoulder and elbow kinematics and accuracy.Design:Pretest–posttest.Setting:Laboratory.Participants:30 healthy men.Interventions:Subjects performed seated overhead throws into a target before and after a standardized scapular-muscle-fatigue protocol.Main Outcome Measurements:Shoulder and elbow kinematic data were analyzed during throwing. Scapular upward rotation was measured (0°, 45°, and 90° humeral elevation in scaption) with an inclinometer. Throwing accuracy was measured as mean error distance from the target (cm).Results:After fatigue, there was a significant increase in total elbow motion (12 % more in cocking phase,P< .05) and elbow velocity in the follow-through phase (average and maximum into flexion,P< .05). Throwing accuracy decreased 26% after fatigue (P< .05).Conclusions:Scapular-muscle fatigue results in compensatory motions at the elbow that might affect performance and contribute to elbow pathologies.

Neuronavigational neuroendoscopic surgery

Considering the separate benefits of neuronavigation and neuroendoscopy, neuroendoscopic surgery with the aid of neuronavigation systems will play an increasingly important role in the future. Bearing this in mind, the present research project was conducted to facilitate neuronavigational neuroendoscopic surgery along the pathway to the prepontine cistern using cadaver heads. A computer-aided, frameless image-guided stereotactic navigation system and a new type of handy rigid-rod neuroendoscope were used. The ideal entry point and the safest trajectory to the prepontine cistern through the foramen of Monro were defined in two formalin-fixed cadaver heads and clinical brain MRI data. Then, maneuvering of the neuroendoscope with the aid of the neuronavigation system was performed. Straight trajectories from the entry point to the prepontine cistern could be designed. For the registration accuracy of the tip of the neuroendoscope, the virtual image registered a mean error distance of 5.42 mm away from the reference point along the axis of vertical line. However, free-hand maneuvering enabled the neuroendoscope to be finely manipulated without damaging brain tissues. Neuroendoscopic anatomical views of the interpeduncular and prepontine cistern were also acquired. Interactive use of free-hand maneuvering of the handy rigid-rod neuroendoscope together with frameless neuronavigation systems plot the way to true neuronavigational neuroendoscopic surgery in a safe and reliable manner. This pairing of the most recent technological neurosurgical options with better understanding of neuroendoscopic anatomy enables the neurosurgeon to acquire broader treatment options for central nervous system diseases.

Electromagnetic Catheter Navigation During Bronchoscopy: Validation of a Novel Method by Conventional Fluoroscopy

Electromagnetic navigation in bronchoscopy is a novel method for assisting in the localization of peripheral lung lesions. To assess the usability, accuracy, and safety of electromagnetic navigation during flexible bronchoscopy in a clinical setting. Prospective evaluation. Consecutive patients referred to the bronchoscopy unit for the diagnosis of peripheral infiltrates or solitary pulmonary nodules (SPNs). Navigation was performed using an electromagnetic tracking system with a position sensor encapsulated in the tip of a flexible catheter that was pushed through the working channel of the bronchoscope. Real-time, multiplanar reconstruction of a previously acquired CT data set provided three-dimensional views for localization of the catheter. To match the position of the sensor with the CT scan, four anatomic landmarks were used for registration. The sensor position generated in the navigation system was controlled by fluoroscopy, and the corresponding error distances were measured. This was performed with all SPNs and at two different peripheral locations of the right upper lobe (RUL). Sixteen patients (10 men and 6 women; mean age, 63.7 years) were studied. Navigation prolonged bronchoscopy by 3.9 +/- 1.3 min (mean +/- SD). The navigation system identified all lesions. The position sensor achieved a direct hit in three of five SPNs. Fluoroscopy failed to recognize three SPNs (60%) and three infiltrates (38%). The mean error distances between sensor tip position and fluoroscopically verified RUL reference position were 10.4 mm (lateral position) and 12.5 mm (apical position) respectively. The mean error distances between the sensor tip and two endobronchial registration points at the end of the procedure were 4.2 mm and 5.1 mm, respectively. Electromagnetic navigation is useful, accurate, and safe in the localization of peripheral lung lesions and may help to improve the yield of diagnostic bronchoscopic procedures.