Automatic on-line electronic portal image analysis with a wavelet-based edge detector

A frequency-based approach to locate common structure for 2D-3D intensity-based registration of setup images in prostate radiotherapy

In many radiotherapy clinics, geometric uncertainties in the delivery of 3D conformal radiation therapy and intensity modulated radiation therapy of the prostate are reduced by aligning the patient's bony anatomy in the planning 3D CT to corresponding bony anatomy in 2D portal images acquired before every treatment fraction. In this paper, we seek to determine if there is a frequency band within the portal images and the digitally reconstructed radiographs (DRRs) of the planning CT in which bony anatomy predominates over non-bony anatomy such that portal images and DRRs can be suitably filtered to achieve high registration accuracy in an automated 2D-3D single portal intensity-based registration framework. Two similarity measures, mutual information and the Pearson correlation coefficient were tested on carefully collected gold-standard data consisting of a kilovoltage cone-beam CT (CBCT) and megavoltage portal images in the anterior-posterior (AP) view of an anthropomorphic phantom acquired under clinical conditions at known poses, and on patient data. It was found that filtering the portal images and DRRs during the registration considerably improved registration performance. Without filtering, the registration did not always converge while with filtering it always converged to an accurate solution. For the pose-determination experiments conducted on the anthropomorphic phantom with the correlation coefficient, the mean (and standard deviation) of the absolute errors in recovering each of the six transformation parameters were Theta(x):0.18(0.19) degrees, Theta(y):0.04(0.04) degrees, Theta(z):0.04(0.02) degrees, t(x):0.14(0.15) mm, t(y):0.09(0.05) mm, and t(z):0.49(0.40) mm. The mutual information-based registration with filtered images also resulted in similarly small errors. For the patient data, visual inspection of the superimposed registered images showed that they were correctly aligned in all instances. The results presented in this paper suggest that robust and accurate registration can be achieved with intensity-based methods by focusing on rigid bony structures in the images while diminishing the influence of artifacts with similar frequencies as soft tissue.

Accuracy of an automatic patient-positioning system based on the correlation of two edge images in radiotherapy

We have clinically evaluated the accuracy of an automatic patient-positioning system based on the image correlation of two edge images in radiotherapy. Ninety-six head & neck images from eight patients undergoing proton therapy were compared with a digitally reconstructed radiograph (DRR) of planning CT. Two edge images, a reference image and a test image, were extracted by applying a Canny edge detector algorithm to a DRR and a 2D X-ray image, respectively, of each patient before positioning. In a simulation using a humanoid phantom, performed to verify the effectiveness of the proposed method, no registration errors were observed for given ranges of rotation, pitch, and translation in the x, y, and z directions. For real patients, however, there were discrepancies between the automatic positioning method and manual positioning by physicians or technicians. Using edged head coronal- and sagittal-view images, the average differences in registration between these two methods for the x, y, and z directions were 0.11 cm, 0.09 cm and 0.11 cm, respectively, whereas the maximum discrepancies were 0.34 cm, 0.38 cm, and 0.50 cm, respectively. For rotation and pitch, the average registration errors were 0.95° and 1.00°, respectively, and the maximum errors were 3.6° and 2.3°, respectively. The proposed automatic patient-positioning system based on edge image comparison was relatively accurate for head and neck patients. However, image deformation during treatment may render the automatic method less accurate, since the test image many differ significantly from the reference image.

Automated 2D-3D registration of portal images and CT data using line-segment enhancement

In prostate radiotherapy, setup errors with respect to the patient's bony anatomy can be reduced by aligning 2D megavoltage (MV) portal images acquired during treatment to a reference 3D kilovoltage (kV) CT acquired for treatment planning purposes. The purpose of this study was to evaluate a fully automated 2D-3D registration algorithm to quantify setup errors in 3D through the alignment of line-enhanced portal images and digitally reconstructed radiographs computed from the CT. The line-enhanced images were obtained by correlating the images with a filter bank of short line segments, or "sticks" at different orientations. The proposed methods were validated on (1) accurately collected gold-standard data consisting of a 3D kV cone-beam CT scan of an anthropomorphic phantom of the pelvis and 2D MV portal images in the anterior-posterior (AP) view acquired at 15 different poses and (2) a conventional 3D kV CT scan and weekly 2D MV AP portal images of a patient over 8 weeks. The mean (and standard deviation) of the absolute registration error for rotations around the right-lateral (RL), inferior-superior (IS), and posterior-anterior (PA) axes were 0.212 degree (0.214 degree), 0.055 degree (0.033 degree) and 0.041 degree (0.039 degree), respectively. The corresponding registration errors for translations along the RL, IS, and PA axes were 0.161 (0.131) mm, 0.096 (0.033) mm, and 0.612 (0.485) mm. The mean (and standard deviation) of the total registration error was 0.778 (0.543) mm. Registration on the patient images was successful in all eight cases as determined visually. The results indicate that it is feasible to automatically enhance features in MV portal images of the pelvis for use within a completely automated 2D-3D registration framework for the accurate determination of patient setup errors. They also indicate that it is feasible to estimate all six transformation parameters from a 3D CT of the pelvis and a single portal image in the AP view.

Edge detection of the radiation field in double exposure portal images using a curve propagation algorithm

An accurate detection of the radiation field is crucial to 3D conformal radiotherapy (3D‐CRT). Automated techniques to detect the field edges on double exposure portal images have previously focused on thresholding techniques. In this paper, we present a new approach based on a curve propagation technique (the Fast Marching method) which proves to be more effective at detecting the radiation field than its thresholding counterpart. The comparison of both techniques in terms of computational speed and effectiveness of the detection is presented using complex images with non‐homogeneous intensity levels inside the radiation field, and gradual variations in intensity level at the field boundaries. Results show that our Fast Marching method is easier to automate, and converges faster to the boundaries of the segmented radiation field. The computation time of the Fast Marching technique is five times faster in typical portal images.

PACS numbers: 87.53.Oq, 87.57.Nk, 87.57.‐s.

High antinoise photoacoustic tomography based on a modified filtered backprojection algorithm with combination wavelet

How to extract the weak photoacoustic signals from the collected signals with high noise is the key to photoacoustic signal processing. We have developed a modified filtered backprojection algorithm based on combination wavelet for high antinoise photoacoustic tomography. A Q-switched-Nd: yttrium-aluminum-garnet laser operating at 532 nm is used as light source. The laser has a pulse width of 7 ns and a repetition frequency of 20 Hz. A needle polyvinylidene fluoride hydrophone with diameter of 1 mm is used to capture photoacoustic signals. The modified algorithm is successfully applied to imaging vascular network of a chick embryo chorioallantoic membrane in situ and brain structure of a rat brain in vivo, respectively. In the reconstructed images, almost all of the capillary vessels and the vascular ramifications of the chick embryo chorioallantoic membrane are accurately resolved, and the detailed brain structures of the rat brain organization are clearly identified with the skull and scalp intact. The experimental results demonstrate that the modified algorithm has much higher antinoise capacity, and can greatly improve the reconstruction image quality. The spatial resolution of the reconstructed images can reach 204 microm. The modified filtered back-projection algorithm based on the combination wavelet has the potential in the practical high-noise signal processing for deeply penetrating photoacoustic tomography.

Optimal control of set-up margins and internal margins for intra- and extracranial radiotherapy using stereoscopic kilovoltage imaging

In this paper the clinical introduction of stereoscopic kV-imaging in combination with a 6 degrees-of-freedom (6 DOF) robotics system and breathing synchronized irradiation will be discussed in view of optimally reducing interfractional as well as intrafractional geometric uncertainties in conformal radiation therapy. Extracranial cases represent approximately 70% of the patient population on the NOVALIS treatment machine (BrainLAB A.G., Germany) at the AZ-VUB, which is largely due to the efficiency of the real-time positioning features of the kV-imaging system. The prostate case will be used as an example of those target volumes showing considerable changes in position from day-to-day, yet with negligible motion during the actual course of the treatment. As such it will be used to illustrate the on-line target localization using kV-imaging and 6 DOF patient adjustment with and without implanted radio-opaque markers prior to treatment. Small lung lesion will be used to illustrate the system's potential to synchronize the irradiation with breathing in coping with intrafractional organ motion.

Automated 2D-3D registration of a radiograph and a cone beam CT using line-segment enhancement

The objective of this study was to develop a fully automated two-dimensional (2D)-three-dimensional (3D) registration framework to quantify setup deviations in prostate radiation therapy from cone beam CT (CBCT) data and a single AP radiograph. A kilovoltage CBCT image and kilovoltage AP radiograph of an anthropomorphic phantom of the pelvis were acquired at 14 accurately known positions. The shifts in the phantom position were subsequently estimated by registering digitally reconstructed radiographs (DRRs) from the 3D CBCT scan to the AP radiographs through the correlation of enhanced linear image features mainly representing bony ridges. Linear features were enhanced by filtering the images with "sticks," short line segments which are varied in orientation to achieve the maximum projection value at every pixel in the image. The mean (and standard deviations) of the absolute errors in estimating translations along the three orthogonal axes in millimeters were 0.134 (0.096) AP(out-of-plane), 0.021 (0.023) ML and 0.020 (0.020) SI. The corresponding errors for rotations in degrees were 0.011 (0.009) AP, 0.029 (0.016) ML (out-of-plane), and 0.030 (0.028) SI (out-of-plane). Preliminary results with megavoltage patient data have also been reported. The results suggest that it may be possible to enhance anatomic features that are common to DRRs from a CBCT image and a single AP radiography of the pelvis for use in a completely automated and accurate 2D-3D registration framework for setup verification in prostate radiotherapy. This technique is theoretically applicable to other rigid bony structures such as the cranial vault or skull base and piecewise rigid structures such as the spine.

Improvement of image quality in chest MDCT using nonlinear wavelet shrinkage with trimmed-thresholding

Multidetector-row computed tomography (MDCT) has dramatically increased the speed of scanning, and allows high-resolution imaging compared with conventional single detector-row CT (SDCT). However, the use MDCT makes use of an increase in volume scanning, and causes a simultaneous increase in radiation dose to the patient. Thus, the radiation dose from the X-ray CT has become a problem in recent years. In this study, nonlinear wavelet-based edge preservation de-noising using trimmed-thresholding was applied to reconstructed low-dose chest MDCT images, and optimal wavelet processing including wavelet functions and thresholding methods was examined. Moreover, the usefulness of the de-noising for reducing radiation dose was examined. As a result of optimized edge preservation de-noising, noise reduction was achieved with little deterioration in image quality, and the wavelet function used at that time was Coiflet's with shorter support. As a result, almost the same quality of reconstructed image of the chest phantom was obtained for conventional scanning and low-dose scanning with the wavelet de-noising method using trimmed- thresholding. That is, the radiation dose from MDCT could be reduced using this wavelet-based de-noising method.

Patient positioning method based on binary image correlation between two edge images for proton-beam radiation therapy

A new technique based on normalized binary image correlation between two edge images has been proposed for positioning proton-beam radiotherapy patients. A Canny edge detector was used to extract two edge images from a reference x-ray image and a test x-ray image of a patient before positioning. While translating and rotating the edged test image, the absolute value of the normalized binary image correlation between the two edge images is iteratively maximized. Each time before rotation, dilation is applied to the edged test image to avoid a steep reduction of the image correlation. To evaluate robustness of the proposed method, a simulation has been carried out using 240 simulated edged head front-view images extracted from a reference image by varying parameters of the Canny algorithm with a given range of rotation angles and translation amounts in x and y directions. It was shown that resulting registration errors have an accuracy of one pixel in x and y directions and zero degrees in rotation, even when the number of edge pixels significantly differs between the edged reference image and the edged simulation image. Subsequently, positioning experiments using several sets of head, lung, and hip data have been performed. We have observed that the differences of translation and rotation between manual positioning and the proposed method were within one pixel in translation and one degree in rotation. From the results of the validation study, it can be concluded that a significant reduction in workload for the physicians and technicians can be achieved with this method.

Quality assurance of a system for improved target localization and patient set-up that combines real-time infrared tracking and stereoscopic X-ray imaging

BACKGROUND AND PURPOSE

The aim of this study is to investigate the positional accuracy of a prototype X-ray imaging tool in combination with a real-time infrared tracking device allowing automated patient set-up in three dimensions.

MATERIAL AND METHODS

A prototype X-ray imaging tool has been integrated with a commercially released real-time infrared tracking device. The system, consisting of two X-ray tubes mounted to the ceiling and a centrally located amorphous silicon detector has been developed for automated patient positioning from outside the treatment room prior to treatment. Two major functions are supported: (a) automated fusion of the actual treatment images with digitally reconstructed radiographs (DRRs) representing the desired position; (b) matching of implanted radio opaque markers. Measurements of known translational (up to 30.0mm) and rotational (up to 4.0 degrees ) set-up errors in three dimensions as well as hidden target tests have been performed on anthropomorphic phantoms.

RESULTS

The system's accuracy can be represented with the mean three-dimensional displacement vector, which yielded 0.6mm (with an overall SD of 0.9mm) for the fusion of DRRs and X-ray images. Average deviations between known translational errors and calculations varied from -0.3 to 0.6mm with a standard deviation in the range of 0.6-1.2mm. The marker matching algorithm yielded a three-dimensional uncertainty of 0.3mm (overall SD: 0.4mm), with averages ranging from 0.0 to 0.3mm and a standard deviation in the range between 0.3 and 0.4mm.

CONCLUSIONS

The stereoscopic X-ray imaging device integrated with the real-time infrared tracking device represents a positioning tool allowing for the geometrical accuracy that is required for conformal radiation therapy of abdominal and pelvic lesions, within an acceptable time-frame.

Thresholds for human detection of patient setup errors in digitally reconstructed portal images of prostate fields

PURPOSE

Computer-assisted methods to analyze electronic portal images for the presence of treatment setup errors should be studied in controlled experiments before use in the clinical setting. Validation experiments using images that contain known errors usually report the smallest errors that can be detected by the image analysis algorithm. This paper offers human error-detection thresholds as one benchmark for evaluating the smallest errors detected by algorithms. Unfortunately, reliable data are lacking describing human performance. The most rigorous benchmarks for human performance are obtained under conditions that favor error detection. To establish such benchmarks, controlled observer studies were carried out to determine the thresholds of detectability for in-plane and out-of-plane translation and rotation setup errors introduced into digitally reconstructed portal radiographs (DRPRs) of prostate fields.

METHODS AND MATERIALS

Seventeen observers comprising radiation oncologists, radiation oncology residents, physicists, and therapy students participated in a two-alternative forced choice experiment involving 378 DRPRs computed using the National Library of Medicine Visible Human data sets. An observer viewed three images at a time displayed on adjacent computer monitors. Each image triplet included a reference digitally reconstructed radiograph displayed on the central monitor and two DRPRs displayed on the flanking monitors. One DRPR was error free. The other DRPR contained a known in-plane or out-of-plane error in the placement of the treatment field over a target region in the pelvis. The range for each type of error was determined from pilot observer studies based on a Probit model for error detection. The smallest errors approached the limit of human visual capability. The observer was told what kind of error was introduced, and was asked to choose the DRPR that contained the error. Observer decisions were recorded and analyzed using repeated-measures analysis of variance.

RESULTS

The thresholds of detectability averaged over all observers were approximately 2.5 mm for in-plane translations, 1.6 degrees for in-plane rotations, 1 degrees for out-of-plane rotations, and 8% change in magnification for out-of-plane translations along the central axis. When one inexperienced observer is excluded, the average threshold for change in magnification is 5%. Experienced observers tended to perform better, but differences between groups were not statistically significant. Thresholds were computed as averages over all observers. Because of the broad range of observer capabilities, some detection tasks were too difficult for some observers, leading to missing threshold values in our data analysis. The missing values were excluded from computation of the average thresholds reported above. The effect of the missing values is to bias the average values toward the best human performance.

CONCLUSIONS

Under favorable conditions, humans can detect small errors in setup geometry. The thresholds for error detection reported in this study are believed to represent rigorous but reasonable benchmarks that can be incorporated into studies evaluating algorithms for computer-assisted detection of setup errors in electronic portal images.

Remote control for a stand-alone freely movable treatment couch with limitation system

One of our linear accelerators is equipped with a free-movable treatment couch. An additional projects was to develop a system that first protects the free-movable couch against collisions, secondly build a remote control for moving the couch from outside the treatment room and finally implement this remote control/limitation system in an automatic position algorithm using an electronic portal image. The latter has been the subject of an on-going departmental investigation on intra-fractional correction of set-up errors. A few years ago, we developed a limitation system to protect both the table and the accelerator against collisions. In this paper we describe the second part of this project, the remote control system.

Portal imaging

Portal imaging is the acquisition of images with a radiotherapy beam. Imaging theory suggests that the quality of portal images could be much higher if the efficiency of the imaging media in detecting radiation could be improved. Introduction of new media (films and electronic portal imaging devices) has confirmed this by markedly increasing the quality of portal images. Images from these devices can then be used to verify a patient's treatment. Geometric verification requires the portal image to be registered with a reference image. Dosimetric verification requires the portal imager to be calibrated for dose. This review gives a brief overview of the current areas of interest in portal imaging: imaging theory; imaging media, film and electronic portal imaging devices; image registration; and dosimetry using these devices.

Feasibility of automatic marker detection with an a-Si flat-panel imager

Here we study automatic detection of implanted gold markers relative to the field boundary in portal images for on-line position verification. Portal images containing 1-2 MU were taken with an amorphous silicon flat-panel imager. The images were obtained with lateral field at 18 MV. Both the detection success rate and the localization accuracy of markers of 1.0 and 1.2 mm diameter were determined with the help of a marker detection method based on a marker extraction kernel. A method for determining a fiducial reference point related to the field boundary was developed. Detection success rates were 0.99, 0.90 and 0.95 for markers of 1.2 mm diameter and 5 mm length, 1.0 mm diameter and 5 mm length and 1.0 mm diameter and 10 mm length respectively. The localization accuracy appeared to be better than 0.3 mm. The reference point could be reproduced with an accuracy equal to 1 pixel (0.5 mm at isocentre) within one fraction. During the first few seconds of a treatment fraction the field edge was not stable, which appeared to be an effect of the motion of the radiation source. Thanks to the use an a-Si flat-panel imager, on-line position verification using implanted gold markers becomes clinically feasible. We can use a clinically acceptable marker diameter as small as 1.0 mm. These markers can be automatically detected in portal images obtained with 1-2 MU relative to a stable reference point related to the field boundary.

A computerized remote table control for fast on-line patient repositioning: implementation and clinical feasibility

A computerized remote control for a Siemens ZXT treatment couch was implemented and its characteristics were investigated to establish its feasibility for on-line setup corrections, using portal imaging. Communication with the table was obtained by connecting it via a serial line to a work station. The treatment couch enables "goto" commands in the three main directions and around the isocenter. The accuracy of the movements after giving such a command was checked and the time for each movement was recorded. First, the movements into a single direction were studied (range of -4 to +4 cm and -4 degrees to +4 degrees). Each command was repeated four times. Second, the table was moved into the three main directions simultaneously. For this experiment a clinically relevant three-dimensional (3-D) normal distribution of shifts was used [N = 200, standard deviation (SD) 5 mm in the three main directions]. This latter experiment was done twice: without and with rotations (a distribution with SD 1 degrees). During the first experiment, with shifts into one direction, no systematic deviations were found. The overall accuracy of the shifts was 0.6 mm (1 SD) in each direction and 0.04 degrees (1 SD) for the rotations. The time required for a translation ranged between 4 and 13 s and for the rotation between 8 and 20 s. The second experiment with the 3-D distribution of setup errors yielded an error in the 3-D vector length equal to 0.96 mm (1 SD), independent of rotations. Shifts were performed in less than 11 s for 95% of the cases without rotations. When rotations were also performed, 95% of the movements finished in less than 16 s. In conclusion, the table movements are accurate and enable on-line setup corrections in daily clinical practice.