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At least 271 records · Page 15

TU-C-17A-03: An Integrated Contour Evaluation Software Tool Using Supervised Pattern Recognition for Radiotherapy

Purpose: Radiotherapy (RT) contours delineated either manually or semiautomatically require verification before clinical usage. Manual evaluation is very time consuming. A new integrated software tool using supervised pattern contour recognition was thus developed to facilitate this process. Methods: The contouring tool was developed using an object-oriented programming language C# and application programming interfaces, e.g. visualization toolkit (VTK). The C# language served as the tool design basis. The Accord.Net scientific computing libraries were utilized for the required statistical data processing and pattern recognition, while the VTK was used to build and render 3-D mesh models from critical RT structures in real-time and 360° visualization. Principal component analysis (PCA) was used for system self-updating geometry variations of normal structures based on physician-approved RT contours as a training dataset. The inhouse design of supervised PCA-based contour recognition method was used for automatically evaluating contour normality/abnormality. The function for reporting the contour evaluation results was implemented by using C# and Windows Form Designer. Results: The software input was RT simulation images and RT structures from commercial clinical treatment planning systems. Several abilities were demonstrated: automatic assessment of RT contours, file loading/saving of various modality medical images and RT contours, and generation/visualization of 3-D images and anatomical models. Moreover, it supported the 360° rendering of the RT structures in a multi-slice view, which allows physicians to visually check and edit abnormally contoured structures. Conclusion: This new software integrates the supervised learning framework with image processing and graphical visualization modules for RT contour verification. This tool has great potential for facilitating treatment planning with the assistance of an automatic contour evaluation module in avoiding unnecessary manual verification for physicians/dosimetrists. In addition, its nature as a compact and stand-alone tool allows for future extensibility to include additional functions for physicians’ clinical needs.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

WE-G-209-00: Identifying Image Artifacts, Their Causes, and How to Fix Them

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.

60 APPLIED LIFE SCIENCES↗

Time-Encoded Imagers

We have developed two neutron detector systems based on time-encoded imaging and demonstrated their applicability toward non-proliferation missions. The 1D-TEI system was designed for and evaluated against the ability to detect Special Nuclear Material (SNM) in very low signal to noise environments; in particular, very large stand-off and/or weak sources that may be shielded. We have demonstrated significant detection (>5 sigma) of a 2.8e5 n/s neutron fission source at 100 meters stand-off in 30 min. If scaled to an IAEA significant quantity of Pu, we estimate that this could be reduced to as few as ~5 minutes. In contrast to simple counting detectors, this was accomplished without the need of previous background measurements. The 2D-TEI system was designed for high resolution spatial mapping of distributions of SNM and proved feasibility of twodimensional fast neutron imaging using the time encoded modulation of rates on a single pixel detector. Because of the simplicity of the TEI design, there is much lower systematic uncertainty in the detector response typical coded apertures. Other imaging methods require either multiple interactions (e.g. neutron scatter camera or Compton imagers), leading to intrinsically low efficiencies, or spatial modulation of the signal (e.g., Neutron Coded Aperture Imager (Hausladen, 2012)), which requires a complicated, high channel count, and expensive position sensitive detector. In contrast, a single detector using a time-modulated collimator can encode directional information in the time distribution of detected events. This is the first investigation of time-encoded imaging for nuclear nonproliferation applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

SU-F-I-15: Evaluation of a New MR-Compatible Respiratory Motion Device at 3T

Purpose: Recent advances in MRI-guided radiotherapy has inspired the development of MRI-compatible motion devices that simulate patient periodic motion in the scanner, particularly respiratory motion. Most commercial devices rely on non MR-safe ferromagnetic stepper motors which are not practical for regular QA testing. This work evaluates the motion performance of a new fully MRI compatible respiratory motion device at 3T. Methods: The QUASAR™ MRI-compatible respiratory motion phantom has been recently developed by Modus QA Inc., London, ON, Canada. The prototype is constructed from diamagnetic materials with linear motion generated using MRI-compatible piezoelectric motors that can be safely inserted in the scanner bore. The tumor was represented by a fillable sphere and is attached to the linear motion generator. The spherical tumor-representative and its surroundings were filled with different concentrations of MnCl2 to produce realistic relaxation times. The motion was generated along the longitudinal (H/F) axis of the bore using sinusoidal reference waveform (amplitude = 15 mm, frequency 0.25 Hz). Imaging was then performed on 3T Philips Achieva using a 32-channel cardiac coil. Fast 2D spoiled gradient-echo was used with a spatial resolution of 1.8 × 1.8 mm{sup 2} and slice thickness of 4 mm. The motion waveform was then measured on the resultant image series by tracking the centroid of the sphere through the time series. This image-derived measured motion was compared to the software-generated reference waveform. Results: No visible distortions from the device were observed on the images. Excellent agreement between the measured and the reference waveforms were obtained. Negligible motion was observed in the lateral (R/L) direction. Conclusion: Our investigation demonstrates that this piezo-electric motor design is effective at simulating periodic motion and is a potential candidate for MRI-radiotherapy respiratory motion simulation. Future work should focus on evaluating non-sinusoidal waveforms, fast 3D pulse sequences, and perform dosimetric QA.

60 APPLIED LIFE SCIENCES↗

TU-FG-209-11: Validation of a Channelized Hotelling Observer to Optimize Chest Radiography Image Processing for Nodule Detection: A Human Observer Study

Purpose: To validate the use of a Channelized Hotelling Observer (CHO) model for guiding image processing parameter selection and enable improved nodule detection in digital chest radiography. Methods: In a previous study, an anthropomorphic chest phantom was imaged with and without PMMA simulated nodules using a GE Discovery XR656 digital radiography system. The impact of image processing parameters was then explored using a CHO with 10 Laguerre-Gauss channels. In this work, we validate the CHO’s trend in nodule detectability as a function of two processing parameters by conducting a signal-known-exactly, multi-reader-multi-case (MRMC) ROC observer study. Five naive readers scored confidence of nodule visualization in 384 images with 50% nodule prevalence. The image backgrounds were regions-of-interest extracted from 6 normal patient scans, and the digitally inserted simulated nodules were obtained from phantom data in previous work. Each patient image was processed with both a near-optimal and a worst-case parameter combination, as determined by the CHO for nodule detection. The same 192 ROIs were used for each image processing method, with 32 randomly selected lung ROIs per patient image. Finally, the MRMC data was analyzed using the freely available iMRMC software of Gallas et al. Results: The image processing parameters which were optimized for the CHO led to a statistically significant improvement (p=0.049) in human observer AUC from 0.78 to 0.86, relative to the image processing implementation which produced the lowest CHO performance. Conclusion: Differences in user-selectable image processing methods on a commercially available digital radiography system were shown to have a marked impact on performance of human observers in the task of lung nodule detection. Further, the effect of processing on humans was similar to the effect on CHO performance. Future work will expand this study to include a wider range of detection/classification tasks and more observers, including experienced chest radiologists.

60 APPLIED LIFE SCIENCES↗

WE-G-209-01: Digital Radiography

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.

60 APPLIED LIFE SCIENCES↗

WE-G-209-02: CT

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.

60 APPLIED LIFE SCIENCES↗

WE-G-209-03: PET

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.

60 APPLIED LIFE SCIENCES↗

WE-G-209-04: MRI

Digital radiography, CT, PET, and MR are complicated imaging modalities which are composed of many hardware and software components. These components work together in a highly coordinated chain of events with the intent to produce high quality images. Acquisition, processing and reconstruction of data must occur in a precise way for optimum image quality to be achieved. Any error or unexpected event in the entire process can produce unwanted pixel intensities in the final images which may contribute to visible image artifacts. The diagnostic imaging physicist is uniquely qualified to investigate and contribute to resolution of image artifacts. This course will teach the participant to identify common artifacts found clinically in digital radiography, CT, PET, and MR, to determine the causes of artifacts, and to make recommendations for how to resolve artifacts. Learning Objectives: Identify common artifacts found clinically in digital radiography, CT, PET and MR. Determine causes of various clinical artifacts from digital radiography, CT, PET and MR. Describe how to resolve various clinical artifacts from digital radiography, CT, PET and MR.

60 APPLIED LIFE SCIENCES↗

An Application of Multi-band Forced Photometry to One Square Degree of SERVS: Accurate Photometric Redshifts and Implications for Future Science

We apply The Tractor image modeling code to improve upon existing multi-band photometry for the Spitzer Extragalactic Representative Volume Survey (SERVS). SERVS consists of post-cryogenic Spitzer observations at 3.6 and 4.5 μ m over five well-studied deep fields spanning 18 deg{sup 2}. In concert with data from ground-based near-infrared (NIR) and optical surveys, SERVS aims to provide a census of the properties of massive galaxies out to z ≈ 5. To accomplish this, we are using The Tractor to perform “forced photometry.” This technique employs prior measurements of source positions and surface brightness profiles from a high-resolution fiducial band from the VISTA Deep Extragalactic Observations survey to model and fit the fluxes at lower-resolution bands. We discuss our implementation of The Tractor over a square-degree test region within the XMM Large Scale Structure field with deep imaging in 12 NIR/optical bands. Our new multi-band source catalogs offer a number of advantages over traditional position-matched catalogs, including (1) consistent source cross-identification between bands, (2) de-blending of sources that are clearly resolved in the fiducial band but blended in the lower resolution SERVS data, (3) a higher source detection fraction in each band, (4) a larger number of candidate galaxies in the redshift range 5 < z < 6, and (5) a statistically significant improvement in the photometric redshift accuracy as evidenced by the significant decrease in the fraction of outliers compared to spectroscopic redshifts. Thus, forced photometry using The Tractor offers a means of improving the accuracy of multi-band extragalactic surveys designed for galaxy evolution studies. We will extend our application of this technique to the full SERVS footprint in the future.

79 ASTRONOMY AND ASTROPHYSICS↗

SU-F-T-302: Implementation of the RadCalc Image Analysis Tool for IMRT QA

Purpose: To assess RadCalc as a means for analyzing fluence maps of IMRT QA patient plans. Eclipse generated fluence maps were compared to RadCalc fluence maps generated from both Eclipse parameters and from dynalog trajectory files. Methods: Six IMRT plans consisting of fifty individual fields were compared both field-by-field and as composite plans. These plans were exported from Eclipse to RadCalc. Each plan was then delivered in QA mode on a Varian Clinac iX, while recording and saving the dynalog trajectory files. These files were then imported into RadCalc, providing three sources of generating fluence maps: Eclipse, RadCalc, and dynalog files. Using the image analysis tool in RadCalc, a gamma analysis was then performed as a point-by-point comparison for each IMRT field. The Eclipse fluence map was used as the baseline for each comparison. Results: Based on the manufacturer’s recommendations, all fields were normalized to the maximum pixel value within each Eclipse field. All data was analyzed using a gamma index of 3mm/3% with passing criteria of 90%. For both dynalog analysis and RadCalc fluence analysis, 48/50 created fluence maps passed at greater than 90% when compared with the Eclipse baseline. In analyzing the composite of each of the six patients’ plans, all plans passed over 90%. Conclusion: Using the dynalog trajectory files in combination with RadCalc Version 6.3 image analysis is a promising metric for verifying IMRT QA passing rates. Notably, if a field failed, it did so for both dynalog and RadCalc compared to Eclipse. This suggests RadCalc can accurately simulate fluence maps, with similar results to dynalog comparisons. Limitations within the RadCalc software were discovered in the analytical process such as pixel resolution and the inability to set minimum threshold values. Comparisons could be extended to include dose map and distance to agreement analysis by expanding software capabilities.

60 APPLIED LIFE SCIENCES↗

SU-E-T-33: An EPID-Based Method for Testing Absolute Leaf Position for MLC Without Backup Jaws

Purpose: Methods in common use for MLC leaf position QA are limited to measurements relative to an arbitrary reference position. The authors previously presented an EPID-based method for efficiently testing accuracy of leaf position relative to the mechanical isocenter for MLC with backup jaws. The purpose of this work is to extend that method to the general case of MLC without backup jaws. Methods: A pair of collimator walkout images is used to determine the location of the mechanical isocenter relative to the center of one field using a parameter called X-offset. The method allows for shift of the imager panel to cover subsets of MLC leaves within the limited field of view of the imager. For a shifted panel position, an image of three beam strips defined by a subset of MLC leaves allows determination of the position of each leaf relative to the isocenter. The location of the isocenter is determined by applying X-offset to an image of a single rectangular field obtained at that panel position. The method can also be used to test backup jaws instead of MLC leaves. A software tool was developed to efficiently analyze the images. Results: The software tool reports leaf position and deviation from nominal position, and provides visual displays to facilitate rapid qualitative interpretation. Test results using this method agree well with results using the previous method requiring backup jaws. Test results have been successfully used to recalibrate one model MLC (Elekta MLCi2™). Work in progress includes extension of the software tool to other MLC models, and quantification of reproducibility of the measurements. Conclusion: This work successfully demonstrates a method to efficiently and accurately measure MLC leaf position, or backup jaw position, relative to the mechanical isocenter of the collimator.

60 APPLIED LIFE SCIENCES↗

SU-E-T-252: On the Evaluation of Patient Specific IMRT QA Using EPID, Dynalog Files and Patient Anatomy

Purpose: This research, investigates the viability of using the Electronic portal imaging device (EPID) coupled with the treatment planning system (TPS), to calculate the doses delivered and verify agreement with the treatment plan. The results of QA analysis using the EPID, Delta4 and fluence calculations using the multi-leaf collimator (MLC) dynalog files on 10 IMRT patients are presented in this study. Methods: EPID Fluence Images in integrated mode and Dynalog files for each field were acquired for 10 IMRT (6MV) patients and processed through an in house MatLab program to create an opening density matrix (ODM) which was used as the input fluence for dose calculation with the TPS (Pinnacle3, Philips). The EPID used in this study was the aSi1000 Varian on a Novalis TX linac equipped with high definition MLC. The resulting dose distributions were then exported to VeriSoft (PTW) where a 3D gamma was calculated using 3mm-3% criteria. The Scandidos Delta4 phantom was also used to measure a 2D dose distribution for all 10 patients and a 2D gamma was calculated for each patient using the Delta4 software. Results: The average 3D gamma for all 10 patients using the EPID images was 98.2% ± 2.6%. The average 3D gamma using the dynalog files was 94.6% ± 4.9%. The average 2D gamma from the Delta4 was 98.1% ± 2.5%. The minimum 3D gamma for the EPID and dynalog reconstructed dose distributions was found on the same patient which had a very large PTV, requiring the jaws to open to the maximum field size. Conclusion: Use of the EPID, combined with a TPS is a viable method for QA of IMRT plans. A larger ODM size can be implemented to accommodate larger field sizes. An adaptation of this process to Volumetric Arc Therapy (VMAT) is currently under way.

60 APPLIED LIFE SCIENCES↗

SU-E-J-104: Evaluation of Accuracy for Various Deformable Image Registrations with Virtual Deformation QA Software

Purpose: The accuracy of deformable image registration (DIR) has a significant dosimetric impact in radiation treatment planning. We evaluated accuracy of various DIR algorithms using virtual deformation QA software (ImSimQA, Oncology System Limited, UK). Methods: The reference image (Iref) and volume (Vref) was first generated with IMSIMQA software. We deformed Iref with axial movement of deformation point and Vref depending on the type of deformation that are the deformation1 is to increase the Vref (relaxation) and the deformation 2 is to decrease the Vref (contraction) .The deformed image (Idef) and volume (Vdef) were inversely deformed to Iref and Vref using DIR algorithms. As a Result, we acquired deformed image (Iid) and volume (Vid). The DIR algorithms were optical flow (HS, IOF) and demons (MD, FD) of the DIRART. The image similarity evaluation between Iref and Iid was calculated by Normalized Mutual Information (NMI) and Normalized Cross Correlation (NCC). The value of Dice Similarity Coefficient (DSC) was used for evaluation of volume similarity. Results: When moving distance of deformation point was 4 mm, the value of NMI was above 1.81 and NCC was above 0.99 in all DIR algorithms. Since the degree of deformation was increased, the degree of image similarity was decreased. When the Vref increased or decreased about 12%, the difference between Vref and Vid was within ±5% regardless of the type of deformation. The value of DSC was above 0.95 in deformation1 except for the MD algorithm. In case of deformation 2, that of DSC was above 0.95 in all DIR algorithms. Conclusion: The Idef and Vdef have not been completely restored to Iref and Vref and the accuracy of DIR algorithms was different depending on the degree of deformation. Hence, the performance of DIR algorithms should be verified for the desired applications.

60 APPLIED LIFE SCIENCES↗

MO-FG-CAMPUS-TeP1-03: Pre-Treatment Surface Imaging Based Collision Detection

Purpose: Modern radiotherapy increasingly employs large immobilization devices, gantry attachments, and couch rotations for treatments. All of which raise the risk of collisions between the patient and the gantry / couch. Collision detection is often achieved by manually checking each couch position in the treatment room and sometimes results in extraneous imaging if collisions are detected after image based setup has begun. In the interest of improving efficiency and avoiding extra imaging, we explore the use of a surface imaging based collision detection model. Methods: Surfaces acquired from AlignRT (VisionRT, London, UK) were transferred in wavefront format to a custom Matlab (Mathworks, Natick, MA) software package (CCHECK). Computed tomography (CT) scans acquired at the same time were sent to CCHECK in DICOM format. In CCHECK, binary maps of the surfaces were created and overlaid on the CT images based on the fixed relationship of the AlignRT and CT coordinate systems. Isocenters were added through a graphical user interface (GUI). CCHECK then compares the inputted surfaces to a model of the linear accelerator (linac) to check for collisions at defined gantry and couch positions. Note, CCHECK may be used with or without a CT. Results: The nominal surface image field of view is 650 mm × 900 mm, with variance based on patient position and size. The accuracy of collision detections is primarily based on the linac model and the surface mapping process. The current linac model and mapping process yield detection accuracies on the order of 5 mm, assuming no change in patient posture between surface acquisition and treatment. Conclusions: CCHECK provides a non-ionizing method to check for collisions without the patient in the treatment room. Collision detection accuracy may be improved with more robust linac modeling. Additional gantry attachments (e.g. conical collimators) can be easily added to the model.

60 APPLIED LIFE SCIENCES↗

SU-D-BRD-01: An Automated Physics Weekly Chart Checking System Supporting ARIA

Purpose: A software tool was developed in this study to perform automatic weekly physics chart check on the patient data in ARIA. The tool accesses the electronic patient data directly from ARIA server and checks the accuracy of treatment deliveries, and generates reports which summarize the delivery history and highlight the errors. Methods: The tool has four modules. 1) The database interface is designed to directly access treatment delivery data from the ARIA database before reorganizing the data into the patient chart tree (PCT). 2) PCT is a core data structure designed to store and organize the data in logical hierarchies, and to be passed among functions. 3) The treatment data check module analyzes the organized data in PCT and stores the checking results into PCT. 4) Report generation module generates reports containing the treatment delivery summary, chart checking results and plots of daily treatment setup parameters (couch table positions, shifts of image guidance). The errors that are found by the tool are highlighted with colors. Results: The weekly check tool has been implemented in MATLAB and clinically tested at two major cancer centers. Javascript, cascading style sheets (CSS) and dynamic HTML were employed to create the user-interactive reports. It takes 0.06 second to search the delivery records of one beam with PCT and compare the delivery records with beam plan. The reports, saved in the HTML files on shared network folder, can be accessed by web browser on computers and mobile devices. Conclusion: The presented weekly check tool is useful to check the electronic patient treatment data in Varian ARIA system. It could be more efficient and reliable than the manually check by physicists. The work was partially supported by a research grant from Varian Medical System.

60 APPLIED LIFE SCIENCES↗

THE Arp 220 MERGER ON kpc SCALES

For the first time, we study the eastern nucleus in greater detail and search for the more extended emission in the molecular gas in different CO line transitions of the famous ultraluminous infrared galaxy (ULIRG) Arp 220. Furthermore, we present a model of the merger in Arp 220 on large scales with the help of the CO data and an optical and near-infrared composite Hubble Space Telescope image of the prototypical ULIRG. Using the Plateau de Bure interferometer (PdBI), we obtained CO (2-1) and (1-0) data at wavelengths of 1 and 3 mm in 1994, 1996, 1997, and 2006 at different beam sizes and spatial resolutions. The simulations of the merger in Arp 220 were performed with the Identikit modeling tool. The model parameters that describe the galaxy merger best give a mass ratio of 1:2 and result in a merger of {approx}6 Multiplication-Sign 10{sup 8} yr. The low-resolution CO (1-0) PdBI observations suggest that there are indications for emission {approx}10'' toward the south, as well as to the north and to the west of the two nuclei.

79 ASTRONOMY AND ASTROPHYSICS↗

Technical Note: PLASTIMATCH MABS, an open source tool for automatic image segmentation

Purpose: Multiatlas based segmentation is largely used in many clinical and research applications. Due to its good performances, it has recently been included in some commercial platforms for radiotherapy planning and surgery guidance. Anyway, to date, a software with no restrictions about the anatomical district and image modality is still missing. In this paper we introduce PLASTIMATCH MABS, an open source software that can be used with any image modality for automatic segmentation. Methods: PLASTIMATCH MABS workflow consists of two main parts: (1) an offline phase, where optimal registration and voting parameters are tuned and (2) an online phase, where a new patient is labeled from scratch by using the same parameters as identified in the former phase. Several registration strategies, as well as different voting criteria can be selected. A flexible atlas selection scheme is also available. To prove the effectiveness of the proposed software across anatomical districts and image modalities, it was tested on two very different scenarios: head and neck (H&N) CT segmentation for radiotherapy application, and magnetic resonance image brain labeling for neuroscience investigation. Results: For the neurological study, minimum dice was equal to 0.76 (investigated structures: left and right caudate, putamen, thalamus, and hippocampus). For head and neck case, minimum dice was 0.42 for the most challenging structures (optic nerves and submandibular glands) and 0.62 for the other ones (mandible, brainstem, and parotid glands). Time required to obtain the labels was compatible with a real clinical workflow (35 and 120 min). Conclusions: The proposed software fills a gap in the multiatlas based segmentation field, since all currently available tools (both for commercial and for research purposes) are restricted to a well specified application. Furthermore, it can be adopted as a platform for exploring MABS parameters and as a reference implementation for comparing against other segmentation algorithms.

60 APPLIED LIFE SCIENCES↗