Sparse arrays and image compounding techniques for non-destructive testing using guided acoustic waves

Piezoelectric array transducers applications are becoming usual in the ultrasonic non-destructive testing area. However, the number of elements can increase the system complexity, due to the necessity of multichannel circuitry and to the large amount of data to be processed. Synthetic aperture techniques, where one or few transmission and reception channels are necessary, and the data are post-processed, can be used to reduce the system complexity. Another possibility is to use sparse arrays instead of a full-populated array. In sparse arrays, there is a smaller number of elements and the interelement spacing is larger than half wavelength. In this work, results of ultrasonic inspection of an aluminum plate with artificial defects using guided acoustic waves and sparse arrays are presented. Synthetic aperture techniques are used to obtain a set of images that are then processed with an image compounding technique, which was previously evaluated only with full-populated arrays, in order to increase the resolution and contrast of the images. The results with sparse arrays are equivalent to the ones obtained with full-populated arrays in terms of resolution. Although there is an 8 dB contrast reduction when using sparse arrays, defect detection is preserved and there is the advantage of a reduction in the number of transducer elements and data volume. © 2013 Brazilian Society for Automatics - SBA.

Development of automated image analysis tools for verification of radiotherapy field accuracy with an electronic portal imaging device

The successful management of cancer with radiation relies on the accurate deposition of a prescribed dose to a prescribed anatomical volume within the patient. Treatment set-up errors are inevitable because the alignment of field shaping devices with the patient must be repeated daily up to eighty times during the course of a fractionated radiotherapy treatment. With the invention of electronic portal imaging devices (EPIDs), patient's portal images can be visualized daily in real-time after only a small fraction of the radiation dose has been delivered to each treatment field. However, the accuracy of human visual evaluation of low-contrast portal images has been found to be inadequate. The goal of this research is to develop automated image analysis tools to detect both treatment field shape errors and patient anatomy placement errors with an EPID. A moments method has been developed to align treatment field images to compensate for lack of repositioning precision of the image detector. A figure of merit has also been established to verify the shape and rotation of the treatment fields. Following proper alignment of treatment field boundaries, a cross-correlation method has been developed to detect shifts of the patient's anatomy relative to the treatment field boundary. Phantom studies showed that the moments method aligned the radiation fields to within 0.5mm of translation and 0.5$\sp\circ$ of rotation and that the cross-correlation method aligned anatomical structures inside the radiation field to within 1 mm of translation and 1$\sp\circ$ of rotation. A new procedure of generating and using digitally reconstructed radiographs (DRRs) at megavoltage energies as reference images was also investigated. The procedure allowed a direct comparison between a designed treatment portal and the actual patient setup positions detected by an EPID. Phantom studies confirmed the feasibility of the methodology. Both the moments method and the cross-correlation technique were implemented within an experimental radiotherapy picture archival and communication system (RT-PACS) and were used clinically to evaluate the setup variability of two groups of cancer patients treated with and without an alpha-cradle immobilization aid. The tools developed in this project have proven to be very effective and have played an important role in detecting patient alignment errors and field-shape errors in treatment fields formed by a multileaf collimator (MLC). ^

The Feasibly of Functionally Guided Intensity Modulated Radiation Therapy Treatment Planning Using Perfluoropropane-Enhanced MRI for Lung Cancer

Radiotherapy is commonly used to treat lung cancer. However, radiation induced damage to lung tissue is a major limiting factor to its use. To minimize normal tissue lung toxicity from conformal radiotherapy treatment planning, we investigated the use of Perfluoropropane(PFP)-enhanced MR imaging to assess and guide the sparing of functioning lung. Fluorine Enhanced MRI using Perfluoropropane(PFP) is a dynamic multi-breath steady state technique enabling quantitative and qualitative assessments of lung function(1).

Imaging data was obtained from studies previously acquired in the Duke Image Analysis Laboratory. All studies were approved by the Duke IRB. The data was de-identified for this project, which was also approved by the Duke IRB. Subjects performed several breath-holds at total lung capacity(TLC) interspersed with multiple tidal breaths(TB) of Perfluoropropane(PFP)/oxygen mixture. Additive wash-in intensity images were created through the summation of the wash-in phase breath-holds. Additionally, model based fitting was utilized to create parametric images of lung function(1).

Varian Eclipse treatment planning software was used for putative treatment planning. For each subject two plans were made, a standard plan, with no regional functional lung information considered other than current standard models. Another was created using functional information to spare functional lung while maintaining dose to the target lesion. Plans were optimized to a prescription dose of 60 Gy to the target over the course of 30 fractions.

A decrease in dose to functioning lung was observed when utilizing this functional information compared to the standard plan for all five subjects. PFP-enhanced MR imaging is a feasible method to assess ventilatory lung function and we have shown how this can be incorporated into treatment planning to potentially decrease the dose to normal tissue.

CT Image Electron Density Quantification in Regions with Metal Implants: Implications for Radiotherapy Treatment Planning

In radiotherapy planning, computed tomography (CT) images are used to quantify the electron density of tissues and provide spatial anatomical information. Treatment planning systems use these data to calculate the expected spatial distribution of absorbed dose in a patient. CT imaging is complicated by the presence of metal implants which cause increased image noise, produce artifacts throughout the image and can exceed the available range of CT number values within the implant, perturbing electron density estimates in the image. Furthermore, current dose calculation algorithms do not accurately model radiation transport at metal-tissue interfaces. Combined, these issues adversely affect the accuracy of dose calculations in the vicinity of metal implants. As the number of patients with orthopedic and dental implants grows, so does the need to deliver safe and effective radiotherapy treatments in the presence of implants. The Medical Physics group at the Cancer Centre of Southeastern Ontario and Queen's University has developed a Cobalt-60 CT system that is relatively insensitive to metal artifacts due to the high energy, nearly monoenergetic Cobalt-60 photon beam. Kilovoltage CT (kVCT) images, including images corrected using a commercial metal artifact reduction tool, were compared to Cobalt-60 CT images throughout the treatment planning process, from initial imaging through to dose calculation. An effective metal artifact reduction algorithm was also implemented for the Cobalt-60 CT system. Electron density maps derived from the same kVCT and Cobalt-60 CT images indicated the impact of image artifacts on estimates of photon attenuation for treatment planning applications. Measurements showed that truncation of CT number data in kVCT images produced significant mischaracterization of the electron density of metals. Dose measurements downstream of metal inserts in a water phantom were compared to dose data calculated using CT images from kVCT and Cobalt-60 systems with and without artifact correction. The superior accuracy of electron density data derived from Cobalt-60 images compared to kVCT images produced calculated dose with far better agreement with measured results. These results indicated that dose calculation errors from metal image artifacts are primarily due to misrepresentation of electron density within metals rather than artifacts surrounding the implants.

Exploring domain-informed and physics-guided learning in image-to-image translation

Image-to-image (i2i) translation networks can generate fake images beneficial for many applications in augmented reality, computer graphics, and robotics. However, they require large scale datasets and high contextual understanding to be trained correctly. In this thesis, we propose strategies for solving these problems, improving performances of i2i translation networks by using domain- or physics-related priors. The thesis is divided into two parts. In Part I, we exploit human abstraction capabilities to identify existing relationships in images, thus defining domains that can be leveraged to improve data usage efficiency. We use additional domain-related information to train networks on web-crawled data, hallucinate scenarios unseen during training, and perform few-shot learning. In Part II, we instead rely on physics priors. First, we combine realistic physics-based rendering with generative networks to boost outputs realism and controllability. Then, we exploit naive physical guidance to drive a manifold reorganization, which allowed generating continuous conditions such as timelapses.

CT arthrography of the glenohumeral joint: CT fluoroscopy versus conventional CT and fluoroscopy--comparison of image-guidance techniques.

PURPOSE: To compare examination time with radiologist time and to measure radiation dose of computed tomographic (CT) fluoroscopy, conventional CT, and conventional fluoroscopy as guiding modalities for shoulder CT arthrography. MATERIALS AND METHODS: Glenohumeral injection of contrast material for CT arthrography was performed in 64 consecutive patients (mean age, 32 years; age range, 16-74 years) and was guided with CT fluoroscopy (n = 28), conventional CT (n = 14), or conventional fluoroscopy (n = 22). Room times (arthrography, room change, CT, and total examination times) and radiologist times (time the radiologist spent in the fluoroscopy or CT room) were measured. One-way analysis of variance and Bonferroni-Dunn posthoc tests were performed for comparison of mean times. Mean effective radiation dose was calculated for each method with examination data, phantom measurements, and standard software. RESULTS: Mean total examination time was 28.0 minutes for CT fluoroscopy, 28.6 minutes for conventional CT, and 29.4 minutes for conventional fluoroscopy; mean radiologist time was 9.9 minutes, 10.5 minutes, and 9.0 minutes, respectively. These differences were not statistically significant. Mean effective radiation dose was 0.0015 mSv for conventional fluoroscopy (mean, nine sections), 0.22 mSv for CT fluoroscopy (120 kV; 50 mA; mean, 15 sections), and 0.96 mSv for conventional CT (140 kV; 240 mA; mean, six sections). Effective radiation dose can be reduced to 0.18 mSv for conventional CT by changing imaging parameters to 120 kV and 100 mA. Mean effective radiation dose of the diagnostic CT arthrographic examination (140 kV; 240 mA; mean, 25 sections) was 2.4 mSv. CONCLUSION: CT fluoroscopy and conventional CT are valuable alternative modalities for glenohumeral CT arthrography, as examination and radiologist times are not significantly different. CT guidance requires a greater radiation dose than does conventional fluoroscopy, but with adequate parameters CT guidance constitutes approximately 8% of the radiation dose.

Model-based Segmentation and Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

Computed Tomography (CT) represents the standard imaging modality for tumor volume delineation for radiotherapy treatment planning of retinoblastoma despite some inherent limitations. CT scan is very useful in providing information on physical density for dose calculation and morphological volumetric information but presents a low sensitivity in assessing the tumor viability. On the other hand, 3D ultrasound (US) allows a highly accurate definition of the tumor volume thanks to its high spatial resolution but it is not currently integrated in the treatment planning but used only for diagnosis and follow-up. Our ultimate goal is an automatic segmentation of gross tumor volume (GTV) in the 3D US, the segmentation of the organs at risk (OAR) in the CT and the registration of both modalities. In this paper, we present some preliminary results in this direction. We present 3D active contour-based segmentation of the eye ball and the lens in CT images; the presented approach incorporates the prior knowledge of the anatomy by using a 3D geometrical eye model. The automated segmentation results are validated by comparing with manual segmentations. Then, we present two approaches for the fusion of 3D CT and US images: (i) landmark-based transformation, and (ii) object-based transformation that makes use of eye ball contour information on CT and US images.

The role of the radiotherapy technologist in gamma knife radiosurgery within a multidisciplinary team: the Lausanne experience

Objective: Integration of the radiotherapy technologist "know-how" in the Gamma Knife treatment processMaterials and Methods: Gamma Knife (GK) treatments started in July 2010 at the GK Center in C.H.U.V. with the Leksell Gamma KnifeR Perfexion?(Elekta AB, Sweden). The multidisciplinary GK team involves neurosurgeons, radio-oncologists, physicists, neuroradiologists, nurses and technologists, aiming at a full integration for optimal patient management.Results: Between July and December 2010, 60 patients have been treated. Required stereotactic imaging involves IRM, CT scan (and angiography for AVM). All the steps in the treatment process (Leksell coordinate frame fixation, imaging, planning, treatment) are supervised by the members of the multidisciplinary team. In our experience, radiotherapy technologist (RTT) have acquired an important role in the multidisciplinary team communication and integration. Specifically, the RTT are responsible of: supervision of the image acquisition, performing the Gamma Knife unit control tests, patient setup, and patient surveillance during treatment.Conclusion: RTT have a fundamental role in the communication within the team, between the team and the patient and also to assure the patient security. Our experience shows that it is possible and required to involve RTT in all steps of the GK treatment process, to guarantee the best GK treatment possible.

Segmentation of Head and Neck Lymph Node Regions for Radiotherapy Planning Using Active Contour-Based Atlas Registration

In this paper, we present the segmentation of the headand neck lymph node regions using a new active contourbased atlas registration model. We propose to segment thelymph node regions without directly including them in theatlas registration process; instead, they are segmentedusing the dense deformation field computed from theregistration of the atlas structures with distinctboundaries. This approach results in robust and accuratesegmentation of the lymph node regions even in thepresence of significant anatomical variations between theatlas-image and the patient's image to be segmented. Wealso present a quantitative evaluation of lymph noderegions segmentation using various statistical as well asgeometrical metrics: sensitivity, specificity, dicesimilarity coefficient and Hausdorff distance. Acomparison of the proposed method with two other state ofthe art methods is presented. The robustness of theproposed method to the atlas selection, in segmenting thelymph node regions, is also evaluated.

A concurrent region growing algorithm guided by circumscribed contours

Image segmentation of natural scenes constitutes a major problem in machine vision. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. This approach begins by detecting the main contours of the scene which are later used to guide a concurrent set of growing processes. A previous analysis of the seed pixels permits adjustment of the homogeneity criterion to the region's characteristics during the growing process. Since the high variability of regions representing outdoor scenes makes the classical homogeneity criteria useless, a new homogeneity criterion based on clustering analysis and convex hull construction is proposed. Experimental results have proven the reliability of the proposed approach

ESTRO-HERO survey: Radiotherapy equipment and departments in the European countries: Final results from the ESTRO-HERO survey

Background: Documenting the distribution of radiotherapy departments and the availability of radiotherapy equipment in the European countries is an important part of HERO the ESTRO Health Economics in Radiation Oncology project. HERO has the overall aim to develop a knowledge base of the provision of radiotherapy in Europe and build a model for health economic evaluation of radiation treatments at the European level. The aim of the current report is to describe the distribution of radiotherapy equipment in European countries. Methods: An 84-item questionnaire was sent out to European countries, principally through their national societies. The current report includes a detailed analysis of radiotherapy departments and equipment (questionnaire items 2629), analyzed in relation to the annual number of treatment courses and the socio-economic status of the countries. The analysis is based on validated responses from 28 of the 40 European countries defined by the European Cancer Observatory (ECO). Results: A large variation between countries was found for most parameters studied. There were 2192 linear accelerators, 96 dedicated stereotactic machines, and 77 cobalt machines reported in the 27 countries where this information was available. A total of 12 countries had at least one cobalt machine in use. There was a median of 0.5 simulator per MV unit (range 0.31.5) and 1.4 (range 0.44.4) simulators per department. Of the 874 simulators, a total of 654 (75%) were capable of 3D imaging (CT-scanner or CBCToption). The number of MV machines (cobalt, linear accelerators, and dedicated stereotactic machines) per million inhabitants ranged from 1.4 to 9.5 (median 5.3) and the average number of MV machines per department from 0.9 to 8.2 (median 2.6). The average number of treatment courses per year per MV machine varied from 262 to 1061 (median 419). While 69% of MV units were capable of IMRT only 49% were equipped for image guidance (IGRT). There was a clear relation between socio-economic status, as measured by GNI per capita, and availability of radiotherapy equipment in the countries. In many low income countries in Southern and Central-Eastern Europe there was very limited access to radiotherapy and especially to equipment for IMRT or IGRT. Conclusions: The European average number of MV machines per million inhabitants and per department is now better in line with QUARTS recommendations from 2005, but the survey also showed a significant heterogeneity in the access to modern radiotherapy equipment in Europe. High income countries especially in Northern-Western Europe are well-served with radiotherapy resources, other countries are facing important shortages of both equipment in general and especially machines capable of delivering high precision conformal treatments (IMRT, IGRT)

A concurrent region growing algorithm guided by circumscribed contours

Image segmentation of natural scenes constitutes a major problem in machine vision. This paper presents a new proposal for the image segmentation problem which has been based on the integration of edge and region information. This approach begins by detecting the main contours of the scene which are later used to guide a concurrent set of growing processes. A previous analysis of the seed pixels permits adjustment of the homogeneity criterion to the region's characteristics during the growing process. Since the high variability of regions representing outdoor scenes makes the classical homogeneity criteria useless, a new homogeneity criterion based on clustering analysis and convex hull construction is proposed. Experimental results have proven the reliability of the proposed approach

Image segmentation integrating colour, texture and boundary information

La tesis se centra en la Visión por Computador y, más concretamente, en la segmentación de imágenes, la cual es una de las etapas básicas en el análisis de imágenes y consiste en la división de la imagen en un conjunto de regiones visualmente distintas y uniformes considerando su intensidad, color o textura. Se propone una estrategia basada en el uso complementario de la información de región y de frontera durante el proceso de segmentación, integración que permite paliar algunos de los problemas básicos de la segmentación tradicional. La información de frontera permite inicialmente identificar el número de regiones presentes en la imagen y colocar en el interior de cada una de ellas una semilla, con el objetivo de modelar estadísticamente las características de las regiones y definir de esta forma la información de región. Esta información, conjuntamente con la información de frontera, es utilizada en la definición de una función de energía que expresa las propiedades requeridas a la segmentación deseada: uniformidad en el interior de las regiones y contraste con las regiones vecinas en los límites. Un conjunto de regiones activas inician entonces su crecimiento, compitiendo por los píxeles de la imagen, con el objetivo de optimizar la función de energía o, en otras palabras, encontrar la segmentación que mejor se adecua a los requerimientos exprsados en dicha función. Finalmente, todo esta proceso ha sido considerado en una estructura piramidal, lo que nos permite refinar progresivamente el resultado de la segmentación y mejorar su coste computacional. La estrategia ha sido extendida al problema de segmentación de texturas, lo que implica algunas consideraciones básicas como el modelaje de las regiones a partir de un conjunto de características de textura y la extracción de la información de frontera cuando la textura es presente en la imagen. Finalmente, se ha llevado a cabo la extensión a la segmentación de imágenes teniendo en cuenta las propiedades de color y textura. En este sentido, el uso conjunto de técnicas no-paramétricas de estimación de la función de densidad para la descripción del color, y de características textuales basadas en la matriz de co-ocurrencia, ha sido propuesto para modelar adecuadamente y de forma completa las regiones de la imagen. La propuesta ha sido evaluada de forma objetiva y comparada con distintas técnicas de integración utilizando imágenes sintéticas. Además, se han incluido experimentos con imágenes reales con resultados muy positivos.

Acellular dermal matrix as a barrier in guided bone regeneration: a clinical, radiographic and histomorphometric study in dogs

Objectives The purpose of this study was to evaluate the effectiveness of the acellular dermal matrix (ADM) as a membrane for guided bone regeneration (GBR), in comparison with a bioabsorbable membrane. Material and methods In seven dogs, the mandibular pre-molars were extracted. After 8 weeks, one bone defect was surgically created bilaterally and the GBR was performed. Each side was randomly assigned to the control group (CG: bioabsorbable membrane made of glycolide and lactide copolymer) or the test group (TG: ADM as a membrane). Immediately following GBR, standardized digital X-ray radiographs were taken, and were repeated at 8 and 16 weeks post-operatively. Before the GBR and euthanasia, clinical measurements of the width and thickness of the keratinized tissue (WKT and TKT, respectively) were performed. One animal was excluded from the study due to complications in the TG during wound healing; therefore, six dogs remained in the sample. The dogs were sacrificed 16 weeks following GBR, and a histomorphometric analysis was performed. Area measurements of new tissue and new bone, and linear measurements of bone height were performed. Results Post-operative healing of the CG was uneventful. In the TG membrane was exposed in two animals, and one of them was excluded from the sample. There were no statistically significant differences between the groups for any histomorphometric measurement. Clinically, both groups showed an increase in the TKT and a reduction in the WKT. Radiographically, an image suggestive of new bone formation could be observed in both groups at 8 and 16 weeks following GBR. Conclusion ADM acted as a barrier in GBR, with clinical, radiographic and histomorphometric results similar to those obtained with the bioabsorbable membrane. To cite this article:Borges GJ, Novaes AB Jr, de Moraes Grisi MF, Palioto DB, Taba M Jr, de Souza SLS. Acellular dermal matrix as a barrier in guided bone regeneration: a clinical, radiographic and histomorphometric study in dogs.Clin. Oral Impl. Res. 20, 2009; 1105-1115.

Technique to combine images produced by different propagation modes of guided waves for damage detection and contrast improvement in plate-like structures

This paper describes an image compounding technique based on the use of different apodization functions, the evaluation of the signals phases and information from the interaction of different propagation modes of Lamb waves with defects for enhanced damage detection, resolution and contrast. A 16 elements linear array is attached to a 1 mm thickness isotropic aluminum plate with artificial defects. The array can excite the fundamental A0 and S0 modes at the frequencies of 100 kHz and 360 kHz, respectively. For each mode two synthetic aperture (SA) images with uniform and Blackman apodization and one image of Coherence Factor Map (CFM) are obtained. The specific interaction between each propagation mode and the defects and the characteristics of acoustic radiation patterns due to different apodization functions result in images with different resolution and contrast. From the phase information one of the SA images is selected at each pixel to compound the final image. The SA images are multiplied by the CFM image to improve contrast and for the dispersive A0 mode it is used a technique for dispersion compensation. There is a contrast improvement of 47.5 dB, reducing the dead zone and improving resolution and damage detection. © 2012 IEEE.