Thesis (Ph.D)--Electrical and Computer Engineering, Georgia Institute of Technology, 2009. / Committee Chair: Oskar krinjar; Committee Member: Allen Tannenbaum; Committee Member: Anthony Yezzi; Committee Member: John Oshinski; Committee Member: Patricio Vela. Part of the SMARTech Electronic Thesis and Dissertation Collection.

Thesis (Ph.D.)--University of Alberta, 2010. / A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Medical Physics, Department of Physics. Title from pdf file main screen (viewed on June 26, 2010). Includes bibliographical references.

Thesis (M.S.)--Mississippi State University. Department of Electrical and Computer Engineering. / Title from title screen. Includes bibliographical references.

This thesis belongs to the research line of Biomedical Imaging Tecnologies and proposes as main objective to develop and research spatio-temporal non-rigid registration methods to estimate and compesate motion in cardiac magnetic resonance sequences and to validate and verify the suitability of those techniques in the clinical environment. / -

Η ψηφιακή απεικόνιση είναι ένας ραγδαία αναπτυσσόμενος κλάδος στην εξέλιξη της τεχνολογίας των υπολογιστών και έχει γίνει ένα συμβατικό εργαλείο στην χαρτογράφηση της τηλεπισκόπησης. Η ανάγκη για καλύτερη ποιότητα απεικόνισης ενισχύει τον ψηφιακό τομέα να παράγει μεθόδους για την αποκατάσταση της γεωμετρικής παραμόρφωσης. Παρά το προχωρημένο επίπεδο της σημερινής τεχνολογίας, είναι γνωστό ότι οι συσκευές εισόδου και εξόδου, σαρωτές οι οποίοι είναι περιφερειακές συσκευές που αποτυπώνουν την εικόνα μιας περιοχής και χρησιμοποιούνται ως επί το πλείστον ως συσκευές εισόδου, προκαλούν παραμορφώσεις στη εικόνα. Στην παρούσα εργασία, γίνεται μια προσπάθεια να αντιμετωπισθούν λάθη στη γεωμετρία με χρήση του προγράμματος Matlab και της μεθόδου της αντιστοίχησης εικόνας. Η αντιστοίχηση εικόνας αποσκοπεί στην εύρεση αντίστοιχων σημείων σε δύο ή περισσότερες εικόνες, τα οποία αποτελούν προβολές του ίδιου σημείου της σκηνής. Η διαδικασία δειγματοληψίας των ψηφιακών εικόνων, το μοντέλο προβολής της σκηνής μέσω αισθητήρα όρασης στο επίπεδο των εικόνων και η κίνηση του αισθητήρα ή και της σκηνής, αποτελούν τους κύριους παράγοντες που καθιστούν το πρόβλημα της αντιστοίχησης αρκετά δύσκολο. Την πλειοψηφία των αλγορίθμων αντιστοίχησης εικόνας συνθέτουν οι παραμετρικές τεχνικές, σύμφωνα με τις οποίες υιοθετείται ένα παραμετρικό μοντέλο, το οποίο εφαρμοζόμενο στη μία εικόνα δύναται να παρέχει μια προσέγγιση της άλλης. Η προσέγγιση αυτή αξιολογείται μέσω ενός δείκτη συνολικού σφάλματος, ενώ η βέλτιστη δυνατή προσέγγιση επιτυγχάνεται με την εκτίμηση των τιμών των παραμέτρων του μοντέλου που βελτιστοποιούν τον δείκτη αυτό. Το βασικό σημείο του προτεινόμενου μοντέλου είναι η εφαρμογή πολυωνυμικών σχέσεων και η σωστή επιλογή του πολυωνυμικού γεωμετρικού μετασχηματισμού, λαμβάνοντας υπόψη τα χαρακτηριστικά της εκάστοτε παραμόρφωσης, για την αντιμετώπιση του προβλήματος. Λειτουργίες μετασχηματισμών χρησιμοποιούνται για να περιγράψουν τις γεωμετρικές διαφορές μεταξύ δύο εικόνων που έχουν το ίδιο περιεχόμενο. Λαμβάνοντας υπόψη τις συντεταγμένες ενός σημείου σε μια εικόνα ένας μετασχηματισμός θα καθορίσει τις συντεταγμένες του ίδιου σημείου στην άλλη εικόνα. Θα καλούμε μία από τις εικόνες δευτερεύουσα και την άλλη κύρια. Η κύρια εικόνα παραμένει αμετάβλητη ενώ η δευτερεύουσα παραμορφώνεται ώστε να έχει την γεωμετρία της κύριας εικόνας. Οι λειτουργίες των μετασχηματισμών για την αντιστοίχηση εικόνας καθορίζεται βάσει ενός αριθμού αντίστοιχων συντεταγμένων στις δύο εικόνες και επιλέγεται χειροκίνητα. Στην αντιστοίχηση εικόνας δίνονται και η κύρια και η δευτερεύουσα εικόνα με την δευτερεύουσα να παραμορφώνεται ώστε να αντιστοιχηθεί με την κύρια. / Digital imaging is a rapidly growing sector in the development of computer technology and has become a conventional tool in remote sensing mapping. The need for better image quality enhances the digital sector to produce methods for restoring the geometric distortion. Despite the advanced level of today’s technology, it is known that input and output devices, scanners that are peripheral devices that capture the image of a region, and are used mostly as an input device, cause distortions in the image. In this paper, by using the Matlab program and the method of image registration we try to deal with errors in geometry. Image registration aims to find corresponding points in two or more images which are projections of the same point of a scene. The resampling process of digital images, the projection model of the scene through vision sensor at the level of images and the motion of the sensor or scene’s , are the main factors of image mapping. The majority of algorithms of image registration compose the parametric techniques that adopt a parametric model which is applied to an image and can provide an approximation of another image. This approach is evaluated through a total error rate, while the optimal approximation is achieved by the evaluation of the values of the model parameters that optimize this indicator. The key point of the proposed model is the application of polynomial equations and the proper selection of polynomial geometric transformation. Transformation functions are used to describe geometric differences between two images that have the same or overlapping contents. Given the coordinates of a point in one image, a transformation function will determine the coordinates of the same point in the other image. We will call one of the images the slave and the other image the master. Master image is kept unchanged. Slave image needs to be deformed to have the geometry of the master image. The transformation functions for image registration are determined using the coordinates of a number of corresponding points in the images, selected manually. In image registration, both master and slave images are given, and the slave image is deformed to overlay the master image.

<p>Quality assurance (QA) is a critical component of radiation oncology medical physics for both effective treatment and patient safety, particularly as innovations in technology allow movement toward advanced treatment techniques that require increasingly higher accuracy in delivery. Comprehensive 3D dosimetry with PRESAGE® 3D dosimeters read out via optical CT has the potential to detect errors that would be missed by current systems of measurement, and thereby improve the rigor of current QA techniques through providing high-resolution, full 3D verification for a wide range of clinical applications. The broad objective of this dissertation research is to advance and strengthen the standards of QA for radiation therapy, both by driving the development and optimization of PRESAGE® 3D dosimeters for specific clinical and research applications and by applying the technique of high resolution 3D dosimetry toward addressing clinical needs in the current practice of radiation therapy. The specific applications that this dissertation focuses on address several topical concerns: (1) increasing the quality, consistency, and rigor of radiation therapy delivery through comprehensive 3D verification in remote credentialing evaluations, (2) investigating a reusable 3D dosimeter that could potentially facilitate wider implementation of 3D dosimetry through improving cost-effectiveness, and (3) validating deformable image registration (DIR) algorithms prior to clinical implementation in dose deformation and accumulation calculations.</p><p>3D Remote Dosimetry: The feasibility of remote high-resolution 3D dosimetry with the PRESAGE®/Optical-CT system was investigated using two nominally identical optical-CT scanners for 3D dosimetry were constructed and placed at the base (Duke University) and remote (IROC Houston) institutions. Two formulations of PRESAGE® (SS1, SS2) were investigated with four unirradiated PRESAGE® dosimeters imaged at the base institution, then shipped to the remote institution for planning and irradiation. After each dosimeter was irradiated with the same treatment plan and subsequently read out by optical CT at the remote institution, the dosimeters were shipped back to the base institution for remote dosimetry readout 3 days post-irradiation. Measured on-site and remote relative 3D dose distributions were registered to the Pinnacle dose calculation, which served as the reference distribution for 3D gamma calculations with passing criteria of 5%/2mm, 3%/3mm, and 3%/2mm with a 10% dose threshold. Gamma passing rates, dose profiles, and dose maps were used to assess and compare the performance of both PRESAGE® formulations for remote dosimetry. Both PRESAGE® formulations under study maintained high linearity of dose response (R2>0.996) over 14 days with response slope consistency within 4.9% (SS1) and 6.6% (SS2). Better agreements between the Pinnacle plan and dosimeter readout were observed in PRESAGE® formulation SS2, which had higher passing rates and consistency between immediate and remote results at all metrics. This formulation also demonstrated a relative dose distribution that remained stable over time. These results provide a foundation for future investigations using remote dosimetry to study the accuracy of advanced radiation treatments.</p><p>A Reusable 3D Dosimeter: New Presage-RU formulations made using a lower durometer polyurethane matrix (Shore hardness 30-50A) exhibit a response that optically clears following irradiation and opens up the potential for reirradiation and dosimeter reusability. This would have the practical benefit of improving cost-effectiveness and thereby facilitating the wider implementation of comprehensive, high resolution 3D dosimetry. Three formulations (RU-3050-1.7, RU-3050-1.5, and RU-50-1.5) were assessed with multiple irradiations of both small volume samples and larger volume dosimeters, then characterized and evaluated for dose response sensitivity, optical clearing, dose-rate independence, dosimetric accuracy, and the effects of reirradiation on dose measurement. The primary shortcoming of these dosimeters was the discovery of age-dependent gradients in dose response sensitivity, which varied dose response by as much as 30% and prevented accurate measurement. This is unprecedented in the standard formulations and presumably caused by diffusion of a desensitizing agent into the lower durometer polyurethane. The effect of prior irradiation on the dosimeters would also be a concern as it was seen that the relative amount of dose delivered to any given region of the dosimeter will affect subsequent sensitivity in that area, which would in effect create spatially-dependent variable dose sensitivities throughout the dosimeter based on the distributions of prior irradiations. While a successful reusable dosimeter may not have been realized from this work, these studies nonetheless contributed useful information that will affect future development, including in the area of deformable dosimetry, and provide a framework for future reusable dosimeter testing.</p><p>Validating Deformable Image Registration Algorithms: Deformable image registration (DIR) algorithms are used for multi-fraction dose accumulation and treatment response assessment for adaptive radiation therapy, but the accuracy of these methods must be investigated prior to clinical implementation. 12 novel deformable PRESAGE® 3D dosimeter formulations were introduced and characterized for potential use in validating DIR algorithms by providing accurate, ground-truth deformed dose measurement for comparison to DIR-predicted deformed dose distributions. Two commercial clinical DIR software algorithms were evaluated for dose deformation accuracy by comparison against a measured deformed dosimeter dose distribution. This measured distribution was obtained by irradiating a dosimeter under lateral compression, then releasing it from compression so that it could return to its original geometry. The dose distribution within the dosimeter deformed along with the dosimeter volume as it regained to its original shape, thus providing a measurable ground truth deformed dose distribution. Results showed that intensity-based DIR algorithms produce high levels of error and physically unrealistic deformations when deforming a homogeneous structure; this is expected as lack of internal structure is challenging for intensity-based DIR algorithms to deform accurately as they rely on matching fairly closely spaced heterogeneous intensity features. A biomechanical, intensity-independent DIR algorithm demonstrated substantially closer agreement to the measured deformed dose distribution with 3D gamma passing rates (3%/3mm) in the range of 90-91%. These results underscore the necessity and importance of validating DIR algorithms for specific clinical scenarios prior to clinical implementation.</p> / Dissertation

Apesar dos avanços recentes na tecnologia dos aparelhos de ressonância magnética (RM) permitirem a aquisição de imagens de alta resolução, ainda não é possível delinear de forma confiável os limites entre regiões de diferentes citoarquiteturas baseando-se somente nesta modalidade. As imagens de histologia são mandatórias quando se necessita saber o limite exato entre diferentes regiões neuroanatômicas. Contudo, o processamento histológico inevitavelmente causa grandes deforma¸coes no tecido, o que torna a compara- ção direta entre as duas modalidades inviável. Os estudos de neuroimagem/neuroanatomia que necessitam de comparação com a histologia devem necessariamente incluir uma etapa de alinhamento entre as duas modalidades; tarefa que muitas vezes acaba sendo realizada manualmente. Entretanto, o registro manual ´e demorado e pouco acurado, se tornando inviável quando os exames de histologia geram centenas de imagens. Este trabalho propõe um método para registro de imagens de histologia e RM, composto por um conjunto de recomenda¸coes para o preparo das imagens cujo objetivo ´e otimizá-las para o registro; e por uma pipeline computacional capaz de registrar as imagens consideradas. O trabalho aqui descrito foi desenvolvido primeiramente com o intuito de registrar imagens de espécimens de hipocampo provenientes do projeto CINAPCE e, posteriormente, para registro de imagens de encéfalo inteiro provenientes do Banco de Cérebros da Faculdade de Medicina da Universidade de São Paulo. A pipeline computacional foi testada com sucesso em imagens reais de dois encéfalos inteiros. A avaliação quantitativa dos registros realizados foi feita comparando segmenta¸coes manuais do hipocampo direito, núcleo caudado esquerdo e ventrículos laterais superiores, realizadas no volume de RM e da histologia registrada. A quantificação do resultado foi feita através do cálculo das métricas coeficiente de Dice (CSD) e distancia espectral ponderada (DEP) sobre as segmentações. A pipeline obteve um CSD médio de aproximadamente 0,77 e um DEP médio de aproximadamente 0,003. Os resultados mostraram que o método foi capaz de registrar as imagens de histologia nas respectivas imagens de RM exigindo interação mínima com o usuário. / Although latest advances in MRI technology have allowed the acquisition of higher resolution images, reliable delineation of cytoarchitectural boundaries is not yet possible based solely on that modality. Histological images are regularly required to locate the exact limits between neuroanatomical structures. Histological processing is nevertheless prone to cause a high amount of tissue distortion, which prevents direct comparison between the two modalities. Neuroimage/neuroanatomy studies that require direct comparison between histology am MRI must include a registration step. Such task is usually manually performed, but that becames infeasible for large histology volumes. Moreover, manual registration is time consuming and inaccurate. This thesis proposes a set of tissue processing recommendations aiming at optimizing the registration proccess, together with a computational pipeline for registering histology to MRI. The herein described work was initially designed to proccess hippocampi specimens from the CINAPCE project and posteriorly improved to process full brain images from the Brain Bank of the Brazilian Aging Brain Study Group. The pipeline was tested on two full brain histology volumes from the Brain Bank of the Brazilian Aging Brain Study Group. Results were assessed by comparison of manual segmentations of the left caudate nucleus, right hippocampus and superior lateral ventricles, performend on both MRIs and registered histology volumes. Quatitative evaluation was performed by computing the Dice coeficient (DC) and normalized weighted spectral distance (WESD) on the segmentations. The pipeline precessing yielded mean DC of 0.77 and mean WESD of 0.0033. The described method was able to sucessfuly register histology to their corresponding MRI volumes with minimal user interaction.

Anatomic changes occur throughout head and neck radiotherapy, and a new treatment plan is often required to mitigate the resulting changes in delivered dose to key structures. This process is known as adaptive radiotherapy (ART), and can be labour-intensive. The aim of this thesis is to optimise ART, addressing some of the technical and clinical challenges facing its routine clinical implementation. Optimising the frequency and timing of adaptive replanning is important, and it has been shown here that intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) are equally robust to weight loss during head and neck radiotherapy. Plan adaptation strategies that have previously been developed for IMRT are therefore applicable to VMAT.Contour propagation is an important component of ART, and it is essential to ensure that propagated contours are accurate. A method for assessing the suitability of a metric for measuring automatic segmentation accuracy has been developed and applied to the head and neck. For the parotids and larynx, metrics based on surface agreement were better than the commonly used Dice similarity coefficient. By establishing a consensus on which metrics should be used to assess segmentation accuracy, comparison of different algorithms is more objective and should lead to more accurate automatic segmentation. A novel method of assessing contour propagation accuracy on a patient-specific basis has also been developed. This was demonstrated on a cohort of head and neck patients and shows potential as a tool for identifying propagated contours that are subject to a high degree of uncertainty. This is a novel tool that will increase the efficiency of automatic segmentation and, therefore, ART.Optimum ART requires consideration of different radiotherapy-related toxicities, and image-based data mining is a powerful technique for spatially localising dose-response relationships. Correction for multiple comparisons through permutation testing is essential, but has so far only been applied to categorical data. A novel method has been developed for performing permutation testing and image-based data mining with a continuously variable clinical endpoint. Application to trismus for head and neck radiotherapy identified a region with a dose-response relationship in the ipsilateral masseter. Sparing this structure during radiotherapy should reduce the severity of radiation-induced trismus. ART mitigates the dosimetric effects of anatomic changes, and this thesis has addressed technical and clinical challenges that have so far limited its clinical implementation. Detailed knowledge of dose-response relationships will enable selection of patients for ART based on potential clinical benefit, and accurate contour propagation will make ART more efficient, facilitating its routine implementation.

This dissertation focuses on two distinct but related problems involving detection in multiple images. The first problem focuses on the accurate detection of runways by fusing Synthetic Vision System (SVS) and Enhanced Vision System (EVS) images. A novel procedure is developed to accurately detect runways and horizons and also enhance runway surrounding areas by fusing enhanced vision system (EVS) and synthetic vision system (SVS) images of the runway while an aircraft is landing. Because the EVS and SVS frames are not aligned, a registration step is introduced to align the EVS and SVS images prior to fusion. The most notable feature of the registration procedure is that it is guided by the information extracted from the weather-invariant SVS images. Four fusion rules based on combining Discrete Wavelet Transform (DWT) sub-bands are implemented and evaluated. The resulting procedure is tested on real EVS-SVS image pairs and also on image pairs containing simulated EVS images with varying levels of turbulence. The subjective and objective evaluations reveal that runways and horizons can be detected accurately even in poor visibility conditions. Furthermore, it is demonstrated that different aspects of the EVS and SVS images can be emphasized by using different DWT fusion rules. Another notable feature is that the entire procedure is autonomous throughout the landing sequence irrespective of the weather conditions. Given the excellent fusion results and the autonomous feature, it can be concluded that the fusion procedure developed is quite promising for incorporation into head-up displays (HUDs) to assist pilots in safely landing aircrafts in varying weather conditions. The second problem focuses on the blind detection of hidden messages that are embedded in images using various steganography methods. A new steganalysis strategy is introduced to blindly detect hidden messages that have been embedded in JPEG images using various steganography techniques. The key contribution is the formulation of a multi-domain feature extraction, ranking, and selection strategy to improve the steganalysis performance. The multi-domain features are statistical measures extracted from DWT, muti-wavelet (MWT), and slantlet (SLT) transforms. Feature ranking and selection is based on evaluating the performance of each feature independently and combining the best uncorrelated features. The resulting feature set is used in conjunction with discriminant analysis and support vector classifiers to detect the presence/absence of hidden messages in images. Numerous experiments are conducted to demonstrate the improved performance of the new steganalysis strategy over existing steganalysis methods.

Le cancer de la prostate est le cancer le plus fréquent chez l'homme en France et aux pays occidentaux. Il est la troisième cause de décès liés au cancer, étant responsable d'environ 10% des morts. La curiethérapie, une technique de radiothérapie, est liée à une meilleure qualité de vie après le traitement, par rapport aux autres méthodes de traitement. La curiethérapie de la prostate consiste à insérer des sources radioactives dans la prostate afin de délivrer une dose d'irradiation localisée à la tumeur tout en protégeant les tissus sains environnants. L'imagerie multimodale est utilisée afin d'améliorer la précision du traitement. Les images Tomodensitométriques préopératoires, appelées Computed Tomography (CT), peuvent être utilisées pour calculer une distribution personnalisée et plus précise de dose. Pendant l'intervention, le chirurgien utilise un système de guidage temps-réel par l'Ultrason Transrectale, Transrectal Ultrasound (TRUS), pour placer correctement les sources radioactives dans leurs positions souhaitées. Par conséquent, si les positions des sources sont déterminées sur l'image CT, elles doivent être transférées à l'image US. Cependant, un recalage US/CT direct et robuste est difficilement envisageable parce que les tissus mous, telle que la prostate, offrent peu de contraste en CT et en US. En revanche, l'Imagerie par Résonance Magnétique (IRM) fournit un meilleur contraste et peut, potentiellement, améliorer le traitement en améliorant la visualisation. Donc, ces trois modalités (IRM, CT et US) doivent être correctement alignées. Pour compenser les déformations de la prostate, due au changement de taille et forme entre les différentes acquisitions, un recalage non-rigide est nécessaire. Une méthode de recalage entièrement automatique est nécessaire, afin de faciliter son intégration au bloc opératoire. Nous proposons dans un premier temps un recalage IRM/CT basé sur la maximisation de l'information mutuelle en combinaison avec un champ de déformation paramétré par B-Splines. Nous proposons de contraindre le recalage sur des volumes d'intérêt (VOIs) afin d'améliorer la robustesse et le temps de calcul. L'approche proposée a été validée sur des jeux de données cliniques. Une évaluation quantitative a montré que l'erreur de recalage est égale à 1.15±0.20 mm; qui répond à la précision clinique souhaitée. Ensuite, nous proposons un deuxième recalage US/IRM, où nous utilisons une approche multi-résolution pour éviter les minima locaux et améliorer le temps de calcul. Un critère de similarité, qui met en corrélation l'intensité de l'image US avec l'intensité ainsi que le gradient de l'image IRM, a été utilisé afin de trouver la transformation qui aligne les deux images. Cette méthode a été validée sur un fantôme de prostate dans un premier temps pour évaluer sa faisabilité. Ensuite, elle a été validée sur des jeux de données cliniques en utilisant des critères qualitatives et quantitatives. La distance Hausdorff a montré que l'erreur de recalage est égale à 1.44±0.06 mm. L'approche proposée dans ce travail permet d'aller vers un protocole de curiethérapie guidée par l'imagerie multimodale qui puisse améliorer la précision globale de cette procédure. Malgré ces résultats plutôt encourageants, les travaux futurs impliqueront une évaluation plus approfondie sur plus de jeux de données afin d'évaluer la fiabilité et l'efficacité de cette méthode avant de l'intégrer au bloc opératoire. / Prostate cancer is the most common cancer in men in France and western countries. It is the third leading cause of death from cancer, being responsible for around 10% of deaths. Brachytherapy, a radiotherapy technique, is associated with a better health-related quality of life after the treatment, compared to other treatment techniques. Prostate brachytherapy involves the implantation of radioactive sources inside the prostate to deliver a localized radiation dose to the tumor while sparing the surrounding healthy tissues. Multi-modal imaging is used in order to improve the overall accuracy of the treatment. The pre-operative Computed Tomography (CT) images can be used to calculate a personalized and accurate dose distribution. During the intervention, the surgeon utilizes a real-time guiding system, Trasnrectal Ultrasound (TRUS), to accurately place the radioactive sources in their desired pre-planned positions. Therefore, if the positions of the sources were determined on CT, they need to be transferred to US. However, a robust and direct US/CT registration is hardly possible since they both provide low soft tissue contrast. Magnetic Resonance Imaging (MRI), on the other hand, has a superior contrast and can potentially improve the treatment planning and delivery by providing a better visualization. Thus, these three modalities (MRI, US and CT) need to be accurately registered. To compensate for prostate deformations, caused by changes in size and form between the different acquisitions, non-rigid registration is essential. Fully automatic registration methodology is necessary in order to facilitate its integration in a clinical workflow. At first, we propose a registration between pre-operative MR and CT images based on the maximization of the mutual information in combination with a deformation field parameterized by cubic B-Splines. We propose to constrain the registration to volumes of interest (VOIs) in order to improve the robustness and the computational efficiency. The proposed approach was validated on clinical patient datasets. Quantitative evaluation indicated that the overall registration error was of 1.15±0.20 mm; which satisfies the desired clinical accuracy. Then, we propose a second intra-operative US/MRI registration, where a multi-resolution approach is implemented to reduce the probability of local minima and improve the computational efficiency. A similarity measure, which correlates intensities of the US image with intensities and gradient magnitude of the MRI, is used to determine the transformation that aligns the two images. The proposed methodology was validated on a prostate phantom at first to assess its feasibility. Subsequently, the method was validated on clinical patient datasets and evaluated using qualitative and quantitative criteria, resulting in a registration error of 1.44±0.06 mm. The approach proposed in this work allows going towards a multimodal protocol for image-guided brachytherapy which can improve the overall accuracy of this procedure. Despite such encouraging results, future work will involve further evaluation on a larger number of datasets in order to assess the reliability and the efficiency of this methodology before integrating it in a clinical workflow.