Recalage multimodale [i.e. multimodal] d'images de résonance magnétique et échographiques de la prostate

En aquesta tesi s'investiga l'ús de diferents tècniques de registre deformable per registrar imatges de ressonància magnètica preoperatòries i imatges d'ultrasò interoperatòries en la biòpsia de pròstata. Un registre correcte garanteix l'adequada presa de mostres de biòpsia dels teixits malignes de la pròstata i redueix la taxa de re-biòpsies. Aquesta tesis inicialment presenta una comparació i resultats experimentals d’uns dels mètodes de registre més utilitzats basats en intensitat i en punts (landmarks): thin-plate splines i deformacions free form utilitzant B-splines. La principal contribució d'aquesta tesi és una nova metodologia de registre per imatges multimodals basada en splines i formulació difeomòrfica. En aquesta metodologia, s’assegura el difeomorfisme de la transformació basada en thin-plate splines mitjançant la incorporació d'un conjunt de funcions polinòmiques no lineals. Per tal de garantir deformacions clínicament significatives també introduïm thin-plate splines aproximants de manera que la solució s'obté mitjançant una minimització conjunta de les similituds de la superfície de les regions de la pròstata segmentades i de l'energia de la curvatura del thin-plate spline. El mètode per establir les correspondències de punts per el registre en thin-plate splines és un mètode geomètric basat en la simetria de la forma de la pròstata. Alhora, es suggereix una millora addicional basada en la utilització de la mètrica Bhattacharyya en la representació de forma (shape context) dels contorns de la pròstata segmentats. La metodologia de deformació proposada inicialment és computacionalment costosa i no està ben adaptada per el registre interoperatiu durant la biòpsia de pròstata. Per tant, s’investiga més a fons un procediment d'aprenentatge off-line per aprendre els paràmetres de deformació dels thin-plate splines a partir d'un conjunt d'entrenament de dades ressonància magnètica preoperatòries i les seves corresponents imatges d'ultrasò interoperatòries i es construeixen models de deformació mitjançant l'aplicació de mètodes d’agrupació espectral (spectral clustering) en els paràmetres de deformació. Les estimacions lineals d'aquests models de deformació s'apliquen després en un conjunt de test de ressonància magnètica i ultrasò. El problema de trobar la llesca del volum de ressonància magnètica preoperatòria que coincideixi amb la imatge d'ultrasò interoperatòria ens ha motivat a investigar sobre les mesures de similitud basades en la forma i contingut de la imatge i ens ha portat a proposar un nou mètode per a la correspondència tall a tall basat en la maximització conjunta de les mesures de similitud esmentadesThis thesis investigates the employment of different deformable registration techniques to register pre-operative magnetic resonance and inter-operative ultrasound images during prostate biopsy. Accurate registration ensures appropriate biopsy sampling of malignant prostate tissues and reduces the rate of re-biopsies. Therefore, we provide comparisons and experimental results for some landmark- and intensity-based registration methods: thin-plate splines, free-form deformation with B-splines. The primary contribution of this thesis is a new spline-based diffeomorphic registration framework for multimodal images. In this framework we ensure diffeomorphism of the thin-plate spline-based transformation by incorporating a set of non-linear polynomial functions. In order to ensure clinically meaningful deformations we also introduce the approximating thin-plate splines so that the solution is obtained by a joint-minimization of the surface similarities of the segmented prostate regions and the thin-plate spline bending energy. The method to establish point correspondences for the thin-plate spline-based registration is a geometric method based on prostate shape symmetry but a further improvement is suggested by computing the Bhattacharyya metric on shape-context based representation of the segmented prostate contours. The proposed deformable framework is computationally expensive and is not well-suited for registration of inter-operative images during prostate biopsy. Therefore, we further investigate upon an off-line learning procedure to learn the deformation parameters of a thin-plate spline from a training set of pre-operative magnetic resonance and its corresponding inter-operative ultrasound images and build deformation models by applying spectral clustering on the deformation parameters. Linear estimations of these deformation models are then applied on a test set of inter-operative and pre-operative ultrasound and magnetic resonance images respectively. The problem of finding the pre-operative magnetic resonance image slice from a volume that matches the inter-operative ultrasound image has further motivated us to investigate on shape-based and image-based similarity measures and propose for slice-to-slice correspondence based on joint-maximization of the similarity measures.Dans cette thèse, nous avons exploré différentes méthodes de recalage déformables pouvant être appliquées entre les images IRM et les images ETR acquises pendant la biopsie. Nous avons observé à partir d'une étude de la littérature que les méthodes de recalage déformables existantes pour le recalage des images de prostate multimodales ne fournissent pas de précisions satisfaisantes et que la plupart sont coûteuse [sic] en ressources informatiques, notre méthode proposée n'étant pas une exception à cette tendance. Dans ce contexte, notre objectif secondaire a été de rechercher une méthode de recalage déformable qui puisse être appliquée au cours des interventions (nécessitant du temps réel). Par conséquent, nous proposons un schéma d'apprentissage où les paramètres de déformation sont appris sur une série d'images d'entraînement puis modélisés et une estimation linéaire de ces modèles est ensuite appliquée pour recaler les images ETR-IRM. Cette solution assure une vitesse de calcul sans compromettre beaucoup la précision de recalage.Dans les expérimentations réalisées pour valider nos travaux, la sonde transrectale de biopsie n'était pas équippée pour permettre une localisation 3D (par conséquent, la position spatiale (coordonnée z) des ETR images par rapport au système d'imagerie n'était pas disponible). Toutefois, pour la fusion ETR-IRM, il est important d'identifier la coupe pré-biopsie axiale IRM qui correspond à l'image ETR acquise au cours de la biopsie. Par conséquent, un autre objectif de ce travail a été d'identifier automatiquement la coupe axiale IRM d'un volume pré-biopsie correspondant à l'image ETR en utilisant une méthode qui exploite les métriques de similarité basées sur l'image et la forme

Recalage multimodale [i.e. multimodal] d'images de résonance magnétique et échographiques de la prostate

Dans cette thèse, nous avons exploré différentes méthodes de recalage déformables pouvant être appliquées entre les images IRM et les images ETR acquises pendant la biopsie. Nous avons observé à partir d'une étude de la littérature que les méthodes de recalage déformables existantes pour le recalage des images de prostate multimodales ne fournissent pas de précisions satisfaisantes et que la plupart sont coûteuse [sic] en ressources informatiques, notre méthode proposée n'étant pas une exception à cette tendance. Dans ce contexte, notre objectif secondaire a été de rechercher une méthode de recalage déformable qui puisse être appliquée au cours des interventions (nécessitant du temps réel). Par conséquent, nous proposons un schéma d'apprentissage où les paramètres de déformation sont appris sur une série d'images d'entraînement puis modélisés et une estimation linéaire de ces modèles est ensuite appliquée pour recaler les images ETR-IRM. Cette solution assure une vitesse de calcul sans compromettre beaucoup la précision de recalage.Dans les expérimentations réalisées pour valider nos travaux, la sonde transrectale de biopsie n'était pas équippée pour permettre une localisation 3D (par conséquent, la position spatiale (coordonnée z) des ETR images par rapport au système d'imagerie n'était pas disponible). Toutefois, pour la fusion ETR-IRM, il est important d'identifier la coupe pré-biopsie axiale IRM qui correspond à l'image ETR acquise au cours de la biopsie. Par conséquent, un autre objectif de ce travail a été d'identifier automatiquement la coupe axiale IRM d'un volume pré-biopsie correspondant à l'image ETR en utilisant une méthode qui exploite les métriques de similarité basées sur l'image et la forme.This thesis investigates the employment of different deformable registration techniques to register pre-operative magnetic resonance and inter-operative ultrasound images during prostate biopsy. Accurate registration ensures appropriate biopsy sampling of malignant prostate tissues and reduces the rate of re-biopsies. Therefore, we provide comparisons and experimental results for some landmark- and intensity-based registration methods: thin-plate splines, free-form deformation with B-splines. The primary contribution of this thesis is a new spline-based diffeomorphic registration framework for multimodal images. In this framework we ensure diffeomorphism of the thin-plate spline-based transformation by incorporating a set of non-linear polynomial functions. In order to ensure clinically meaningful deformations we also introduce the approximating thin-plate splines so that the solution is obtained by a joint-minimization of the surface similarities of the segmented prostate regions and the thin-plate spline bending energy. The method to establish point correspondences for the thin-plate spline-based registration is a geometric method based on prostate shape symmetry but a further improvement is suggested by computing the Bhattacharyya metric on shape-context based representation of the segmented prostate contours. The proposed deformable framework is computationally expensive and is not well-suited for registration of inter-operative images during prostate biopsy. Therefore, we further investigate upon an off-line learning procedure to learn the deformation parameters of a thin-plate spline from a training set of pre-operative magnetic resonance and its corresponding inter-operative ultrasound images and build deformation models by applying spectral clustering on the deformation parameters. Linear estimations of these deformation models are then applied on a test set of inter-operative and pre-operative ultrasound and magnetic resonance images respectively. The problem of finding the pre-operative magnetic resonance image slice from a volume that matches the inter-operative ultrasound image has further motivated us to investigate on shape-based and image-based similarity measures and propose for slice-to-slice correspondence based on joint-maximization of the similarity measures.DIJON-BU Doc.électronique (212319901) / SudocSudocFranceF

B-splines Coupled with Quadrature Texture to Register Prostate Multimodal Images

International audienceNeedle biopsy of the prostate is guided by Transrectal Ultrasound (TRUS) imaging. The TRUS images do not provide proper spatial localiza- tion of malignant tissues due to the poor sensitivity of TRUS to visualize early malignancy. Magnetic Reso- nance Imaging (MRI) has been shown to be sensitive for detection of early stage malignancy and therefore, a novel 2D deformable registration method that overlays pre-biopsy MRI onto TRUS images has been proposed. Method: The registration method involves B-spline de- formations with Normalized Mutual Information (NMI) as similarity measure computed from the tex- ture images obtained from the amplitude responses of the directional quadrature filter pairs. Registration ac- curacy of the proposed method is evaluated by com- puting the Dice Similarity coefficient (DSC) and 95% Hausdorff Distance (HD) values for 20 patient datasets and Target Registration Error (TRE) for 18 patients only where homologous structures are visible in both the TRUS and transformed MR images. Results: The proposed method and B-splines using NMI computed from intensities provide average TRE values of 2.64±1.37 mm and 4.43±2.77 mm respectively. Our J. Mitra*, R. Mart'ı, A. Oliver, X. Llad'o, S. Ghose Universitat de Girona,Computer Vision and Robotics Group, Girona, Spain. E-mail: [email protected], [email protected], [email protected], [email protected], [email protected] J. C. Vilanova Cl'ınica Girona, Girona, Spain. E-mail: [email protected] F. Meriaudeau *Universit'e de Bourgogne, Le2i-UMR CNRS 5158, Le Creusot, France. E-mail: [email protected] method shows statistically significant improvement in TRE when compared to B-spline using NMI computed from intensities with Student's t-test p = 0.02. The proposed method shows 1.18 times improvement over Thin-plate splines registration with average TRE of 3.11±2.18 mm. The mean DSC and the mean 95% HD values obtained with the proposed method of B-spline with NMI computed from texture are 0.943±0.039 and 4.75 ± 2.40 mm respectively. Conclusions: The texture energy computed from the quadrature filter pairs provides better registration ac- curacy for multimodal images than raw intensities. Low TRE values of the proposed registration method adds to the feasibility of it being used during TRUS guided biopsy

Source separation on hyperspectral cube applied to dermatology

International audienceThis paper proposes a method of quantification of the components underlying the human skin that are supposed to be responsible for the effective reflectance spectrum of the skin over the visible wavelength. The method is based on independent component analysis assuming that the epidermal melanin and the dermal haemoglobin absorbance spectra are independent of each other. The method extracts the source spectra that correspond to the ideal absorbance spectra of melanin and haemoglobin. The noisy melanin spectrum is fixed using a polynomial fit and the quantifications associated with it are reestimated. The results produce feasible quantifications of each source component in the examined skin patch

Blind source separation of skin chromophores on a hyperspectral cube

International audienceBackground/Purpose The ASCLEPIOS system developed by the M2D+ team of the Le2i laboratory (Université de Bourgogne, France) allows determination of a skin reflectance spectrum over the visible wavelength range in each pixel of a 2D image, thereby generating a hyperspectral (3D) cube. Reflectance spectra mainly result from the reflectance of two skin chromophores, epidermal melanin and dermal haemoglobin. A source separation method was applied on the mixed reflectance spectra, resulting in two component spectra for melanin and haemoglobin, respectively. We also obtained through this process quantification of each chromophore in each pixel of a 2D skin image. The accuracy of the pure source spectra obtained was validated by comparison with the theoretical spectra of each chromophore [1]. In vivo assessment of the 2D quantification of chromophores was performed on an image of a café-au-lait macule where only melanin accounts for the difference in pigmentation from normal skin. Method Independent component analysis [2] was used as a source separation method. Melanin is mostly found in the epidermis and haemoglobin in the dermis. Thus, melanin and haemoglobin reflectance spectra are assumed to be completely independent from each other. As the known source spectra are non-Gaussian, this criterion was exploited in the separation process. In order to handle the noise in the obtained melanin spectrum, a polynomial fit method has been established to obtain a source spectrum close to the theoretical one. Consequently, melanin quantification was re-estimated using a linear mathematical model. As 'café-au-lait' macules result from increased melanin production from a normal number of melanocytes in the basal epidermal layer, the proposed method was tested on a skin image of a 'café-au-lait' spot on lightly pigmented skin Results Source spectra obtained for melanin and haemoglobin were similar to their calculated theoretical spectra. The amount of melanin calculated from the 2D quantification process was significantly increased in the pigmented area as compared with normal skin. In contrast, haemoglobin quantification was almost uniform, irrespective of visible pigmentation. Conclusions We have developed a quantification method for skin chromophores such as melanin and haemoglobin using an algorithm for blind source separation from hyperspectral data. A café-au-lait macule could be clearly differentiated from normal skin based on its melanin content. Likewise, erythema intensity could also be quantified from haemoglobin content. Therefore, ASCLEPIOS device combined with our blind source separation method could allow non-invasive monitoring of pigmentation and erythema in a number of skin diseases

A comparison of thin-plate splines with automatic correspondences and B-splines with uniform grids for multimodal prostate registration

International audienceThis paper provides a comparison of spline-based registration methods applied to register interventional Trans Rectal Ultrasound (TRUS) and pre-acquired Magnetic Resonance (MR) prostate images for needle guided prostate biopsy. B-splines and Thin-plate Splines (TPS) are the most prevalent spline-based approaches to achieve deformable registration. Pertaining to the strategic selection of correspondences for the TPS registration, we use an automatic method already proposed in our previous work to generate correspondences in the MR and US prostate images. The method exploits the prostate geometry with the principal components of the segmented prostate as the underlying framework and involves a triangulation approach. The correspondences are generated with successive refinements and Normalized Mutual Information (NMI) is employed to determine the optimal number of correspondences required to achieve TPS registration. B-spline registration with successive grid refinements are consecutively applied for a significant comparison of the impact of the strategically chosen correspondences on the TPS registration against the uniform B-spline control grids. The experimental results are validated on 4 patient datasets. Dice Similarity Coefficient (DSC) is used as a measure of the registration accuracy. Average DSC values of 0.97±0.01 and 0.95±0.03 are achieved for the TPS and B-spline registrations respectively. B-spline registration is observed to be more computationally expensive than the TPS registration with average execution times of 128.09 ± 21.7 seconds and 62.83 ± 32.77 seconds respectively for images with maximum width of 264 pixels and a maximum height of 211 pixels

Energy Transfer from Polyaniline to Chlorophyll‑a Supramolecular Assembly in Nanohybrid

Polyaniline (PANI)/chlorophyll-a (CHL-a) nanohybrids have been synthesized using two different oxidants (APS, FeCl₃) where the shape of polymeric nanostructure is influenced by CHL-a supramolecular arrangement in FeCl₃ oxidized system. The presence of stacked CHL-a porphyrin (evident from hypsochromic shift of Q absorption and shortening of lifetime at CHL-a emission) assists the evolution of nanorod cluster from PANI nanoflakes connected by 1D nanofibers. The radiative decay rate of CHL-a is found to increase in nanohybrids oxidized via FeCl₃ rather than those via the APS counterpart as there is a greater amount of CHL-a aggregates present in the former. This phenomenon indicates energy flux along supramolecular stacking. The significant quenching of the PL spectra and the shortening of the decay time of host PANI with increasing CHL-a concentration show the energy transfer from PANI to CHL-a is more pronounced in FeCl₃ oxidized system, due to shorter donor–acceptor distances. These findings clearly pave the way to architect CHL-a-based functional nanomaterial for effective energy transfer

Multi-atlas and unsupervised learning approach to perirectal space segmentation in CT images

Perirectal space segmentation in computed tomography images aids in quantifying radiation dose received by healthy tissues and toxicity during the course of radiation therapy treatment of the prostate. Radiation dose normalised by tissue volume facilitates predicting outcomes or possible harmful side effects of radiation therapy treatment. Manual segmentation of the perirectal space is time consuming and challenging in the presence of inter-patient anatomical variability and may suffer from inter- and intra-observer variabilities. However automatic or semi-automatic segmentation of the perirectal space in CT images is a challenging task due to inter patient anatomical variability, contrast variability and imaging artifacts. In the model presented here, a volume of interest is obtained in a multi-atlas based segmentation approach. Un-supervised learning in the volume of interest with a Gaussian-mixture-modeling based clustering approach is adopted to achieve a soft segmentation of the perirectal space. Probabilities from soft clustering are further refined by rigid registration of the multi-atlas mask in a probabilistic domain. A maximum a posteriori approach is adopted to achieve a binary segmentation from the refined probabilities. A mean volume similarity value of 97% and a mean surface difference of 3.06 ± 0.51 mm is achieved in a leave-one-patient-out validation framework with a subset of a clinical trial dataset. Qualitative results show a good approximation of the perirectal space volume compared to the ground truth.</p

Statistical shape and texture model of quadrature phase information for prostate segmentation

International audiencePurpose: Prostate volume estimation from segmentation of transrectal ultrasound (TRUS) images aids in diagnosis and treatment of prostate hypertro- phy and cancer. Computer-aided accurate and compu- tationally efficient prostate segmentation in TRUS im- ages is a challenging task, owing to low signal-to-noise ratio, speckle noise, calcifications and heterogeneous in- tensity distribution in the prostate region. Method: A multi-resolution framework using texture features in a parametric deformable statistical model of shape and appearance was developed to segment the prostate. Local phase information of log-Gabor quadra- ture filter extracted texture of the prostate region in TRUS images. Large bandwidth of log-Gabor filter en- sures easy estimation of local orientations and zero re- sponse for a constant signal provides invariance to gray level shift. This aids in enhanced representation of the underlying texture information of the prostate unaf- fected by speckle noise and imaging artifacts. The para- metric model of the propagating contour is derived from principal component analysis of prior shape and texture information of the prostate from the training data. The Soumya Ghose*, Jhimli Mitra*, Arnau Oliver, Robert Mart'ı, Xavier Llad'o and Jordi Freixenet Computer Vision and Robotics Group, University of Girona Campus Montilivi, Edifici P-IV,17071 Girona, Spain. E-mail: [email protected], [email protected], {aoliver, marly, llado, and jordif}@eia.udg.edu Joan C.Vilanova Clinica Girona, Calle Joan Maragall 26, 17002 Girona, Spain. Josep Comet University Hospital Dr. Josep Trueta, Av. Frana, 17007 Girona, Spain. Fabrice Meriaudeau *Laboratoire Le2I - UMR CNRS 5158, Universit'e de Bour- gogne,12 Rue de la Fonderie, 71200 Le Creusot, Bourgogne, France. E-mail: [email protected]. parameters were modified using prior knowledge of the optimization space to achieve segmentation. Results: The proposed method achieves a mean Dice similarity coefficient value of 0.95±0.02, and mean ab- solute distance of 1.26±0.51 millimeter when validated with 24 TRUS images of 6 datasets in a leave-one- patient-out validation framework. Conclusions: The proposed method for prostate TRUS image segmentation is computationally efficient and pro- vides accurate prostate segmentations in presence of in- tensity heterogeneities and imaging artifacts