The XP-Endo Finisher for the removal of calcium hydroxide paste from root canals and from the apical third

The aim was to compare the efficacy of the passive ultrasonic irrigation PUI and the Xp-endo Finisher (FKG-Dentaire, La-Chaux-de-Fonds, Switzerland) in removing the calcium hydroxide paste from root canals and from the apical third. Sixty-eight root canals of single-rooted teeth were shaped using the BT-Race files (FKG-Dentaire, La-Chaux-de-Fonds, Switzerland). Ca(OH)2 was placed in all samples except for the negative control group (n=4). Remaining teeth were randomly divided into three groups: G1-Xp (n=30), G2-PUI (n=30) and the positive control group (n=4). Removal procedure consisted of three repeated one-minute-cycles. Samples were split longitudinally, photos of halves were taken at X6.4 magnification and were analyzed using the ImageJ-Software (The National Institutes of Health NIH, Bethesda, Maryland, USA) to calculate the percentage of surfaces with residual Ca(OH)2; the results were compared using the Wilcoxon-Mann Whitney test. Photos of the apical thirds were taken at X16 and X40 magnifications and were scored by two examiners from (0) to (4). Scores of the apical third were compared using the Fisher test. The Xp-endo Finisher removed completely the Ca(OH)2 dressing from four teeth (13.33%) whereas the PUI in one tooth (3.33%). The mean values of the remaining Ca(OH)2 were (2.1%, 3.6%) respectively and the difference was not significant (p= 0.195). Both examiners found the Xp-endo Finisher more efficient in the apical third and the difference was significant; p= (0.025, 0.047) respectively. The Xp-endo Finisher showed a superiority over the PUI in removing the Ca(OH)2 from the apical third after 3 minutes of activation

Deep Learning-Based Super-Resolution Applied to Dental Computed Tomography

The resolution of dental computed tomography (CT) images is limited by detector geometry, sensitivity, patient movement, the reconstruction technique and the need to minimize radiation dose. Recently, the use of convolutional neural network (CNN) architectures has shown promise as a resolution enhancement method. In the current work, two CNN architectures—a subpixel network and the so called U-net—have been considered for the resolution enhancement of 2-D cone-beam CT image slices of ex vivo teeth. To do so, a training set of 5680 cross-sectional slices of 13 teeth and a test set of 1824 slices of 4 structurally different teeth were used. Two existing reconstruction-based super-resolution methods using l2-norm and total variation regularization were used for comparison. The results were evaluated with different metrics (peak signal-to-noise ratio, structure similarity index, and other objective measures estimating human perception) and subsequent image-segmentation-based analysis. In the evaluation, micro-CT images were used as ground truth.The results suggest the superiority of the proposed CNN-based approaches over reconstruction-based methods in the case of dental CT images, allowing better detection of medically salient features, such as the size, shape, or curvature of the root canal

Segmentation endodontique sur des images scanner 3D : méthodes et validation

Dans les cabinets dentaires, la dévitalisation des dents est un traitement réalisé quotidiennement (6 millions de traitement par an en France). Une bonne connaissance de l'anatomie canalaire (intérieur de la dent ou endodonte) est un pré requis indispensable au succès d'un traitement endodontique. Pour faire face aux nombreuses variations anatomiques qui viennent compliquer cette thérapeutique, les chirurgiens-dentistes ne disposent essentiellement que de la radiographie intra-buccale deux dimensions (2D) laquelle ne permet pas la complète compréhension de cette anatomie 3D. Distorsion, compression de l'anatomie et superposition des structures avoisinantes perturbent la qualité de l'image n'autorisant pas une évaluation qualitative et quantitative précise de cette anatomie. Les appareils de tomographie volumique à faisceau conique (TVFC) présents dans les cabinets dentaires pourraient constituer une alternative en fournissant de petites reconstructions 3D de structures dento-maxillofaciales. Mais l'évaluation de la précision diagnostique des TVFC dentaires sur l'anatomie canalaire est nécessaire afin de pouvoir justifier leur indication pour les traitements endodontiques. En effet, le développement d'une méthode de segmentation endodontique sur des images de TVFC n'est pas aisée du fait de la finesse de cette anatomie canalaire par rapport à la résolution du système d'imagerie, de la qualité d'image et de la difficulté à valider les résultats obtenus. Afin d'aider la thérapeutique endodontique, les travaux réalisés dans cette thèse ont pour but de fournir des outils informatiques et des méthodes utiles à l'obtention d'une évaluation quantitative du réseau canalaire radiculaire. Après une présentation de l'anatomie endodontique et des principes du traitement canalaire, nous avons décrits les caractéristiques techniques des appareils de tomographie volumique à faisceau conique et les outils existants pour évaluer de manière quantitative cette anatomie sur des images issues de micro-scanners haute-résolution dédiés à la recherche. Nous avons ensuite proposé une méthode pour évaluer les résultats de segmentation endodontique en TVFC par comparaison avec les données micro-scanners. Afin de valider cette méthode et d'évaluer la faisabilité de segmenter l'endodonte en TVFC, nous avons testé un seuillage local adaptatif développé pour répondre à notre problématique sur des dents extraites. Pour permettre la validation des résultats de segmentation sur des images de qualité clinique (dégradée par les structures anatomiques autour des dents dans et hors champ de vue), nous avons élaboré et validé un fantôme parodontal réalisé autour de dents extraites et permettant de préserver la comparaison avec la vérité terrain fournie par les micro-scanners. En fin de thèse, nous avons évoqué les perspectives basées sur l'apprentissage profond et les premières études réalisées pour compenser la réduction de la qualité d'image afin de pouvoir tester et valider la segmentation endodontique en condition clinique.In dental offices, endodontic or root canal treatments are daily performed (over 6 million treatments per year in France). A good knowledge of the root canal anatomy (inside of the tooth or pulp) is an indispensable prerequisite for ensuring the success of root canal treatment. To understand and overpass common morphological variations which are potential source of failures during the treatment, two-dimensional (2D) intra buccal radiography can help dental surgeons. However, distortion, anatomical compression and neighboring anatomical structures superposition reduce image quality and do not allow an accurate qualitative and quantitative evaluation of the root canal anatomy. Cone-beam computed tomography (CBCT) available in dental offices might be an alternative by providing 3D reconstructions of dento-maxillofacial structures. But the evaluation of the diagnostic accuracy of dental CBCT devices in identifying root canal anatomy is necessary to justify their indication in endodontic treatment. Indeed, root canal segmentation on (CBCT) images is difficult because of the noise level, resolution limitations, and to the difficulty to validate results. To help dental surgeons in root canal treatment, this thesis aims at providing image processing methods in order to develop segmentation and visualization methods of the inside of the teeth. To begin with, we have introduced the root canal morphology, the different rules of the root canal treatment and described technical specifications of CBCT devices. We also investigated existing techniques and methods to explore quantitatively root canal anatomy on high resolution microcomputed tomography (µCT) images. Afterwards, we proposed a method to evaluate CBCT endodontic segmentation results by comparing with equivalent µCT data. To validate this method and to test endodontic segmentation on CBCT images, we developed a local adaptive thresholding and evaluated results on extracted teeth. To ensure validation on image quality similar to in vivo condition (quality reduced by anatomical structures in and out of the field of view), we designed and validated a periodontal phantom which are made around extracted teeth and allowing to preserve comparison with the ground truth providing by the µCT. At the end of the thesis, we evocated our perspectives based on deep learning and our first results to compensate image quality reduction in order to test endodontic segmentation in clinical condition

Endodontie et tomographie volumique à faisceau conique (exploration détaillée de l'anatomie canalaire par le 9000 3d ® de Kodak)

Le succès de la thérapeutique endodontique dépend grandement de la connaissance de l'anatomie canalaire. Cependant, les chirurgiens dentistes n'ont à leur disposition aucun outil permettant la réalisation de son étude exhaustive. Récemment, le développement des systèmes de radiographie à faisceau conique a considérablement améliorer les possibilités d'imagerie de la région maxillo-faciale. Le but de notre thèse est donc d'évaluer la capacité et la précision d'un appareil de tomographie volumique, le 9000 3D ® de Kodak, pour détailler l'anatomie endodontique. Afin de répondre à cet objectif, nous avons réalisé sur 14 canaux de dents extraites, une étude comparative entre des reconstructions cC et les images numérisées de sections canalaires correspondantes.TOULOUSE3-BU Santé-Centrale (315552105) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Single Image Super-Resolution Of Noisy 3d Dental Ct Images Using Tucker Decomposition

International audienceTensor decomposition has proven to be a strong tool in various 3D image processing tasks such as denoising and superresolution. In this context, we recently proposed a computationally effective, canonical polyadic decomposition (CPD) based algorithm for single image super-resolution. In this work, we investigated the added value brought by Tucker decomposition. While CPD allows a joint implementation of the denoising and deconvolution steps, with Tucker decomposition the denoising is followed by the deconvolution. This way the ill-posedness of the deconvolution caused by noise is partially mitigated. The results achieved using the two different tensor decomposition techniques were compared, and the robustness against noise was investigated. For validation, dental images were used. The superiority of the proposed method is shown in terms of peak signal-to-ratio, structural similarity index, the root canal segmentation accuracy, and runtime

A Novel Fast 3D Single Image Super-Resolution Algorithm

5 pages, 2 figuresInternational audienceThis paper introduces a novel computationally efficient method of solving the 3D single image super-resolution (SR) problem, i.e., reconstruction of a high-resolution volume from its low-resolution counterpart. The main contribution lies in the original way of handling simultaneously the associated decimation and blurring operators, based on their underlying properties in the frequency domain. In particular, the proposed decomposition technique of the 3D decimation operator allows a straightforward implementation for Tikhonov regularization, and can be further used to take into consideration other regularization functions such as the total variation, enabling the computational cost of state-of-the-art algorithms to be considerably decreased. Numerical experiments carried out showed that the proposed approach outperforms existing 3D SR methods

Quantum denoising-based super-resolution algorithm applied to dental tomography images

International audienceEnhancing the spatial resolution of an image is an important field of research in a number of applications including medical ones. In this paper, we address the super-resolution (SR) problem exploiting a newly introduced adaptive quantum denoiser which is based on quantum interaction theory applied in an imaging context. In particular, following recent developments, we impose this external denoiser as a prior function within the Plug-and-Play (PnP) and Regularization by Denoising (RED) approaches. This quantum denoiser combined with, on the one hand, a computationally efficient way of handing both decimation and blur operators, and on the other hand PnP and RED schemes, shows an original way of solving the SR problems. Dental computed tomography images are used to illustrate the potential of the proposed algorithms for high-resolution image retrieval. Numerical experiments show that the proposed methods provide comparable or slightly better results than existing methods

Quantum denoising-based super-resolution algorithm applied to dental tomography images

International audienceEnhancing the spatial resolution of an image is an important field of research in a number of applications including medical ones. In this paper, we address the super-resolution (SR) problem exploiting a newly introduced adaptive quantum denoiser which is based on quantum interaction theory applied in an imaging context. In particular, following recent developments, we impose this external denoiser as a prior function within the Plug-and-Play (PnP) and Regularization by Denoising (RED) approaches. This quantum denoiser combined with, on the one hand, a computationally efficient way of handing both decimation and blur operators, and on the other hand PnP and RED schemes, shows an original way of solving the SR problems. Dental computed tomography images are used to illustrate the potential of the proposed algorithms for high-resolution image retrieval. Numerical experiments show that the proposed methods provide comparable or slightly better results than existing methods

Evaluation of Two Shaping Systems and Two Ultrasonic Irrigation Devices in Removing Root Canal Filling Material from Mesial Roots of Mandibular Molars: A Micro CT Study

We assessed the efficiency of two shaping file systems and two passive ultrasonic irrigation (PUI) devices for removing filling material during retreatment. The mesial canals from 44 extracted mandibular molars were prepared and obturated. The teeth were randomly divided into two groups, and then one group was retreated with Reciproc R25 (VDW, Munich, Germany) (n = 44) and the other group was retreated with 2Shape (TS, Micro Mega, Besançon, France) (n = 44). A micro-computed tomography (CT) scan was taken before and after the retreatment to assess the volume of the filling material remnants. The teeth were then randomly divided into four groups to test two different PUI devices: Irrisafe (Satelec Acteon Group, Merignac, France) and Endo Ultra (Vista Dental Products, Racine, WI, USA). The teeth in Group A were retreated with 2Shape to test the Endo Ultra (n = 22) device, the teeth in Group B were retreated with 2Shape in order to test the Irrisafe (n = 22) device, the teeth in Group C were retreated with Reciproc to test the Endo Ultra (n = 22) device, and Group D was retreated with Reciproc to test the Irrisafe (n = 22) device. A third micro-CT scan was taken after the retreatment to test the PUIs. The percentage of Gutta-Percha (GP) and sealer removed was 94.75% for TS2 (p < 0.001) and 89.3% for R25 (p < 0.001). The PUI significantly enhanced the removal of the filling material by 0.76% for Group A (p < 0.001), 1.47% for Group B (p < 0.001), 2.61% for Group C (p < 0.001), and by 1.66% for Group D (p < 0.001). 2Shape was more effective at removing the GP and sealer during retreatment (p = 0.018). The supplementary approach with PUI significantly improved filling material removal, with no statistical difference between the four groups (p = 0.106)

Assessment of root canal transportation of 2Shape and ProTaper gold in mandibular molar mesial canals: A micro–computed tomographic study

International audienceThe aim of this study was to compare shaping abilities of Protaper Gold® (PTG) and 2Shape® (TS) by using a new automatic process and micro-computed tomography (Micro-CT). 32 first mandibular molars with two separate mesial canals were selected. Only mesial roots were prepared with PTG and TS. Pre- and post-operative scans were performed using Micro-CT to provide volumes with a voxel size of 20 μm. Volumes, non-instrumented area, amount of transportation and centering ability in coronal, middle and apical third shaping time and procedural errors were recorded. TS and PTG increased the endodontic volume of 2.98 mm3 (±1.56) and 3.21 mm3 (±1.78) respectively with no statistical difference (p = .168) and no procedural errors. No significant difference was found concerning canal transportation among groups but only within the same group PTG (p value < .001) and TS (p value < .001). The mean centering ratio was significantly different only between the section levels for PTG (p value < .001) and TS (p value = .01); it was significantly reduced in the cervical third. The percentage of untouched canal walls ranged between 29.78% (±15.145) and 36.60% (±11.968) respectively for PTG and TS with no statistical difference among groups (p value = .168). TS and PTG with post machining heat treatment were able to produce centered preparations with no significant difference or procedural errors. TS system provided a shorter preparation time than PTG files