AUTOMATIC RECOGNITION OF DENTAL PATHOLOGIES AS PART OF A CLINICAL DECISION SUPPORT PLATFORM

The current work is done within the context of Romanian National Program II (PNII) research project "Application for Using Image Data Mining and 3D Modeling in Dental Screening" (AIMMS). The AIMMS project aims to design a program that can detect anatomical information and possible pathological formations from a collection of digital imaging and communications in medicine (DICOM) images. The main function of the AIMMS platform is to provide the user with the opportunity to use an integrated dental support platform, using image processing techniques and 3D modeling. From the literature review, it can be found that for the detection and classification of teeth and dental pathologies existing studies are in their infancy. Therefore, the work reported in this article makes a scientific contribution in this field. In this article it is presented the relevant literature review and algorithms that were created for detection of dental pathologies in the context of research project AIMMS

Deep Learning Method for Mandibular Canal Segmentation in Dental Cone Beam Computed Tomography Volumes

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Automated segmentation of dental CBCT image with prior-guided sequential random forests: Automated segmentation of dental CBCT image

Cone-beam computed tomography (CBCT) is an increasingly utilized imaging modality for the diagnosis and treatment planning of the patients with craniomaxillofacial (CMF) deformities. Accurate segmentation of CBCT image is an essential step to generate 3D models for the diagnosis and treatment planning of the patients with CMF deformities. However, due to the image artifacts caused by beam hardening, imaging noise, inhomogeneity, truncation, and maximal intercuspation, it is difficult to segment the CBCT

The Digital Bee Brain: Integrating and Managing Neurons in a Common 3D Reference System

The honeybee standard brain (HSB) serves as an interactive tool for relating morphologies of bee brain neurons and provides a reference system for functional and bibliographical properties (http://www.neurobiologie.fu-berlin.de/beebrain/). The ultimate goal is to document not only the morphological network properties of neurons collected from separate brains, but also to establish a graphical user interface for a neuron-related data base. Here, we review the current methods and protocols used to incorporate neuronal reconstructions into the HSB. Our registration protocol consists of two separate steps applied to imaging data from two-channel confocal microscopy scans: (1) The reconstruction of the neuron, facilitated by an automatic extraction of the neuron's skeleton based on threshold segmentation, and (2) the semi-automatic 3D segmentation of the neuropils and their registration with the HSB. The integration of neurons in the HSB is performed by applying the transformation computed in step (2) to the reconstructed neurons of step (1). The most critical issue of this protocol in terms of user interaction time – the segmentation process – is drastically improved by the use of a model-based segmentation process. Furthermore, the underlying statistical shape models (SSM) allow the visualization and analysis of characteristic variations in large sets of bee brain data. The anatomy of neural networks composed of multiple neurons that are registered into the HSB are visualized by depicting the 3D reconstructions together with semantic information with the objective to integrate data from multiple sources (electrophysiology, imaging, immunocytochemistry, molecular biology). Ultimately, this will allow the user to specify cell types and retrieve their morphologies along with physiological characterizations

Contributions to the three-dimensional virtual treatment planning of orthognathic surgery

Orientadores: José Mario De Martino, Luis Augusto PasseriTese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de ComputaçãoResumo: A tecnologia mais recente à disposição da Cirurgia Ortognática possibilita que o diagnóstico e o planejamento do tratamento das deformidades dentofaciais sejam realizados sob uma representação virtual tridimensional (3D) da cabeça do paciente. Com o propósito de contribuir para o aperfeiçoamento desta tecnologia, o trabalho apresentado nesta tese identificou e tratou quatro problemas. A primeira contribuição consistiu na verificação da validade da hipótese de que a mudança de definição do plano horizontal de Frankfort não produz diferenças de medição clinicamente relevantes quando sob indivíduos cujos crânios são consideravelmente simétricos. Os resultados da análise realizada no contexto deste tese indicam que, ao contrário do que se presumia, a hipótese é falsa. A segunda contribuição consistiu na extensão do método de análise cefalométrica de McNamara para que ele pudesse produzir valores 3D. Ao contrário de outros métodos de análise cefalométrica 3D, a extensão criada produz valores verdadeiramente 3D, não perde as informações do método original e preserva as definições geométricas originais das linhas e planos cefalométricos. A terceira contribuição consistiu a) no estabelecimento de normas cefalométricas para brasileiros adultos de ascendência europeia, a partir de imagens de tomografia computadorizada de feixe cônico, que produz uma imagem craniofacial mais precisa e confiável do que a telerradiografia; e b) na avaliação de dimorfismo sexual, para a identificação de características anatômicas diferenciadas entre homens e mulheres desta população. A quarta e última contribuição consistiu na automatização da principal etapa da tecnologia em questão, na qual o cirurgião executa o reposicionamento dos segmentos ósseos maxilares no crânio. O método criado é capaz de corrigir automaticamente os problemas dentofaciais mais comuns tratados pela Cirurgia Ortognática, que envolvem maloclusão esquelética, assimetria facial e discrepância de maxilares. Todas as contribuições deste trabalho foram publicadas em periódicos internacionais do campo da Odontologia e afinsAbstract: The latest technology available for orthognathic surgery allows the diagnosis and treatment planning of dentofacial deformities based on a three-dimensional (3D) virtual representation of the patient's head. In order to contribute to the improvement of this technology, the work presented in this thesis identified and treated four problems. The first contribution consisted in testing the validity of the hypothesis that changing the definition of the Frankfort horizontal plane does not produce clinically relevant measurement differences for subjects whose skulls are considerably symmetrical. The results of the analysis performed in this thesis indicate that, contrary to what was presumed, the hypothesis is false. The second contribution is an extension of the McNamara's method of cephalometric analysis to produce 3D values. Unlike other methods of 3D cephalometric analysis, the extension produces true 3D values, does not lose information captured by the original method, and preserves the original geometric definitions of the cephalometric lines and planes. The third contribution consisted in a) establishing cephalometric norms for Brazilian adults of European descent, based on images from cone-beam computed tomography, which produce a more accurate and reliable craniofacial image than cephalometric radiography; and b) evaluating sexual dimorphism, for the identification of distinct anatomic features between males and females of this population. The fourth contribution consisted in automating the main stage of the technology in question, in which the surgeon performs the positioning of jaw bone segments in the skull. The created method is able to automatically correct the most common dentofacial problems treated by orthognathic surgery, which involves skeletal malocclusion, facial asymmetry, and jaw discrepancy. The contributions of this work were published in international journals of the field of Dentistry and relatedDoutoradoEngenharia de ComputaçãoDoutor em Engenharia ElétricaCAPE