Os sistemas de recuperação de imagens por conteúdo (CBIR -Content-based Image Retrieval) possuem a habilidade de retornar imagens utilizando como chave de busca outras imagens. Considerando uma imagem de consulta, o foco de um sistema CBIR é pesquisar no banco de dados as "n" imagens mais similares à imagem de consulta de acordo com um critério dado. Este trabalho de pesquisa foi direcionado na geração de vetores de características para um sistema CBIR considerando bancos de imagens médicas, para propiciar tal tipo de consulta. Um vetor de características é uma representação numérica sucinta de uma imagem ou parte dela, descrevendo seus detalhes mais representativos. O vetor de características é um vetor "n"-dimensional contendo esses valores. Essa nova representação da imagem pode ser armazenada em uma base de dados, e assim, agilizar o processo de recuperação de imagens. Uma abordagem alternativa para caracterizar imagens para um sistema CBIR é a transformação do domínio. A principal vantagem de uma transformação é sua efetiva caracterização das propriedades locais da imagem. Recentemente, pesquisadores das áreas de matemática aplicada e de processamento de sinais desenvolveram técnicas práticas de "wavelet" para a representação multiescala e análise de sinais. Estas novas ferramentas diferenciam-se das tradicionais técnicas de Fourier pela forma de localizar a informação no plano tempo-freqüência; basicamente, elas têm a capacidade de mudar de uma resolução para outra, o que faz delas especialmente adequadas para a análise de sinais não estacionários. A transformada "wavelet" consiste de um conjunto de funções base que representa o sinal em diferentes bandas de freqüência, cada uma com resoluções distintas correspondentes a cada escala. Estas foram aplicadas com sucesso na compressão, melhoria, análise, classificação, caracterização e recuperação de imagens. Uma das áreas beneficiadas, onde essas propriedades têm encontrado grande relevância, é a área médica, através da representação e descrição de imagens médicas. Este trabalho descreve uma abordagem para um banco de imagens médicas, que é orientada à extração de características para um sistema CBIR baseada na decomposição multiresolução de "wavelets" utilizando os filtros de Daubechies e Gabor. Essas novas características de imagens foram também testadas utilizando uma estrutura de indexação métrica "Slim-tree". Assim, pode-se aumentar o alcance semântico do sistema cbPACS (Content-Based Picture Archiving and Comunication Systems), atualmente em desenvolvimento conjunto entre o Grupo de Bases de Dados e Imagens do ICMC--USP e o Centro de Ciências de Imagens e Física Médica do Hospital das Clínicas de Riberão Preto-USP. / Content-based image retrieval (CBIR) refers to the ability to retrieve images on the basis of the image content. Given a query image, the goal of a CBIR system is to search the database and return the "n" most similar (close) ones to the query image according to a given criteria. Our research addresses the generation of feature vectors of a CBIR system for medical image databases. A feature vector is a numeric representation of an image or part of it over its representative aspects. The feature vector is a "n"-dimensional vector organizing such values. This new image representation can be stored into a database and allow a fast image retrieval. An alternative for image characterization for a CBIR system is the domain transform. The principal advantage of a transform is its effective characterization for their local image properties. In the past few years, researches in applied mathematics and signal processing have developed practical "wavelet" methods for the multiscale representation and analysis of signals. These new tools differ from the traditional Fourier techniques by the way in which they localize the information in the time-frequency plane; in particular, they are capable of trading one type of resolution for the other, which makes them especially suitable for the analysis of non-stationary signals. The "wavelet" transform is a set of basis functions that represents signals in different frequency bands, each one with a resolution matching its scale. They have been successfully applied to image compression, enhancements, analysis, classifications, characterization and retrieval. One privileged area of application where these properties have been found to be relevant is medical imaging. In this work we describe an approach to CBIR for medical image databases focused on feature extraction based on multiresolution "wavelets" decomposition, taking advantage of the Daubechies and Gabor. Fundamental to our approach is how images are characterized, such that the retrieval procedure can bring similar images within the domain of interest, using a metric structure indexing, like the "Slim-tree". Thus, it increased the semantic capability of the cbPACS(Content-Based Picture Archiving and Comunication Systems), currently in joined developing between the Database and Image Group of the ICMC--USP and the Science Center for Images and Physical Medic of the Clinics Hospital of Riberão Preto--USP.

Orientador: Jorge Stolfi / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-16T21:27:57Z (GMT). No. of bitstreams: 1 Zampieri_CarlosEliasArminio_M.pdf: 4003666 bytes, checksum: a730c8935e9f68bc9c1cd9a6e9d68c8c (MD5) Previous issue date: 2010 / Resumo: Neste trabalho apresentamos um método geral para busca de imagem por conteúdo (BIPC, CBIR) em grandes coleções de imagens, usando estimação intervalar multiescala de distância. Consideramos especificamente buscas por exemplo, em que o objetivo é encontrar a imagem da coleção que é mais próxima a uma imagem dada, segundo alguma função de distância de imagens. Neste trabalho não procuramos desenvolver métricas que melhor atendem as intenções do usuário; em vez disso, supondo que a métrica está escolhida, apresentamos um algoritmo genérico (que denominamos MuSIS, de Multiscale Image Search) para realizar a busca de maneira eficiente usando aritmética intervalar. Estimativas intervalares das distâncias entre imagens são usadas para eliminar rapidamente imagens candidatas, considerando apenas versões reduzidas das mesmas, de maneira semelhante ao paradigma de otimização branch-and-bound. Como parte deste trabalho, desenvolvemos estimadores intervalares eficazes para distância euclidiana e algumas variantes da mesma, incluindo métricas sensíveis ao gradiente em escalas variadas. Experimentos indicaram que o método promove significativa redução de custos em relação à busca exaustiva. Apesar de menos eficiente do que outros métodos comumente usados para BIPC, o algoritmo MuSIS sempre retorna a resposta exata - isto é, a imagem mais próxima na métrica escolhida - e não apenas uma aproximação. A abordagem MuSIS é compatível com uma ampla variedade de funções de distância, sem a necessidade de pré-calcular ou armazenar descritores específicos para cada função / Abstract: We present a general method for content-based image retrieval (CBIR) in large image collections, using multiscale interval distance estimation. We consider specifically queries by example, where the goal is to find the image in the collection that is closest to a given image, according to some image distance function. In this work we do not aim to develop metrics that best meet the user's intentions; instead, assuming that the metric is chosen, we describe an algorithm (wich we call MuSIS, for MultiScale Image Search) to perform the search efficiently using interval arithmetic. Interval estimates of the image distances are used to quickly discard candidate images after examining only small versions of them, in a manner similar to the branch-and-bound optimization paradigm. As part of this work, we developed effective interval estimators for the Euclidean distance and for some variations of it, including metrics that are sensitive to the gradient at various scales. Experiments indicate that the method yields significant cost savings over exhaustive search. Although less efficient than other methods commonly used for CBIR, the MuSIS algorithm always returns the exact answer - that is, the nearest image in metric chosen - and not just an approximation thereof. The MuSIS approach is compatible with a wide variety of distance functions without the need to pre-compute or store specific descriptors for each function / Mestrado / Processamento de Imagens / Mestre em Ciência da Computação

Orientador: Cláudia Maria Bauzer Medeiros / Dissertação (mestrado) - Universidade Estadual de Campinas, Instituto de Computação / Made available in DSpace on 2018-08-18T07:07:49Z (GMT). No. of bitstreams: 1 Fedel_GabrieldeSouza_M.pdf: 14390093 bytes, checksum: 63058da33a22121e927f1cdbaff297d3 (MD5) Previous issue date: 2011 / Resumo: A pesquisa em computação aplicada à biodiversidade apresenta muitos desafios, que vão desde o grande volume de dados altamente heterogêneos até a variedade de tipos de usuários. Isto gera a necessidade de ferramentas versáteis de recuperação. As ferramentas disponíveis ainda são limitadas e normalmente só consideram dados textuais, deixando de explorar a potencialidade da busca por dados de outra natureza, como imagens ou sons. Esta dissertação analisa os problemas de realizar consultas multimodais a partir de predicados que envolvem texto e imagem para o domínio de biodiversidade, especificando e implementando um conjunto de ferramentas para processar tais consultas. As contribuições do trabalho, validado com dados reais, incluem a construção de uma ontologia taxonômica associada a nomes vulgares e a possibilidade de apoiar dois perfis de usuários (especialistas e leigos). Estas características estendem o escopo da consultas atualmente disponíveis em sistemas de biodiversidade. Este trabalho está inserido no projeto Bio-CORE, uma parceria entre pesquisadores de computação e biologia para criar ferramentas computacionais para dar apoio à pesquisa em biodiversidade / Abstract: Research on Computing applied to biodiversity present several challenges, ranging from the massive volumes of highly heterogeneous data to the variety in user profiles. This kind of scenario requires versatile data retrieval and management tools. Available tools are still limited. Most often, they only consider textual data and do not take advantage of the multiple data types available, such as images or sounds. This dissertation discusses issues concerning multimodal queries that involve both text and images as search parameters, for the domanin of biodiversity. It presents the specification and implementation of a set of tools to process such queries, which were validate with real data from Unicamp's Zoology Museum. The aim contributions also include the construction of a taxonomic ontology that includes species common names, and support to both researchers and non-experts in queries. Such features extend the scop of queries available in biodiversity information systems. This research is associated with the Biocore project, jointly conducted by researchers in computing and biology, to design and develop computational tools to support research in biodiversity / Mestrado / Banco de Dados / Mestre em Ciência da Computação

Os sistemas de recuperação de imagens por conteúdo (CBIR -Content-based Image Retrieval) possuem a habilidade de retornar imagens utilizando como chave de busca outras imagens. Considerando uma imagem de consulta, o foco de um sistema CBIR é pesquisar no banco de dados as "n" imagens mais similares à imagem de consulta de acordo com um critério dado. Este trabalho de pesquisa foi direcionado na geração de vetores de características para um sistema CBIR considerando bancos de imagens médicas, para propiciar tal tipo de consulta. Um vetor de características é uma representação numérica sucinta de uma imagem ou parte dela, descrevendo seus detalhes mais representativos. O vetor de características é um vetor "n"-dimensional contendo esses valores. Essa nova representação da imagem pode ser armazenada em uma base de dados, e assim, agilizar o processo de recuperação de imagens. Uma abordagem alternativa para caracterizar imagens para um sistema CBIR é a transformação do domínio. A principal vantagem de uma transformação é sua efetiva caracterização das propriedades locais da imagem. Recentemente, pesquisadores das áreas de matemática aplicada e de processamento de sinais desenvolveram técnicas práticas de "wavelet" para a representação multiescala e análise de sinais. Estas novas ferramentas diferenciam-se das tradicionais técnicas de Fourier pela forma de localizar a informação no plano tempo-freqüência; basicamente, elas têm a capacidade de mudar de uma resolução para outra, o que faz delas especialmente adequadas para a análise de sinais não estacionários. A transformada "wavelet" consiste de um conjunto de funções base que representa o sinal em diferentes bandas de freqüência, cada uma com resoluções distintas correspondentes a cada escala. Estas foram aplicadas com sucesso na compressão, melhoria, análise, classificação, caracterização e recuperação de imagens. Uma das áreas beneficiadas, onde essas propriedades têm encontrado grande relevância, é a área médica, através da representação e descrição de imagens médicas. Este trabalho descreve uma abordagem para um banco de imagens médicas, que é orientada à extração de características para um sistema CBIR baseada na decomposição multiresolução de "wavelets" utilizando os filtros de Daubechies e Gabor. Essas novas características de imagens foram também testadas utilizando uma estrutura de indexação métrica "Slim-tree". Assim, pode-se aumentar o alcance semântico do sistema cbPACS (Content-Based Picture Archiving and Comunication Systems), atualmente em desenvolvimento conjunto entre o Grupo de Bases de Dados e Imagens do ICMC--USP e o Centro de Ciências de Imagens e Física Médica do Hospital das Clínicas de Riberão Preto-USP. / Content-based image retrieval (CBIR) refers to the ability to retrieve images on the basis of the image content. Given a query image, the goal of a CBIR system is to search the database and return the "n" most similar (close) ones to the query image according to a given criteria. Our research addresses the generation of feature vectors of a CBIR system for medical image databases. A feature vector is a numeric representation of an image or part of it over its representative aspects. The feature vector is a "n"-dimensional vector organizing such values. This new image representation can be stored into a database and allow a fast image retrieval. An alternative for image characterization for a CBIR system is the domain transform. The principal advantage of a transform is its effective characterization for their local image properties. In the past few years, researches in applied mathematics and signal processing have developed practical "wavelet" methods for the multiscale representation and analysis of signals. These new tools differ from the traditional Fourier techniques by the way in which they localize the information in the time-frequency plane; in particular, they are capable of trading one type of resolution for the other, which makes them especially suitable for the analysis of non-stationary signals. The "wavelet" transform is a set of basis functions that represents signals in different frequency bands, each one with a resolution matching its scale. They have been successfully applied to image compression, enhancements, analysis, classifications, characterization and retrieval. One privileged area of application where these properties have been found to be relevant is medical imaging. In this work we describe an approach to CBIR for medical image databases focused on feature extraction based on multiresolution "wavelets" decomposition, taking advantage of the Daubechies and Gabor. Fundamental to our approach is how images are characterized, such that the retrieval procedure can bring similar images within the domain of interest, using a metric structure indexing, like the "Slim-tree". Thus, it increased the semantic capability of the cbPACS(Content-Based Picture Archiving and Comunication Systems), currently in joined developing between the Database and Image Group of the ICMC--USP and the Science Center for Images and Physical Medic of the Clinics Hospital of Riberão Preto--USP.

Ob Standorte von Kirchen in Deutschland, Schlössern und Rittergütern in Sachsen oder Mühlen in Brandenburg, ob hausnummerngenauer Nachweis von Wohnhäusern in der Dresdner Neustadt oder der Sammlungsorte von Kunstwerken – seit Sommer 2007 können die geografischen Bezüge der Aufnahmen aus der Bilddatenbank der Deutschen Fotothek komfortabel und übersichtlich auf Karten- und Satellitenbildern dargestellt werden.

Το ερευνητικό αντικείμενο της συγκεκριμένης διατριβής αναφέρεται στην επεξεργασία έγχρωμης εικόνας με χρήση της θεωρίας γράφων, την ανάκτηση εικόνας καθώς και την οργάνωση / διαχείριση βάσεων δεδομένων με μεθόδους γραφημάτων και αναγνώρισης προτύπων, με εφαρμογή σε πολυμέσα. Τα συγκεκριμένα προβλήματα προσεγγίστηκαν διατηρώντας τη γενικότητά τους και επιλύθηκαν με βάση τα ακόλουθα σημεία: 1. Ανάπτυξη τεχνικών για την επιλογή χαρακτηριστικών από τις εικόνες βάσει χαρακτηριστικών χαμηλού επιπέδου (χρώματος και υφής), για χρήση τους σε εφαρμογές ομοιότητας και ανάκτησης εικόνας. 2. Υπολογισμός μετρικών και αποστάσεων στο χώρο των χαρακτηριστικών. 3. Μελέτη της πολυσχιδούς δομής των εικόνων μιας βάσης στο χώρο των χαρακτηριστικών. 4. Ελάττωση της διάστασης του χώρου και παραγωγή αναπαραστάσεων δύο διαστάσεων. 5. Εφαρμογή των μεθόδων αυτών σε υποκειμενικές αποστάσεις εικόνων. Η θεωρία γράφων και οι μέθοδοι αναγνώρισης προτύπων χρησιμοποιήθηκαν προκειμένου να παρουσιαστούν βέλτιστες λύσεις αφενός στο πρόβλημα της ανάκτησης εικόνων από βάσεις δεδομένων και αφετέρου στην οργάνωση και διαχείριση τέτοιων βάσεων εικόνων. Η διατριβή φέρνει πιο κοντά την επεξεργασία εικόνας με μεθόδους προερχόμενες από τη θεωρία γραφημάτων, τη στατιστική και την αναγνώριση προτύπων. Σε όλη τη διάρκεια της διατριβής, ιδιαίτερη έμφαση δόθηκε στο ζήτημα της εύρεσης του κατάλληλου συνδυασμού μεταξύ της αποτελεσματικότητας των συστημάτων και της αποδοτικότητας στα πλαίσια της εφαρμογής των προτεινόμενων αλγοριθμικών διαδικασιών. Τα αναλυτικά πειραματικά αποτελέσματα που πραγματοποιήθηκαν, αποδεικνύουν την βελτιωμένη απόδοση των προτεινόμενων μεθοδολογιών. / The subject of this doctoral thesis is related to color image processing using graph theoretic methods, image retrieval and image database management and organization in the reduced feature space, using pattern recognition analysis, with multimedia applications. The author attempted to approach the thesis subject by retaining its genericness and addressing the following points: 1. Development of techniques for extraction of image visual attributes based on low level features (color and texture information), to be used for image similarity and retrieval practices. 2. Calculation of metrics and distances in the feature space. 3. Study of the image manifolds created in the selected feature space. 4. Application of dimensionality reduction techniques and production of biplots. 5. Application of the proposed methodologies using perceptual image distances. Graph theory and pattern recognition methodologies were incorporated in order to provide novel solution to color image retrieval of image databases, as well as to image database management and organization. The current thesis brings closer image processing with graph theoretic methodologies, statistical analysis and pattern recognition. Throughout the thesis, consideration has been taken for finding the best trade off between effectiveness and efficiency when applying the proposed algorithmic procedures. The extended experimental results carried out in all stages of the projected studies reveal the enhanced performance of the proposed methodologies.

Denna kandidatuppsats berör databaser i javabaserade bildhanteringssystem där bilderna lagras och hämtas som binära objekt. I MySQL och en del andra databashanterare kallas detta format för Blob(Binary large object). För att bildhanteringssystemet skall fungera bra krävs det att man använder en snabb databas. Syftet har varit att av ett urval databaser utse den databas som är snabbast i avseende på svarstider för hämtning av bilder som lagras som binära objekt i databaser. Databaserna är de fyra välkända databashanterarna MySQL, MariaDB, PostGreSQL och MongoDB. Testerna har utförts med databaserna integrerade i Javabaserade klient-server moduler för att så mycket som möjligt spegla de villkor som förekommer i ett bildhanteringssystem. De testverktyg som har använts är JMeter som är en avancerad applikation för mätning av svarstider och PerfMon som övervakar åtgång av systemresurser. MongoDB var den snabbaste bilddatabasen men det finns många osäkerhetsfaktorer som måste beaktas vilket också beskrivs i denna kandidatuppsats. Trots att många åtgärder för att motverka osäkerhetsfaktorerna har gjorts, förblir mätosäkerheten stor. Mer åtgärder för att isolera databasernas del av svarstiderna i ett klient-server system måste göras. Förslag på åtgärder redogörs i denna kandidatuppsats. / This bachelor thesis concerns databases in Java-based imaging system where the images are stored and retrieved as binary objects. In MySQL and in some other database management systems this format is called Blob (Binary Large Object). For the imaging system to work well, it is necessary to use a fast database. The aim has been that out of a sample of databases designate the database that is the fastest in terms of response times for downloading images stored as binary objects in databases. The databases are the four well-known database management systems MySQL, MariaDB, PostgreSQL and MongoDB. The tests have been conducted with the databases integrated into Java-based client-server modules in order to as much as possible mirror the conditions prevailing in an imaging system. The test tool that has been used is JMeter which is an advanced application for measuring response times and PerfMon to monitor the consumption of system resources. MongoDB was the fastest image database, but there are many uncertainties that must be considered, which is also explained in this bachelor thesis. Although many measures to counter the uncertainties have been made, the measurement uncertainty remains big. Further measures to isolate the database part of the response times in a client-server system must be made. Proposed measures are described in this bachelor thesis.

This thesis presents a case of study of the development and performance analysis of a surface grading application with real-time compliance. We address the issue of spatial and temporal uniformity in the acquisition system. In a surface grading application it is crucial to ensure the uniform response of the system through time and space. All the results presented for surface grading were obtained using real data from the ceramic tile industry. The VxC TSG database is public and can be accessed at www.disca.upv.es/vision/vxctsg. We present a method based on soft colour-texture descriptors computed in perceptually uniform colour spaces. The method is parameterized and the involved factors are studied using two statistical procedures; experimental design and logistic regression. Although it is not a new theoretical contribution, we have found and demonstrate that a simple set of global colour and texture statistics, together with well-known classifiers, are powerful enough to meet stringent factory requirements for real-time and performance. Also the method is compared with two other approaches from the scientific literature; Colour Histograms and Centile-LBP. Finally, we explore the method's capacity for on-line inspection in a study of real-time compliance and parallelization. / López García, F. (2005). Real-time surface grading of ceramic tiles [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/1909 / Palancia

Aufgrund der rasanten technischen Entwicklung im Bereich der pränatalen Diagnostik in den letzten Jahren werden mehr angeborene Fehlbildungen zu einem früheren Zeitpunkt der Schwangerschaft und detaillierter erkannt. Das führt dazu, dass die zur Autopsie gelangenden Feten zunehmend kleiner sind und komplexere Befunde aufweisen. Gleichzeitig werden die genetischen Ursachen von mehr Erkrankungen, Fehlbildungen und Syndromen aufgedeckt, so dass die DNA-Diagnostik, Chromosomenanlyse u.a. molekulargenetische und biochemische Erkenntnisse die klinisch-genetische Diagnostik zunehmend ergänzen. Durch Festlegung einer gezielten Autopsiestrategie und Nutzung moderner Kommunikationsmittel kann der Pathologe die in den letzten Jahren gestiegenen klinischen Anforderungen erfüllen. Ein Problem ist es jedoch, dass nicht genügend Pathologen auf dem Gebiet der Fetalpathologie spezialisiert sind. Das trifft nicht nur für Deutschland zu, sondern das ist mehr oder weniger eine weltweite Situation. Ein möglicher Lösungsansatz dieses Problems wäre die Nutzung von Softwareprogrammen, die dazu dienen, unerfahrene Pathologen moderne Anleitungen während der Autopsie von Feten zu geben. Das kann mit einer telepathologischen Betreung durch einen Experten auf diesem Gebiet kombiniert werden. Darüberhinaus erlaubt die derzeitige digitalisierte Befunddokumentation den Vergleich aktueller mit gespeicherten Fällen sowie Recherchen und stellt eine gute Basis zur Erstellung von Lehrmaterial dar. / Due to the enormous technical developments in recent years in the area of prenatal ultrasound more malformations are detected in greater detail and at an earlier point in time during pregnancy than in the past. As a result, fetuses of increasingly smaller size and with complex diagnoses are presented for autopsy. At the same time, the genetic causes of ever more diseases, malformations and syndromes are being discovered, so that DNA diagnostics, chromosome analysis and, among others, molecular-genetic and biochemical investigations have come increasingly to complement clinical-genetic diagnostics. Through establishment of a clinically oriented autopsy strategy and the use of modern communication media, pathologists can satisfy the increased clinical demands of recent years. The remaining problem is that we do not have enough pathologists experienced in fetal pathology. This is not only true for Germany, it is more less the situation worldwide. One means of dealing with this problem may be the use of software programs to guide inexperienced pathologists through the modern autopsy procedure. This can be combined with the use of telepathological advise given by an expert in the field. Over and above this, digitized documentation of findings can be used in research, which allows the comparison of current with previously saved cases and presents a good basis for the development of education material.

Aufgrund der rasanten technischen Entwicklung im Bereich der pränatalen Diagnostik in den letzten Jahren werden mehr angeborene Fehlbildungen zu einem früheren Zeitpunkt der Schwangerschaft und detaillierter erkannt. Das führt dazu, dass die zur Autopsie gelangenden Feten zunehmend kleiner sind und komplexere Befunde aufweisen. Gleichzeitig werden die genetischen Ursachen von mehr Erkrankungen, Fehlbildungen und Syndromen aufgedeckt, so dass die DNA-Diagnostik, Chromosomenanlyse u.a. molekulargenetische und biochemische Erkenntnisse die klinisch-genetische Diagnostik zunehmend ergänzen. Durch Festlegung einer gezielten Autopsiestrategie und Nutzung moderner Kommunikationsmittel kann der Pathologe die in den letzten Jahren gestiegenen klinischen Anforderungen erfüllen. Ein Problem ist es jedoch, dass nicht genügend Pathologen auf dem Gebiet der Fetalpathologie spezialisiert sind. Das trifft nicht nur für Deutschland zu, sondern das ist mehr oder weniger eine weltweite Situation. Ein möglicher Lösungsansatz dieses Problems wäre die Nutzung von Softwareprogrammen, die dazu dienen, unerfahrene Pathologen moderne Anleitungen während der Autopsie von Feten zu geben. Das kann mit einer telepathologischen Betreung durch einen Experten auf diesem Gebiet kombiniert werden. Darüberhinaus erlaubt die derzeitige digitalisierte Befunddokumentation den Vergleich aktueller mit gespeicherten Fällen sowie Recherchen und stellt eine gute Basis zur Erstellung von Lehrmaterial dar. / Due to the enormous technical developments in recent years in the area of prenatal ultrasound more malformations are detected in greater detail and at an earlier point in time during pregnancy than in the past. As a result, fetuses of increasingly smaller size and with complex diagnoses are presented for autopsy. At the same time, the genetic causes of ever more diseases, malformations and syndromes are being discovered, so that DNA diagnostics, chromosome analysis and, among others, molecular-genetic and biochemical investigations have come increasingly to complement clinical-genetic diagnostics. Through establishment of a clinically oriented autopsy strategy and the use of modern communication media, pathologists can satisfy the increased clinical demands of recent years. The remaining problem is that we do not have enough pathologists experienced in fetal pathology. This is not only true for Germany, it is more less the situation worldwide. One means of dealing with this problem may be the use of software programs to guide inexperienced pathologists through the modern autopsy procedure. This can be combined with the use of telepathological advise given by an expert in the field. Over and above this, digitized documentation of findings can be used in research, which allows the comparison of current with previously saved cases and presents a good basis for the development of education material.