Segmentierung des Knochens aus T1- und PD-gewichteten Kernspinbildern vom Kopf

Für viele Anwendung, beispielsweise bei der Simulation biomechanischer Eigenschaften des Kopfes oder bei der Lokalisation von Hirnaktivität aus EEG/MEG-Daten, werden genaue, individuelle Modelle des Kopfes benötigt. Bislang erfolgt die Erstellung aus einem T1-gewichteten Kernspinbild. Auf diesen Bildern ist allerdings die innere Kante des Knochens nicht zu erkennen. Daher wird diese geschätzt. Das Ergebnis der genannten Anwendungen hängt aber wesentlich von der Gestalt des Knochens ab. Daher soll zukünftig ein weiteres, PD-gewichtetes Kernspinbild zur Unterstützung der Segmentierung hinzugezogen werden. In dieser Arbeit werden Algorithmen untersucht und daraus Verfahren entwickelt, um den Knochen unter Verwendung eines dual-echo-Datensatzes, bestehend aus einem T1- und einem PD-gewichteten Kernspinbild, zu segmentieren

Comparison of the shaping ability of RaCe, FlexMaster, and ProFile nickel-titanium instruments in severely curved root canals

This in vitro study compared the shaping ability of RaCe, FlexMaster, and ProFile rotary nickel-titanium instruments in severely curved root canals of extracted teeth. Sixty maxillary molars with curvatures ranging from 25° to 65° were embedded in a muffle system and portioned into five horizontal sections (thickness 1.2 mm), starting from the apex. Canals were divided into three groups (n = 20, each) and were prepared with RaCe, FlexMaster, or ProFile rotary nickel-titanium instruments and the TriAuto ZX handpiece using a crown-down preparation technique. We evaluated the difference between pre- and postoperative root canal cross-sections, loss of working length, instrument failure, and preparation time. The root canal area before and after the intervention was determined using an area-measuring software. The data were analyzed statistically using a one-way ANOVA followed by a Kruskal-Wallis multiple-comparison Z-value test. Specimens treated with FlexMaster showed the greatest change from preoperative cross-sections, followed by RaCe and ProFile. The cross-sectional changes induced by RaCe and FlexMaster preparation differed significantly from those produced by ProFile. Loss of working length, instrument failure, and preparation time did not differ significantly between the groups. Root canal preparation with the three instruments did not lead to any significant alteration of the original root anatomy or working length. Thus, we conclude that RaCe, FlexMaster, and ProFile instruments are of comparable efficiency and usefulness in the preparation of severely curved root canals

Focusing Knowledge-based Graph Argument Mining via Topic Modeling

Decision-making usually takes five steps: identifying the problem, collecting data, extracting evidence, identifying pro and con arguments, and making decisions. Focusing on extracting evidence, this paper presents a hybrid model that combines latent Dirichlet allocation and word embeddings to obtain external knowledge from structured and unstructured data. We study the task of sentence-level argument mining, as arguments mostly require some degree of world knowledge to be identified and understood. Given a topic and a sentence, the goal is to classify whether a sentence represents an argument in regard to the topic. We use a topic model to extract topic- and sentence-specific evidence from the structured knowledge base Wikidata, building a graph based on the cosine similarity between the entity word vectors of Wikidata and the vector of the given sentence. Also, we build a second graph based on topic-specific articles found via Google to tackle the general incompleteness of structured knowledge bases. Combining these graphs, we obtain a graph-based model which, as our evaluation shows, successfully capitalizes on both structured and unstructured data