The use of conceptual graphs for the representation of text contents in information retrieval is discussed. A method for measuring the similarity b etween two texts represented as conceptual graphs is presented. The method is based on well-known strategies of text comparison, such as Dice coefficient, with new elements introduced due to the bipartite nature of the conceptual graphs. Examples of...

Accurate spine segmentation allows for improved identification and quantitative characterization of abnormalities of the vertebra, such as vertebral fractures. However, in existing automated vertebra segmentation methods on computed tomography (CT) images, leakage into nearby bones such as ribs occurs due to the close proximity of these visibly intense structures in a 3D CT volume. To reduce th...

Thyroid nodule segmentation is a hard task due to different echo structures, textures and echogenicities in ultrasound (US) images as well as speckle noise. Currently, a typical clinical evaluation involves the manual, approximate measurement in two section planes in order to obtain an estimate of the nodule’s size. The aforementioned nodule attributes are recorded on paper. We propose instead ...

Brain lesion segmentation is a challenging biomedical problem. Here we present a convolutional neural network that produces a semantic segmentation of brain tumors, capable of processing volumetric information from multiple MRI modalities at the same time. This results in the ability to learn from small training datasets and highly imbalanced data. We present a new architecture with three paral...

This paper presents how word alignment techniques could be used for building standardized term banks. It is shown that time and effort could be saved by a relatively simple evaluation metric based on frequency data from term pairs, and source and target distributions inside the alignment results. The proposed Q-value metric is shown to outperform other tested metrics such as Dice’s coefficient,...

Retinal vessel segmentation is an indispensable step for automatic detection of retinal diseases with fundoscopic images. Though many approaches have been proposed, existing methods tend to miss fine vessels or allow false positives at terminal branches. Let alone undersegmentation, over-segmentation is also problematic when quantitative studies need to measure the precise width of vessels. In ...