Abstract: Method of segmenting anatomical structures such as organs in 3D scans in an architecture that combines U-net, time-distributed convolutions and bidirectional convolutional LSTM.

Abstract: An enriched population of modified lipopolysaccharide (LPS) molecular species being: devoid of phosphate group at position C1 of the reducing end of their lipid A domain; and substituted at position C6? of the non-reducing end of their lipid A domain by a hydrophilic moiety, with the proviso that the hydrophilic moiety is not a hydroxyl group. Also, compositions that include the enriched population of modified LPS and uses of naturally-occurring LPS molecular species and/or enriched population of modified LPS molecular species for treating and/or preventing cancer, inflammatory diseases or infectious diseases, and for stimulating an immune response or vaccinating a subject.

Abstract: A method for training an artificial neural network on an additional untrained segmentation task prevents the loss of previously acquired segmentation skills on originally trained segmentation tasks.

Abstract: Method of segmenting anatomical structures such as organs in 3D scans in an architecture that combines U-net, time-distributed convolutions and bidirectional convolutional LSTM.

Abstract: A pipe-line method for multi-label segmentation of anatomic structures in a medical image using a convolutional neural network trained with a weighted loss function takes into account under—representation of at least one anatomical structure in a ground-truth mask relative to other anatomical structures. Different architectures for the convolutional neural network are described.

Abstract: A method for training an artificial neural network on an additional untrained segmentation task prevents the loss of previously acquired segmentation skills on originally trained segmentation tasks.

Abstract: A pipe-line method for multi-label segmentation of anatomic structures in a medical image using a convolutional neural network trained with a weighted loss function takes into account under—representation of at least one anatomical structure in a ground-truth mask relative to other anatomical structures. Different architectures for the convolutional neural network are described.

Abstract: A method and system for automatically detecting systemic arteries in arbitrary field-of-view computed tomography angiography (CTA) includes fully-automatically analyzing a medical image represented by a digital image representation.

Abstract: A method, and an according apparatus and system, for analyzing medical images of blood vessels includes the steps of a) classifying a surrounding of at least one vessel represented in at least one medical image by applying a first classifier to the medical image such that the surrounding of the vessel is assigned to one of at least two surrounding classes, and b) segmentation of the at least one vessel dependent on the surrounding class to which the surrounding of the vessel has been assigned. The invention allows for a reliable segmentation and/or shape detection, in particular bifurcation detection, of blood vessels represented in medical images.

Abstract: A method and system for automatically detecting systemic arteries in arbitrary field-of-view computed tomography angiography (CTA) includes fully-automatically analyzing a medical image represented by a digital image representation.

Abstract: A method, an apparatus, and a system for labeling one or more parts of a spine in at least one magnetic resonance image of a human or animal body, includes transforming the image having a first number of intensity levels into a target image having a second number of intensity levels, the second number of intensity levels being smaller than the first number of intensity levels, preferably by considering the entropy of texture variations in one or more training images; determining a position, in particular a center position, in each of the one or more parts of the spine in the target image; and labeling the determined position of the one or more parts of the spine in the image or the target image with anatomical labels.

Abstract: A method, and an according apparatus and system, for analyzing medical images of blood vessels includes the steps of a) classifying a surrounding of at least one vessel represented in at least one medical image by applying a first classifier to the medical image such that the surrounding of the vessel is assigned to one of at least two surrounding classes, and b) segmentation of the at least one vessel dependent on the surrounding class to which the surrounding of the vessel has been assigned. The invention allows for a reliable segmentation and/or shape detection, in particular bifurcation detection, of blood vessels represented in medical images.

Abstract: A method, and an according apparatus and system, for segmentation of anatomical structures in medical images includes segmenting an anatomical structure represented in a medical image by applying an algorithm based on a morphological active contour without edges (MACWE) to the medical image, wherein in the algorithm based on the morphological active contour without edges one or more features relating to a surrounding and/or context of the anatomical structure represented in the medical image are considered.

Abstract: A filter for use in a spectrometer to filter transmitted radiation and wherein the filter has a birefringent element responsive to an applied signal, a first polarizer for polarizing the radiation transmitted by a sample, a second polarizer for polarizing the radiation transmitted by the birefringent element, and wherein the birefringent element has a birefringent member having a first birefringence and the birefringent member being responsive to a force applied thereto to generate an additional second birefringence; and the filter having a driver for applying a force to the birefringent member in accordance with the applied signal, and the driver has a piezoelectric member coupled to the birefringent member on one end or at two opposite ends.