Abstract: A training method for training neural networks to determine a magnetic susceptibility distribution of a sample may include: storing a simulated magnetic susceptibility map of the sample, generating a modified magnetic susceptibility map by combining an influence of one or more external magnetic susceptibility sources with the simulated magnetic susceptibility map and storing the modified magnetic susceptibility maps. The method may include generating a first training image by applying a quantitative susceptibility mapping model the modified magnetic susceptibility map and storing the first training image, applying the first neural network to the first image and a second neural network to an output of the first neural network and changing network parameters of the first and the second neural network depending on a deviation of an output of the second artificial neural network from the simulated magnetic susceptibility map.

Abstract: A dental model, includes (a) an upper segment, the upper segment having a shape corresponding to at least a portion of a dental arch of a human patient; (b) a base segment having an external surface and a bottom surface; (c) at least one internal cavity formed in the base segment, and optionally the upper segment, the at least one internal cavity extending through the bottom surface; and (d) at least one wash channel extending from the external surface of the base segment through the base segment and into the at least one internal cavity.

Abstract: A training method for training neural networks to determine a magnetic susceptibility distribution of a sample may include: storing a simulated magnetic susceptibility map of the sample, generating a modified magnetic susceptibility map by combining an influence of one or more external magnetic susceptibility sources with the simulated magnetic susceptibility map and storing the modified magnetic susceptibility maps. The method may include generating a first training image by applying a quantitative susceptibility mapping model the modified magnetic susceptibility map and storing the first training image, applying the first neural network to the first image and a second neural network to an output of the first neural network and changing network parameters of the first and the second neural network depending on a deviation of an output of the second artificial neural network from the simulated magnetic susceptibility map.

Abstract: A dental model, includes (a) an upper segment, said upper segment having a shape corresponding to at least a portion of a dental arch of a human patient; (b) a base segment having an external surface and a bottom surface; (c) at least one internal cavity formed in said base segment, and optionally said upper segment, said at least one internal cavity extending through said bottom surface; and (d) at least one wash channel extending from said external surface of said base segment through said base segment and into said at least one internal cavity.

Abstract: Techniques are disclosed to leverage the use of convolutional neural networks or similar machine learning algorithms to predict an underlying susceptibility distribution from MRI phase data, thereby solving the ill-posed inverse problem. These techniques include the use of Deep Quantitative Susceptibility “DeepQSM” mapping, which uses a large amount of simulated susceptibility distributions and computes phase distribution using a unique forward solution. These examples are then used to train a deep convolutional neuronal network to invert the ill-posed problem.

Abstract: A dental model, includes (a) an upper segment, the upper segment having a shape corresponding to at least a portion of a dental arch of a human patient; (b) a base segment having an external surface and a bottom surface; (c) at least one internal cavity formed in the base segment, and optionally the upper segment, the at least one internal cavity extending through the bottom surface; and (d) at least one wash channel extending from the external surface of the base segment through the base segment and into the at least one internal cavity.

Abstract: A method of making at least one three-dimensional object by additive manufacturing, including: (a) producing, on a carrier platform, by bottom-up stereolithography from a single batch of polymerizable resin, a composite article comprising and produced in the sequence of: (i) an open lattice layer on the carrier platform; then (ii) a frangible layer on the lattice layer; and then (iii) at least one three-dimensional object on the frangible layer; then (b) cleaning the composite article with a wash liquid while on the carrier platform; (c) optionally separating the composite article from the carrier platform; and (d) optionally further curing the composite article; and then (e) separating the at least one three-dimensional object from the lattice layer by cutting or breaking the frangible layer.

Abstract: In a magnetic resonance method and apparatus, deficiencies in conventional masking in quantitative susceptibility mapping (QSM) are addressed by the inclusion of an additional step in the conventional QSM post-processing pipeline. In this additional step, atlas-based segmentation techniques, which have been developed for morphological applications such as T1w MPRAGE are used in order to provide the mask. This mask is then fed to the remainder of the QSM post-processing pipeline.

Abstract: In a magnetic resonance method and apparatus, deficiencies in conventional masking in quantitative susceptibility mapping (QSM) are addressed by the inclusion of an additional step in the conventional QSM post-processing pipeline. In this additional step, atlas-based segmentation techniques, which have been developed for morphological applications such as T1w MPRAGE are used in order to provide the mask. This mask is then fed to the remainder of the QSM post-processing pipeline.

Abstract: A method of making at least one three-dimensional object by additive manufacturing, including: (a) producing, on a carrier platform, by bottom-up stereolithography from a single batch of polymerizable resin, a composite article comprising and produced in the sequence of: (i) an open lattice layer on the carrier platform; then (ii) a frangible layer on the lattice layer; and then (iii) at least one three-dimensional object on the frangible layer; then (b) cleaning the composite article with a wash liquid while on the carrier platform; (c) optionally separating the composite article from the carrier platform; and (d) optionally further curing the composite article; and then (e) separating the at least one three-dimensional object from the lattice layer by cutting or breaking the frangible layer.

Abstract: A dental model, includes (a) an upper segment, said upper segment having a shape corresponding to at least a portion of a dental arch of a human patient; (b) a base segment having an external surface and a bottom surface; (c) at least one internal cavity formed in said base segment, and optionally said upper segment, said at least one internal cavity extending through said bottom surface; and (d) at least one wash channel extending from said external surface of said base segment through said base segment and into said at least one internal cavity.

Abstract: Techniques are disclosed to leverage the use of convolutional neural networks or similar machine learning algorithms to predict an underlying susceptibility distribution from MRI phase data, thereby solving the ill-posed inverse problem. These techniques include the use of Deep Quantitative Susceptibility “DeepQSM” mapping, which uses a large amount of simulated susceptibility distributions and computes phase distribution using a unique forward solution. These examples are then used to train a deep convolutional neuronal network to invert the ill-posed problem.

Abstract: A composite article useful in additive manufacturing typically includes: (a) optionally, but preferably, a base; (b) at least one three-dimensional lattice support connected to the base (when present); (c) at least one three-dimensional object, the object having a bottom surface portion, a top surface portion, at least one upright segment, and optionally at least one overhanging segment (e.g., a bridging segment; a cantilevered segment, etc.); (d) interconnecting supports connecting (i) each the at least one overhanging segment to the three-dimensional lattice and/or (ii) each at least one upright segment to the three-dimensional lattice; and (e) optionally, but in some embodiments preferably, a plurality of elongate stand-off supports interconnecting the bottom surface portion of each the three-dimensional object to the base.

Abstract: The invention relates to a device and to a method for optically detecting and receiving, in particular for digitising, interconnected sheets (10) along a margin (6), in particular a book (7), comprising a bearing and/or securing device (8) for the sheets (10) and a receiving device (1) which comprises two angular imaging surfaces (2) which have a common vertex edge (3) and which are arranged in relation to each other, in addition to at least one receiving unit (19). The bearing and/or securing device (8) and the receiving device (1) are arranged in a displaceable manner in relation to each other, such that the vertex edge (3) of receiving device (1) and the margin (6) of the sheets (10) can be joined together. The receiving device (1) comprises traction means (15, 16) which are used to catch at least one sheet (10?) when removing the vertex edge (3) of the receiving device (1) from the margin (6) of the sheets (10).