Abstract: A method, system and computer readable storage media for segmenting individual intra-oral measurements and registering said individual intraoral measurements to eliminate or reduce registration errors. An operator may use a dental camera to scan teeth and a trained deep neural network may automatically detect portions of the input images that can cause registration errors and reduce or eliminate the effect of these sources of registration errors.

Abstract: A method, system and computer readable storage media for segmenting individual intra-oral measurements and registering said individual intraoral measurements to eliminate or reduce registration errors. An operator may use a dental camera to scan teeth and a trained deep neural network may automatically detect portions of the input images that can cause registration errors and reduce or eliminate the effect of these sources of registration errors.

Abstract: A method, system and computer readable storage media for segmenting individual intra-oral measurements and registering said individual intraoral measurements to eliminate or reduce registration errors. An operator may use a dental camera to scan teeth and a trained deep neural network may automatically detect portions of the input images that can cause registration errors and reduce or eliminate the effect of these sources of registration errors.

Abstract: A method, system and computer readable storage media for segmenting individual intra-oral measurements and registering said individual intraoral measurements to eliminate or reduce registration errors. An operator may use a dental camera to scan teeth and a trained deep neural network may automatically detect portions of the input images that can cause registration errors and reduce or eliminate the effect of these sources of registration errors.

Abstract: A method, system and computer readable storage media for segmenting individual intra-oral measurements and registering said individual intraoral measurements to eliminate or reduce registration errors. An operator may use a dental camera to scan teeth and a trained deep neural network may automatically detect portions of the input images that can cause registration errors and reduce or eliminate the effect of these sources of registration errors.

Abstract: A method, apparatus, system, and computer program for generating clinical information. Information indicating at least one clinical aspect of an object is received. Clinical information of interest relating to the at least one clinical aspect is generated from a plurality of projection images.

Abstract: A method, system and computer readable storage media for segmenting individual intra-oral measurements and registering said individual intraoral measurements to eliminate or reduce registration errors. An operator may use a dental camera to scan teeth and a trained deep neural network may automatically detect portions of the input images that can cause registration errors and reduce or eliminate the effect of these sources of registration errors.

Abstract: A method, system and computer readable storage media for segmenting individual intra-oral measurements and registering said individual intraoral measurements to eliminate or reduce registration errors. An operator may use a dental camera to scan teeth and a trained deep neural network may automatically detect portions of the input images that can cause registration errors and reduce or eliminate the effect of these sources of registration errors.

Abstract: A method, system and computer readable storage media for segmenting individual intra-oral measurements and registering said individual intraoral measurements to eliminate or reduce registration errors. An operator may use a dental camera to scan teeth and a trained deep neural network may automatically detect portions of the input images that can cause registration errors and reduce or eliminate the effect of these sources of registration errors.

Abstract: A method, system and computer readable storage media for segmenting individual intra-oral measurements and registering said individual intraoral measurements to eliminate or reduce registration errors. An operator may use a dental camera to scan teeth and a trained deep neural network may automatically detect portions of the input images that can cause registration errors and reduce or eliminate the effect of these sources of registration errors.

Abstract: A method, system and computer readable storage media for segmenting individual intra-oral measurements and registering said individual intraoral measurements to eliminate or reduce registration errors. An operator may use a dental camera to scan teeth and a trained deep neural network may automatically detect portions of the input images that can cause registration errors and reduce or eliminate the effect of these sources of registration errors.

Abstract: Method, system, apparatus, and computer program products for removing marker artifacts from a tomosynthesis dataset. In the method, a first plurality of projection images are acquired by tomosynthesis x-ray imaging, the first plurality of projection images containing at least one imaged representation of at least one alignment marker. In one aspect, the imaged representation of the at least one alignment marker on the first plurality of projection images is minimized to generate a second plurality of projection images. In another aspect, a plurality of tomographic images are reconstructed from the second plurality of projection images.

Abstract: A method, apparatus, system, and computer program for generating clinical information. Information indicating at least one clinical aspect of an object is received. Clinical information of interest relating to the at least one clinical aspect is generated from a plurality of projection images.

Abstract: Method, system, apparatus, and computer program products for removing marker artifacts from a tomosynthesis dataset. In the method, a first plurality of projection images are acquired by tomosynthesis x-ray imaging, the first plurality of projection images containing at least one imaged representation of at least one alignment marker. In one aspect, the imaged representation of the at least one alignment marker on the first plurality of projection images is minimized to generate a second plurality of projection images. In another aspect, a plurality of tomographic images are reconstructed from the second plurality of projection images.

Abstract: A scanning evanescent microwave microscope (SEMM) that uses near-field evanescent electromagnetic waves to probe sample properties is disclosed. The SEMM is capable of high resolution imaging and quantitative measurements of the electrical properties of the sample. The SEMM has the ability to map dielectric constant, loss tangent, conductivity, electrical impedance, and other electrical parameters of materials. Such properties are then used to provide distance control over a wide range, from to microns to nanometers, over dielectric and conductive samples for a scanned evanescent microwave probe, which enable quantitative non-contact and submicron spatial resolution topographic and electrical impedance profiling of dielectric, nonlinear dielectric and conductive materials. The invention also allows quantitative estimation of microwave impedance using signals obtained by the scanned evanescent microwave probe and quasistatic approximation modeling.

Abstract: A scanning evanescent microwave microscope (SEMM) that uses near-field evanescent electromagnetic waves to probe sample properties is disclosed. The SEMM is capable of high resolution imaging and quantitative measurements of the electrical properties of the sample. The SEMM has the ability to map dielectric constant, loss tangent, conductivity, electrical impedance, and other electrical parameters of materials. Such properties are then used to provide distance control over a wide range, from to microns to nanometers, over dielectric and conductive samples for a scanned evanescent microwave probe, which enable quantitative non-contact and submicron spatial resolution topographic and electrical impedance profiling of dielectric, nonlinear dielectric and conductive materials. The invention also allows quantitative estimation of microwave impedance using signals obtained by the scanned evanescent microwave probe and quasistatic approximation modeling.

Abstract: A scanning evanescent microwave microscope (SEMM) that uses near-field evanescent electromagnetic waves to probe sample properties is disclosed. The SEMM is capable of high resolution imaging and quantitative measurements of the electrical properties of the sample. The SEMM has the ability to map dielectric constant, loss tangent, conductivity, electrical impedance, and other electrical parameters of materials. Such properties are then used to provide distance control over a wide range, from to microns to nanometers, over dielectric and conductive samples for a scanned evanescent microwave probe, which enable quantitative non-contact and submicron spatial resolution topographic and electrical impedance profiling of dielectric, nonlinear dielectric and conductive materials. The invention also allows quantitative estimation of microwave impedance using signals obtained by the scanned evanescent microwave probe and quasistatic approximation modeling.

Abstract: A scanning evanescent microwave microscope (SEMM) that uses near-field evanescent electromagnetic waves to probe sample properties is disclosed. The SEMM is capable of high resolution imaging and quantitative measurements of the electrical properties of the sample. The SEMM has the ability to map dielectric constant, loss tangent, conductivity, electrical impedance, and other electrical parameters of materials. Such properties are then used to provide distance control over a wide range, from to microns to nanometers, over dielectric and conductive samples for a scanned evanescent microwave probe, which enable quantitative non-contact and submicron spatial resolution topographic and electrical impedance profiling of dielectric, nonlinear dielectric and conductive materials. The invention also allows quantitative estimation of microwave impedance using signals obtained by the scanned evanescent microwave probe and quasistatic approximation modeling.