Abstract: Tomosynthesis imaging methods, systems, and apparatus include a source to emit penetrating particles toward an object, a detector to acquire a series of projection images responsive to the penetrating particles, and a positioning system to position the source with respect to the object and the detector. An imaging system controls the positioning apparatus, source, and detector to acquire images along a primary scan direction with offsets in a secondary scan direction. An oscillatory velocity may be applied to the source to reduce focal spot blur. Tomographic volumes are constructed that are capable of exhibiting super-resolution from data representing the acquired series of projection images taking the primary scan direction and the offsets into consideration.

Abstract: Tomosynthesis imaging methods, systems, and apparatus are disclosed. The systems may include a source to emit penetrating particles toward an object, a detector to acquire a series of projection images responsive to the penetrating particles, and a positioning system to position the source relative to the object and the detector. An imaging system controls the positioning apparatus, source, and detector to acquire images along a primary scan direction with offsets in a secondary scan direction. An oscillatory motion may be applied to the source to reduce focal spot blur. Tomographic volumes are constructed that are capable of exhibiting super-resolution from data representing the acquired series of projection images taking the primary scan direction and the offsets into consideration.

Abstract: Methods and systems for determining a probabilistic assessment of a person developing cancer are disclosed. The probabilistic assessment may include receiving a digital breast image of a person, selecting a region of interest within the received breast image, and analyzing this selected region of interest with respect to texture analysis. A probabilistic assessment may then be determined through the use of a logistic regression model based on the texture analysis within the region of interest and personal risk factors. A probabilistic assessment may also be determined through the use of a linear regression model based on the texture analysis within the region of interest and a known cancer indicator or risk factor.

Abstract: Methods and systems for determining a probabilistic assessment of a person developing cancer are disclosed. The probabilistic assessment may include receiving a digital breast image of a person, selecting a region of interest within the received breast image, and analyzing this selected region of interest with respect to texture analysis. A probabilistic assessment may then be determined through the use of a logistic regression model based on the texture analysis within the region of interest and personal risk factors. A probabilistic assessment may also be determined through the use of a linear regression model based on the texture analysis within the region of interest and a known cancer indicator or risk factor.