Abstract: Systems and methods providing enhancements to quantitative imaging systems and techniques are described herein. In one aspect, a system for tissue quantification in magnetic resonance fingerprinting (MRF) comprises a feature extraction module operable to convert pixel input high-dimensional signal evolution in to a low-dimensional feature map. The system also comprises a spatially constrained quantification module operable to capture spatial information from the low-dimensional feature map and generate an estimated tissue property map.

Abstract: Systems and methods for estimating a patient-specific reference bone shape model for a patient with craniomaxillofacial (CMF) defects are described herein. An example method includes receiving a twodimensional (“2D”) pre-trauma image of a subject, and generating a three-dimensional (“3D”) facial surface model for the subject from the 2D pre-trauma image. The method also includes providing a correlation model between 3D facial and bone surfaces, and estimating a reference bone model for the subject using the 3D facial surface model and the correlation model.

Abstract: A method for smart image protocoling includes, using a medical imaging device, obtaining, using a first medical imaging sequence, a first set of medical images of a patient. Anatomical and, if present, disease features are extracted from the first set of medical images. A machine learning trained algorithm is used to determine, in real time, and based on the extracted anatomical and/or disease features, whether a desired medical imaging goal is achieved for the patient. In response to determining that the desired medical imaging goal is achieved, at least one image from the first set of medical images is output as a final image. In response to determining that the desired medical imaging goal has not been achieved, the machine learning trained algorithm is used to select a second medical imaging sequence. A second set of medical images of the patient is obtained using the second medical imaging sequence. The above outlined procedures will be repeated until the final imaging goal is achieved for a patient.

Abstract: A method for smart image protocoling includes, using a medical imaging device, obtaining, using a first medical imaging sequence, a first set of medical images of a patient. Anatomical and, if present, disease features are extracted from the first set of medical images. A machine learning trained algorithm is used to determine, in real time, and based on the extracted anatomical and/or disease features, whether a desired medical imaging goal is achieved for the patient. In response to determining that the desired medical imaging goal is achieved, at least one image from the first set of medical images is output as a final image. In response to determining that the desired medical imaging goal has not been achieved, the machine learning trained algorithm is used to select a second medical imaging sequence. A second set of medical images of the patient is obtained using the second medical imaging sequence. The above outlined procedures will be repeated until the final imaging goal is achieved for a patient.

Abstract: Systems and method are provided for registering medical images to reduce movement between the images. In one arrangement, a hierarchical image registration is performed where regions of the largest differences between images are identified and utilized to drive the deformation of one of the images. Such regions are identified in one arrangement by determining intensities and gradient magnitudes for corresponding regions of the images. In another arrangement, a multi-resolution registration strategy is applied.

Abstract: A method of atlas mapping and an apparatus for image mapping are provided. The method includes generating a four dimensional template, linearly transforming the four dimensional representation of a subject to the four dimensional template, generating attribute vectors for a plurality of points of the linearly transformed four dimensional representation of the subject and of the four dimensional template, the plurality of points consisting of a plurality of temporally successive voxels of the four dimensional representation of the subject and of the four dimensional template, evaluating the generated attribute vectors to identify points in the four dimensional template that correspond to the four dimensional representation of the subject, and deforming the four dimensional template to the four dimensional representation of the subject according to relative positions of the corresponding points of the linearly transformed four dimensional representation of the subject and of the four dimensional template.

Abstract: Systems and method are provided for registering medical images to reduce movement between the images. In one arrangement, a hierarchical image registration is performed where regions of the largest differences between images are identified and utilized to drive the deformation of one of the images. Such regions are identified in one arrangement by determining intensities and gradient magnitudes for corresponding regions of the images. In another arrangement, a multi-resolution registration strategy is applied.

Abstract: A method of atlas mapping and an apparatus for image mapping are provided. The method includes generating a four dimensional template, linearly transforming the four dimensional representation of a subject to the four dimensional template, generating attribute vectors for a plurality of points of the linearly transformed four dimensional representation of the subject and of the four dimensional template, the plurality of points consisting of a plurality of temporally successive voxels of the four dimensional representation of the subject and of the four dimensional template, evaluating the generated attribute vectors to identify points in the four dimensional template that correspond to the four dimensional representation of the subject, and deforming the four dimensional template to the four dimensional representation of the subject according to relative positions of the corresponding points of the linearly transformed four dimensional representation of the subject and of the four dimensional template.