Abstract: A system for PET image reconstruction is provided. The system may obtain PET data of a subject. The PET data may be associated with a plurality of coincidence events, which includes scattering events. The system may also generate a preliminary scatter sinogram relating to the scattering events based on the PET data. The system may also generate a target scatter sinogram relating to the scattering events by applying a scatter sinogram generator based on the preliminary scatter sinogram. The target scatter sinogram may have a higher image quality than the preliminary scatter sinogram. The system may further reconstruct a target PET image of the subject based on the PET data and the target scatter sinogram.

Abstract: A framework for cross-modality image synthesis. A first and second model may be trained using respective first and second pairs of complementary images and corresponding first and second ground truth images that represent first and second views of a region of interest. The first and second pairs of complementary images may be acquired by a first modality and the first and second ground truth images may be acquired by a second modality. A combinational network may further be trained to combine features from the first and second models. At least one synthetic second modality image may then be generated by passing current images through the trained first or second model and the combinational network, wherein the current images are acquired by the first modality and represent the first or second view of the region of interest.

Abstract: A method for magnetic resonance imaging may include acquiring first k-space data that is generated by entering acquired magnetic resonance (MR) data into a plurality of first k-space locations. The method may further include synthesizing second k-space data for a plurality of second k-space locations that are not filled with the acquired MR data. The method may further include reconstructing an image from the first k-space data and the second k-space data by applying a reconstruction algorithm. The reconstruction algorithm is based at least in part on a neural network technique.

Abstract: A vacuum system for film lamination, including a vacuum chamber module, a film-pressing module, a substrate susceptor module and a hot-plate heating module, is disclosed, wherein the film-pressing module includes a film-pressing platen, and the substrate susceptor module includes a substrate susceptor supported by a spring-loaded mechanism. During a film-lamination process, the film-pressing platen is actuated to move downwards to attach a laminating film onto a substrate, and the substrate susceptor is actuated to move downwards and finally rest on the hot-plate heating module. Therefore an adhesive glue disposed between the laminating film and the substrate can be thermally cured. After completing the film-lamination process, the film-pressing platen is actuated upwards so that the substrate susceptor also is actuated to move upwards to its initial position by a restoring force exerted by the spring-loaded mechanism.

Abstract: The present disclosure is related to systems and methods for image processing. The method includes obtaining a first image of a first modality. The method includes generating a second image of a second modality by processing, based on a trained machine learning model, the first image. The second modality may be different from the first modality.

Abstract: A method for magnetic resonance imaging may include acquiring first k-space data that is generated by entering acquired magnetic resonance (MR) data into a plurality of first k-space locations. The method may further include synthesizing second k-space data for a plurality of second k-space locations that are not filled with the acquired MR data. The method may further include reconstructing an image from the first k-space data and the second k-space data by applying a reconstruction algorithm. The reconstruction algorithm is based at least in part on a neural network technique.

Abstract: A method and system are for identification of at least one medical reference image. An embodiment of the method includes providing a medical representation image based on a current examination image depicting a body part of a first patient; defining a region of interest in the medical representation image; generating a feature signature, at least for the region of interest; comparing the medical representation image with a plurality of medical images of at least one second patient stored in a medical image database, based on the feature signature generated; and identifying at least one medical image in the medical image database as the at least one medical reference image, the at least one medical reference image providing a similarity degree to the medical representation image above a threshold. In an embodiment, the generating is performed using a trained machine-learning algorithm.

Abstract: A framework for cross-modality image synthesis. A first and second model may be trained using respective first and second pairs of complementary images and corresponding first and second ground truth images that represent first and second views of a region of interest. The first and second pairs of complementary images may be acquired by a first modality and the first and second ground truth images may be acquired by a second modality. A combinational network may further be trained to combine features from the first and second models. At least one synthetic second modality image may then be generated by passing current images through the trained first or second model and the combinational network, wherein the current images are acquired by the first modality and represent the first or second view of the region of interest.

Abstract: A framework for pedicle screw positioning is described herein. In accordance with one aspect, the framework segments at least one vertebra of interest in image data. The framework then automatically determines a pedicle region within the segmented vertebra of interest, and a safe region within the segmented vertebra of interest. An optimal insertion path passing through the pedicle region may then be generated within the safe region.

Abstract: The present disclosure is related to systems and methods for image processing. The method may include obtaining a first set of image data. The method may also include generating a second set of image data by processing, based on a trained machine learning model, the first set of image data. The second set of image data may have a relatively high resolution and/or a relatively low level of artifacts with respect to the first set of image data. The method may further include generating a target image by performing a weighted fusion on the first set of image data and the second set of image data.

Abstract: A framework for automatic retrieval of medical images. In accordance with one aspect, the framework detects patches in a query image volume that contain at least a portion of an anatomical region of interest by using a first trained classifier. The framework determines disease probabilities by applying a second trained classifier to the detected patches, and selects, from the patches, a sub-set of informative patches with disease probabilities above a pre-determined threshold value. For a given patch from the sub-set of informative patches, the framework retrieves, from a database, patches that are most similar to the given image. Image volumes associated with the retrieved patches are then retrieved from the database. A report based on the retrieved image volumes may then be generated and presented.

Abstract: A vacuum system for film lamination, including a vacuum chamber module, a film-pressing module, a substrate susceptor module and a hot-plate heating module, is disclosed, wherein the film-pressing module includes a film-pressing platen, and the substrate susceptor module includes a substrate susceptor supported by a spring-loaded mechanism. During a film-lamination process, the film-pressing platen is actuated to move downwards to attach a laminating film onto a substrate, and the substrate susceptor is actuated to move downwards and finally rest on the hot-plate heating module. Therefore an adhesive glue disposed between the laminating film and the substrate can be thermally cured. After completing the film-lamination process, the film-pressing platen is actuated upwards so that the substrate susceptor also is actuated to move upwards to its initial position by a restoring force exerted by the spring-loaded mechanism.

Abstract: A framework for automatic retrieval of medical images. In accordance with one aspect, the framework detects patches in a query image volume that contain at least a portion of an anatomical region of interest by using a first trained classifier. The framework determines disease probabilities by applying a second trained classifier to the detected patches, and selects, from the patches, a sub-set of informative patches with disease probabilities above a pre-determined threshold value. For a given patch from the sub-set of informative patches, the framework retrieves, from a database, patches that are most similar to the given image. Image volumes associated with the retrieved patches are then retrieved from the database. A report based on the retrieved image volumes may then be generated and presented.

Abstract: A framework for pedicle screw positioning is described herein. In accordance with one aspect, the framework segments at least one vertebra of interest in image data. The framework then automatically determines a pedicle region within the segmented vertebra of interest, and a safe region within the segmented vertebra of interest. An optimal insertion path passing through the pedicle region may then be generated within the safe region.

Abstract: Disclosed herein is a framework for facilitating automatic planning for medical imaging. In accordance with one aspect, the framework receives first image data of a subject. One or more imaging parameters may then be derived using a geometric model and at least one reference anatomical primitive detected in the first image data. The geometric model defines a geometric relationship between the detected reference anatomical primitive and the one or more imaging parameters. The one or more imaging parameters may be presented, via a user interface, for use in acquisition, reconstruction or processing of second image data of the subject.

Abstract: A framework for patient management based on anatomic measurements is described herein. In accordance with one aspect, patient records are clustered into a set of sub-populations based on first anatomic measurements and characteristics extracted from first patient data associated with a population of patients. A representative sub-population similar to a patient may be determined from the set of sub-populations based on the patient data of the patient. A report that presents the second anatomic measurements associated with the patient in relation to corresponding first anatomic measurements associated with the representative sub-population may then be generated.

Abstract: Disclosed herein is a framework for segmenting articulated structures. In accordance with one aspect, the framework receives a target image, a reference image, statistical shape models, local appearance models and a learned landmark detector. The framework may automatically detect first centerline landmarks along centerlines of articulated structures in the target image using the learned landmark detector. The framework may then determine a non-rigid transformation function that registers second centerline landmarks along centerlines of articulated structures in the reference image with the first centerline landmarks. Mean shapes of the statistical shape models may then be deformed to the target image space by applying the non-rigid transformation function on the mean shapes. The framework may further search for candidate points in the mean shapes using the local appearance models. The mean shapes may be fitted to the candidate points to generate a segmentation mask.

Abstract: Disclosed herein is a framework for facilitating automatic planning for medical imaging. In accordance with one aspect, the framework receives first image data of a subject. One or more imaging parameters may then be derived using a geometric model and at least one reference anatomical primitive detected in the first image data. The geometric model defines a geometric relationship between the detected reference anatomical primitive and the one or more imaging parameters. The one or more imaging parameters may be presented, via a user interface, for use in acquisition, reconstruction or processing of second image data of the subject.

Abstract: Disclosed herein is a framework for segmenting articulated structures. In accordance with one aspect, the framework receives a target image, a reference image, statistical shape models, local appearance models and a learned landmark detector. The framework may automatically detect first centerline landmarks along centerlines of articulated structures in the target image using the learned landmark detector. The framework may then determine a non-rigid transformation function that registers second centerline landmarks along centerlines of articulated structures in the reference image with the first centerline landmarks. Mean shapes of the statistical shape models may then be deformed to the target image space by applying the non-rigid transformation function on the mean shapes. The framework may further search for candidate points in the mean shapes using the local appearance models. The mean shapes may be fitted to the candidate points to generate a segmentation mask.

Abstract: A motion platform having decoupled two axes adopts four modularized pneumatic bellows configured in an orthogonal arrangement. The pneumatic bellows can be independently controlled to cause the motion platform to be operated in one rotational degree of freedom with a frontward-and-backward swinging or a leftward-and-rightward swinging; or the pneumatic bellows can be synchronously controlled to cause the motion platform operated in two rotational degrees of freedom without being interfered with each other. Thus, the motion platform of the present disclosure is characterized with advantages of simplified mechanism, fewer components, convenient maintenance and reduced cost.