Abstract: A method for detecting blood-tissue barrier breakdown or disruption is provided. The method includes acquiring first image data of a target region of a subject with a predetermined spatial resolution; administrating exogenous or endogenous tracer into the subject; acquiring second image data of the target region with the predetermined spatial resolution after administration of the tracer; differentiating healthy tissue and pathological tissue with blood-tissue barrier breakdown in the target region based on the first image data and the second image data; and visualizing or analyzing the blood-tissue barrier breakdown of pathological tissue based on the differentiation.

Abstract: A method for spatial resolution enhanced imaging is provided. The method includes determining a target region of a subject being imaged; estimating an achievable spatial resolution; selecting an increased spatial resolution that is greater than a predetermined spatial resolution and equal to or less than the achievable spatial resolution; and acquiring image data of the target region with the increased spatial resolution. A method for enhancing the contrast between the region of interest and other tissue region in the image data acquired with the increased spatial resolution and other tissue region in image data acquired with the predetermined spatial resolution due to the intrinsic partial volume effect is also provided.

Abstract: A method or system for assessing a patient response to a cancer treatment is provided. The method or system includes acquiring at least one base-line radiological image related to a patient immediately before a treatment, acquiring at least one follow-up radiological image during or after the treatment at a predetermined time interval, estimating a first number of specific tumor cells in a region of interest of the patient based on image features of the base-line radiological image using an algorithm or a model, estimating a second number of specific tumor cells in the region of interest of the patient based on image features of the follow-up radiological image using the algorithm or the model, obtaining a difference between the first number of specific tumor cells and the second number of specific tumor cells, and classifying a treatment response to a cancer based on the difference.

Abstract: The present invention belongs to the medical field, and relates to novel ?-lactamase inhibitors, for the treatment of bacterial infections in combination with ?-lactam antibiotics, including infection caused by drug resistant organisms and especially multi-drug resistant organisms. The present invention includes compounds according to formula (I): or pharmaceutically acceptable salts thereof, wherein M and R are as defined herein.

Abstract: A method for motion correction of Magnetic Resonance (MR) images is provided. The method includes acquiring a k-space dataset for an object using an MR scanner, detecting or identifying corrupted k-space data from the acquired k-space dataset, extracting the corrupted k-space data from the acquired k-space dataset, recovering the corrupted k-space data, combining uncorrupted k-space data of the acquired k-space dataset with the recovered k-space data to form a full k-space dataset, and reconstructing an image for the object based on the full k-space dataset. A magnetic resonance imaging system for correcting corrupted k-space data of an entire k-space dataset is also provided.

Abstract: ?-lactamase inhibitors, pharmaceutical compositions including the same, methods of preparing the same, and methods of treating bacterial infections in combination with ?-lactam antibiotics, including infection caused by drug resistant organisms and especially multi-drug resistant organisms. The present invention includes compounds according to formula (I) or pharmaceutically acceptable salts thereof, wherein M and R are as defined herein.

Abstract: A method or system for assessing a patient response to a cancer treatment is provided. The method or system includes acquiring at least one base-line radiological image related to a patient immediately before a treatment, acquiring at least one follow-up radiological image during or after the treatment at a predetermined time interval, estimating a first number of specific tumor cells in a region of interest of the patient based on image features of the base-line radiological image using an algorithm or a model, estimating a second number of specific tumor cells in the region of interest of the patient based on image features of the follow-up radiological image using the algorithm or the model, obtaining a difference between the first number of specific tumor cells and the second number of specific tumor cells, and classifying a treatment response to a cancer based on the difference.

Abstract: A method for k-space registration is provided. The method of k-space registration includes receiving a first partial k-space dataset for an object and a second partial k-space dataset for the object, selecting the first partial k-space dataset as a reference, selecting feature for estimating a transformation matrix for transforming k-space data, estimating a transformation matrix based on the feature of entire or part of the first partial k-space dataset and the feature of the second partial k-space dataset corresponding to the entire or part of the first partial k-space dataset, correcting the second partial k-space dataset based on the transformation matrix, and obtaining the corrected second partial k-space dataset. The present method is further used for partial Fourier reconstruction.

Abstract: A monobactam compound of formula (I), a preparation thereof, and a use thereof as antibiotic agents for the treatment of bacterial infections are provided. In the formula (I), M is hydrogen or a pharmaceutically acceptable salt forming cation, R1 and R2 represent independently of one another hydrogen or methyl, W represents a bond or O, X represents CR4 or N, R4 represents halogen, R3 represents hydrogen, amino, hydroxy, (C1-C6)-alkyl, or a 4-, 5- or 6-membered nitrogen-containing heterocycle.

Abstract: Embodiments provide a deep learning framework to accurately segment liver and spleen using a convolutional neural network with both short and long residual connections to extract their radiomic and deep features from multiparametric MRI. Embodiments will provide an “ensemble” deep learning model to quantify biopsy derived liver fibrosis stage and percentage using the integration of multiparametric MRI radiomic and deep features, MRE data, as well as routinely available clinical data. Embodiments will provide a deep learning model to quantify MRE-derived liver stiffness using multiparametric MRI, radiomic and deep features and routinely-available clinical data.

Abstract: Provided are ?-lactam compounds of formula (I), their preparation and use as antibiotic agents for the treatment of bacterial infections: Wherein X, W, R1, R2 and R3 are defined herein.

Abstract: A method for spatial resolution enhanced imaging is provided. The method includes determining a target region of a subject being imaged; estimating an achievable spatial resolution; selecting an increased spatial resolution that is greater than a predetermined spatial resolution and equal to or less than the achievable spatial resolution; and acquiring image data of the target region with the increased spatial resolution. A method for enhancing the contrast between the region of interest and other tissue region in the image data acquired with the increased spatial resolution and other tissue region in image data acquired with the predetermined spatial resolution due to the intrinsic partial volume effect is also provided.

Abstract: A method and a system for measuring intra-site heterogeneity in a tumor using magnetic resonance imaging (MRI). The method includes acquiring magnetic resonance (MR) images using MRI modality; segmenting tumor sites in the MR images; dividing each of the tumor sites into a plurality of sub-regions; deriving image biomarkers from each voxel or pixel in the plurality of sub-regions; classifying each voxel or pixel in the plurality of sub-regions into genotypes or molecular subtypes based on the extracted image biomarkers and a classifier model including associations between image biomarkers and genotypes or molecule subtypes; creating a distribution of genotypes or molecular subtypes in the each of the plurality of sub-regions based on classifications of voxels or pixels; generating spatial information of genotypes or molecular subtypes in the tumor sites based on the distribution; and measuring intra-site heterogeneity in the tumor sites.

Abstract: Various embodiments disclosed relate to a substrate. The present disclosure provides a substrate for use in both surface enhanced Raman spectroscopy and surface enhanced infrared spectroscopy. The substrate includes a flexible polymeric membrane, a plurality of metal oxide nanoparticles disposed on the polymeric membrane, and a plurality of metallic nanoparticles directly disposed on a portion of the plurality of metal oxide nanoparticles. The plurality of metal oxide nanoparticles are configured to work synergistically with metal nanoparticles upon exposure of the substrate surface to at least one of visible light or infrared radiation.

Abstract: A system for objectively analyzing medical image data for the presence of diffuse white matter abnormalities (DWMA) is configured to identify and determine DWMA characteristics that are not visually apparent. As compared to subjective visual diagnosis, objectively determined DWMA characteristics may be automatically compared to each other, and may be compared to and associated with various scales, evaluations, or other assessment criteria used to measure aspects of infant development. As a result, the disclosed system may objectively determine an impact that objectively determined DWMA characteristics will have on one or more developmental scales, which can be expressed as a time deficit, score deficit, or other value indicative of development deficits.