Some embodiments are directed to a method of estimating a velocity of a contrast agent. The method includes receiving a plurality of video frames that were produced using a dynamic contrast enhanced imaging process, each video frame including a plurality of pixels/voxels. Information from the video frames is used to estimate velocity vectors indicating the velocity and direction of the agent with the vascular networks. The estimated velocity can be used to diagnose cancer, such as prostate cancer. Instead of velocity vectors, agent trajectories can be determined also used for the same purpose.

A method includes obtaining image data, selecting image datasets from the image data, creating three-dimensional (3D) matrices based on the selected image dataset, refining the 3D matrices, applying one or more matrix operations to the refined 3D matrices, selecting corresponding matrix columns from the 3D matrices, applying big data convolution algorithm to the selected corresponding matrix columns to create a two-dimensional (2D) matrix, and applying a reconstruction algorithm to create a super-resolution biomarker map image.

The present disclosure relates to systems and methods for determining quantitative chemical exchange or exchangeable proton information from a region-of-interest in a subject. The methods and systems use adaptive fitting to quantify magnetic resonance (MR) data, such as chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) images, using initial values based on, for example, Lorentzian fitting. Images are iteratively less downsampled until quantitative maps of desired resolution are obtained. Such an approach allows for reliable fitting at a faster fitting speed, and is less susceptible to suboptimal signal to noise (SNR) than conventional methods.

A method includes receiving a plurality of voxel values corresponding to respective locations in a heart, which are acquired using magnetic resonance imaging (MRI). Voxel values that, in spite of (i) corresponding to a same location in the heart and (ii) being gated to a same phase of an electrocardiogram (ECG) cycle of the heart, differ by more than a predefined difference, are identified. An image of at least a portion of the heart is reconstructed from the plurality of voxel values excluding at least the identified voxel values.

Some embodiments are directed to a method of estimating a velocity of a contrast agent. The method includes receiving a plurality of video frames that were produced using a dynamic contrast enhanced imaging process, each video frame including a plurality of pixels/voxels. Information from the video frames is used to estimate velocity vectors indicating the velocity and direction of the agent with the vascular networks. The estimated velocity can be used to diagnose cancer, such as prostate cancer. Instead of velocity vectors, agent trajectories can be determined also used for the same purpose.

A dynamic analysis apparatus includes: an obtainment unit configured to set a region of interest in dynamic images obtained by photographing a dynamic state by irradiation of a check target part with radial rays, and obtain movement information on movement of the region of interest; a determination unit configured to determine an emphasis level of a pixel signal value of an attentional pixel corresponding to a pixel in the region of interest on the basis of the movement information of the region of interest obtained by the obtainment unit; and a correction unit configured to correct the pixel signal value of the attentional pixel of the dynamic images or analysis result images generated by analyzing the dynamic images, on the basis of the emphasis level determined by the determination unit.

A system and method for automated characterization of solid tumors using medical imaging. The system comprises an interface that is configured to acquire data from medical imaging devices, one or more processors, and an outputting device that reports the characterization of said solid tumor. The method of automated characterization, which is implemented by the system, acquires a sequence of images from the medical imager using a Dynamic Contrast Enhanced (DCE) imaging protocol, performs image registration, detects the contour of the solid tumor, and dividing the contours to segments. For each segment, the method calculating a displacement of the contrast material, fitting the displacement to a flow model and extracting an estimation of the interstitial fluid velocity. The estimated interstitial fluid velocity of the segments provide characterization of the solid tumor and includes an assessment of the tumor interstitial fluid pressure, the tumor drug delivery efficiency, and the tumor prognostic or metastasis risk.

A method includes receiving a plurality of voxel values corresponding to respective locations in a heart, which are acquired using magnetic resonance imaging (MRI). Voxel values that, in spite of (i) corresponding to a same location in the heart and (ii) being gated to a same phase of an electrocardiogram (ECG) cycle of the heart, differ by more than a predefined difference, are identified. An image of at least a portion of the heart is reconstructed from the plurality of voxel values excluding at least the identified voxel values.

This invention provides a system and method for fusing and synthesizing a plurality of medical images defined by a plurality of imaging parameters allowing visual enhancements of each image data set to be combined. The system provides an image fusion process/processor that fuses a plurality of magnetic resonance imaging datasets. A first image dataset of the datasets is defined by apparent diffusion coefficient (ADC) values. A second image dataset of the MRI datasets is defined by at least one parameter other than the ADC values. The image fusion processor generates a fused response image that visually displays a combination of image features generated by the ADC values combined with image features generated by the at least one parameter other than the ADC values. The fused response image can illustratively include at least one of color-enhanced regions of interest and intensity-enhanced regions of interest.

A method for detecting an indication of likelihood of malignancy, comprising: receiving a sequence of anatomical images of a breast of a target individual acquired over a time interval during which contrast is administered, analyzing the sequence of anatomical images to identify: a baseline pre-contrast image denoting lack of contrast, a peak contrast image denoting a peak contrast enhancement, an initial uptake image denoting initial contrast enhancement, and a delayed response image denoting final contrast enhancement, creating a multi-channel image representation comprising: intensity channel including the peak contrast enhanced image, contrast-update channel including the computed difference between the peak contrast enhanced image and the pre-contrast image, and contrast-washout channel including the computed difference between the initial uptake image and the delayed response image, and computing by a trained deep convolutional neural network, a classification category indicative of likelihood of malignancy for the sequence according to the multi-channel image representation.