Systems and methods are configured to identify underlying governing equations and/or parameters from analyzed medical imaging data and to form a treatment plan for a patient, modify a treatment plan, and/or treat the patient pursuant to a treatment plan. The type of data that is analyzed can vary and is described herein in an example context of identifying equations governing interstitial fluid transport in tissues from contrast-based medical imaging data, including, but not limited to, Gadolinium-based magnetic resonance imaging (MRI), Iodine-based computed tomography (CT), Iodine-based fluoroscopy, radioisotope-based single photon emission computed tomography (SPECT), dynamic contrast-enhanced MRI (DCE-MRI) or radioisotope-based positron emission tomography (PET.)

Embodiments include systems and methods for determining cardiovascular information for a patient. A method includes receiving patient-specific data regarding a geometry of the patient's vasculature; creating an anatomic model representing at least a portion of the patient's vasculature based on the patient-specific data; and creating a computational model of a blood flow characteristic based on the anatomic model. The method also includes identifying one or more of an uncertain parameter, an uncertain clinical variable, and an uncertain geometry; modifying a probability model based on one or more of the identified uncertain parameter, uncertain clinical variable, or uncertain geometry; determining a blood flow characteristic within the patient's vasculature based on the anatomic model and the computational model of the blood flow characteristic of the patient's vasculature; and calculating, based on the probability model and the determined blood flow characteristic, a sensitivity of the determined fractional flow reserve to one or more of the identified uncertain parameter, uncertain clinical variable, or uncertain geometry.

An information processing device according to an embodiment includes a processing circuit. The processing circuit generates second data that is a data array classified by basis information by performing transform processing on first data, generates third data including a plurality of pieces of data by performing segmentation processing on the second data classified by the basis information, and generates fourth data by combining the pieces of data in the third data.

Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.

According to embodiment, an image processing apparatus comprising a specifying unit and a display controller. The specifying unit that specifies an acquisition position of an indicator relating to blood flow on a blood vessel-containing image collected by a medical image diagnostic apparatus. The display controller that displays the acquisition position on the blood vessel-containing image and displays the indicator on a display unit in association with the acquisition position.

A correlation matrix calculation unit calculates a correlation matrix R.sub.zx for each data element of the frame data. A blood flow luminance image forming unit forms a blood flow extraction filter P.sub.k,N on the basis of an eigenvalue .sub.i of a rank equal to or lower than a first threshold rank, the eigenvalue being obtained by singular value decomposition on the correlation matrix R.sub.zx, and an eigenvector w.sub.i, w.sub.i.sup.H corresponding to the eigenvalue i and applies the blood flow extraction filter P.sub.k,N to frame data F, therebyto forming a blood flow luminance image U.sub.k,N. A tissue image forming unit forms a tissue image including tissue components on the basis of a signal value of each data element forming the plurality of pieces of the frame data. A blood flow extraction image forming unit subtracts the tissue image from the blood flow luminance image U.sub.k, N, thereby forming a blood flow extraction image U.sub.out.

Systems and methods are disclosed for predicting coronary plaque vulnerability, using a computer system. One method includes acquiring anatomical image data of at least part of the patient's vascular system; performing, using a processor, one or more image characteristics analysis, geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis on the anatomical image data; predicting, using the processor, a coronary plaque vulnerability present in the patient's vascular system, wherein predicting the coronary plaque vulnerability includes calculating an adverse plaque characteristic based on results of the one or more of image characteristics analysis, geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis of the anatomical image data; and reporting, using the processor, the calculated adverse plaque characteristic.

Systems and methods are disclosed for performing probabilistic segmentation in anatomical image analysis, using a computer system. One method includes receiving a plurality of images of an anatomical structure; receiving one or more geometric labels of the anatomical structure; generating a parametrized representation of the anatomical structure based on the one or more geometric labels and the received plurality of images; mapping a region of the parameterized representation to a geometric parameter of the anatomical structure; receiving an image of a patient's anatomy; and generating a probability distribution for a patient-specific segmentation boundary of the patient's anatomy, based on the mapping of the region of the parameterized representation of the anatomical structure to the geometric parameter of the anatomical structure.

A method, performed by at least one processor, for calculating a ratio of blood-flow volumes by vessel using a vascular image, includes acquiring at least one vascular image, classifying, in the at least one vascular image, a plurality of vessels, extracting geometric information of each of the plurality of vessels from the at least one vascular image, and calculating a ratio of blood-flow volumes by vessel based on a value extracted as the geometric information of each of the plurality of vessels and a reference value for the geometric information of each of the plurality of vessels, wherein the reference value are set based on values calculated from a plurality of subjects.

Provided is a super-resolution ultrasonic imaging method and an ultrasonic imaging system. A first contrast enhanced image is generated and displayed in real time under a normal contrast enhanced mode. It is switched from the normal contrast enhanced mode to a super-resolution contrast enhanced imaging mode. Second ultrasonic echo signals are obtained to generate and display a second contrast enhanced image. Super-resolution data processing is performed on the second ultrasonic echo signals to obtain a super-resolution image when displaying the second contrast enhanced image. The super-resolution image is displayed.