Inference of appropriate anatomical region from inconsistent descriptions in order to provide fast and accurate prefetching is provided. In various embodiments, an anatomical region of a first medical imaging study is determined. A first plurality of keywords is determined corresponding to the anatomical region of the first medical imaging study. A plurality of studies is accessed having a patient in common with the first medical imaging study. A second plurality of keywords is extracted from the plurality of studies. Those of the plurality of studies having extracted keywords in common with the first plurality of keywords are selected. The selected studies are pre-fetched for display to a user.

Electrical impedance tomography devices and systems having a multi-dimensional electrode arrangement are disclosed including a related method for operating the devices and systems. The reconstructed images may correspond to the planes of the multi-dimensional electrode arrangements as well as one or more images corresponding to a region outside of the electrode planes. Such reconstruction may be performed by application of a finite element mesh having multiple layers defined for the different regions for generating the images.

Provided are a method and apparatus for adjusting blood flow velocity in maximum hyperemia state based on index for microcirculatory resistance. The method comprises: acquiring an index for microcirculatory resistance iFMR during a diastolic phase according to a blood flow velocity v, an aortic pressure waveform, and an physiological parameter (S100); making an adjustment parameter r equal to 1 if the index for microcirculatory resistance iFMR during the diastolic phase is less than K; making the adjustment parameter r satisfy a formula r=1−(iFMR−K)/100 if the index for microcirculatory resistance iFMR during the diastolic phase is greater than or equal to K, wherein K is a positive number less than 100 (S200); acquiring a corrected blood flow velocity in a maximum hyperemia state according to a product of the adjustment parameter and a blood flow velocity in the maximum hyperemia state (S300).

The present invention relates to devices and methods of use thereof for real time blood flow measurements of skin. In one embodiment, the device is a compact laser speckle imaging, or LSI, system that is integrated with a dermatoscope. In another embodiment, the device allows the user to diagnose a disease or condition in an individual, or as part of an overall treatment regimen.

A method and system for creating a dynamic self-learning medical image network system, wherein the method includes receiving, from a first node initial user interaction data pertaining to one or more user interactions with the one or more initially obtained medical images; training a deep learning algorithm based at least in part on the initial user interaction data received from the node; and transmitting an instance of the trained deep learning algorithm to the first node and/or to one or more additional nodes, wherein at each respective node to which the instance of the trained deep learning algorithm is transmitted, the trained deep learning algorithm is applied to respective one or more subsequently obtained medical images in order to obtain a result.

Systems and methods are provided for improving MRI data acquisition efficiency while providing more detailed information with high resolution and isotropic resolution without gaps. Improved data acquisition efficiency may be achieved by implementing a machine learning algorithm with a hardware processor and a memory to estimate imperfections in fast imaging sequences, such as a multi-shot echo planar imaging (MS-EPI) sequence. These imperfections, such as patient motion, physiological noise, and phase variations, may be difficult to model or otherwise estimate using standard physics-based reconstructions.

A method and system for fast non-invasive computer-based computation of a hemodynamic index, such as fractional flow reserve (FFR) from medical image data of a patient is disclosed. A patient-specific anatomical model of one or more arteries of a patient is automatically generated based on medical image data of the patient. Regions in the automatically generated patient-specific anatomical model for which user feedback is required for accurate computation of a hemodynamic index are predicted using one or more trained machine learning models.

An apparatus and method are provided to simultaneously provide good image quality and fast image reconstruction from magnetic resonance imaging (MRI) data by selecting an appropriate value for the regularization parameter used in compressed sensing (CS) image reconstruction. In CS reconstruction a high-resolution image can be reconstructed from randomized undersampled data by imposing sparsity in multi-scale transformation (e.g., wavelet) domain. Further, in the transformation domain, a threshold can be determined between signal and noise levels of the transform coefficients. A regularization parameter based on this threshold scales the regularization term, which imposes sparsity, relative to the data fidelity term in an objective function, thereby balancing the tradeoff between noise and smoothing.

There is provided herein a system and a method for an insertion device positioning guidance system comprising: an electromagnetic field generator configured to generate an electromagnetic field covering a treatment area; a reference sensor configured to be positioned, within the treatment area, on the subject's torso, the reference sensor is configured to define a reference coordinate system representing the position and orientation of the subject's torso relative to the field generator; a registration sensor configured to mark at least a first and a second anatomic locations relative to the reference coordinate system; and a processor configured to operate the field generator, read signals obtained from the reference sensor and the registration sensor, calculate a position and orientation thereof relative to the field generator, generate a 3D anatomic map representing the torso of the subject and the first and second anatomic locations, the processor is further configured to facilitate visualization on the 3D anatomic map of a position, orientation and/or path of a tip sensor, located in a distal tip section of the insertion device, with respect to the first and second anatomic locations, independent of the subject's movement and independent of deviations in the position and/or orientation of the field generator, thus determination of a successful medical procedure is facilitated.

There is provided herein a guidance system for positioning an insertion device comprising: an electromagnetic field generator configured to generate an electromagnetic field covering a treatment area, an insertion device comprising an electromagnetic sensor, the electromagnetic sensor configured to receive signals indicative of the electromagnetic field, and a processing circuitry configured to: load an X-ray, CT, ultrasound or MRI image of the subject's chest, mark a location of a first and a second anatomic landmarks on the subject's torso using a registration sensor and obtaining a subject coordinate system based thereon, identify the location of the first and the second anatomic landmarks on the loaded X-ray, CT, ultrasound or MRI image of the subject's chest; aligning the subject coordinate system with the loaded X-ray, CT, ultrasound or MRI image, and display, on the image, a path of the insertion device insertion with respect to the first and the second anatomic locations; wherein the path is generated according to changes in the strength of the electromagnetic field sensed by the tip sensor's during the insertion of the insertion device.