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Cancer diagnosis is based on the assessment of patient biopsies to determine the tumor type, grade, and stage of malignancy. The proliferative potential of tumors correlates to their growth and metastasis. Visually identifying and quantifying mitotic figures (MF) in cancer biopsy tissue can be used as a surrogate for proliferative activity in tumors.

Cancer diagnosis depends on the assessment of patient biopsies to determine tumor type, grading, and stage of malignancy. Pathologists visually review specimens and count mitotic figures (MF) in a variety of cancer types to help gauge aggressiveness, guide treatment, and inform patient prognosis. Current technology for recording MF counts in surgical pathology is lacking in objectivity, and enumeration of MF by microscopy can be error prone. In particular, a lack of systematic means for recording contributes to recognized variability.

This technology includes a method for performing cardiac imaging without the need for the patient to hold their breath. Free breathing pixel-wise myocardial T1 parameter mapping includes performing a free-breathing scan of a cardiac region at a plurality of varying saturation recovery times to acquire a k-space dataset; generating an image dataset based on the k-space dataset; and performing a respiratory motion correction process on the image dataset.

This technology includes a fully automatic 3D image processing system to segment the heart as well as other organs from contrast-enhanced cardiac computed tomography (CCT) images. Our method detects four cardiac chambers including left ventricle, right ventricle, left atrium, right atrium, as well as the ascending aorta and left ventricular myocardium. It also classifies noncardiac tissue structures in the CCT images such as lung, chest wall, spine, descending aorta, and liver.

This technology includes a computer-implemented method for determining magnetic field inversion time of a tissue species using a T1-mapping image, information about the region of interest, and a tissue classification algorithm. This method includes T1-mapping image comprising a plurality of T1 values within an expected range of T1 values for the tissue of interest. An image mask is created based on predetermined identification information about the tissue of interest. Next, an updated image mask is created based on a largest connected region in the image mask.

This technology includes a method to reduce scanning time while retaining high image quality during MRI scans. A reconstructed image is rendered from a set of MRI data by first estimating an image with an area which does not contain artifacts or has an artifact with a relatively small magnitude. Corresponding data elements in the estimated image and a trial image are processed, for instance by multiplication, to generate an intermediate data set.

This technology includes a novel Principal Component Analysis (PCA) based approach to correct motion related B0 changes in PRF thermometry. Proton Resonance Frequency (PRF) thermometry is a widely used Magnetic Resonance Imaging (MRI) based technique to monitor changes in tissue temperature in response to thermal therapy. The use of PRF thermometry with thermal therapy procedures is indispensable to ensure delivery of desired thermal dose to the target tissue, and to minimize unintended damage to the normal tissue.

This technology includes the incorporation of a magnetic field gradient waveform (consisting of two or more pulses) between excitation and encoding to eliminate signal from moving fluid for imaging applications. Proton Resonance Frequency (PRF) thermometry is a widely used Magnetic Resonance Imaging (MRI) based technique to monitor changes in tissue temperature in response to thermal therapy. The use of PRF thermometry with thermal therapy procedures is indispensable to ensure delivery of desired thermal dose to the target tissue, and to minimize unintended damage to the normal tissue.

This technology includes the determination of temperature dependent temporal deviations of the real from the intended gradient waveforms and k-space trajectories during MRI image acquisition, and the use of appropriate temperature dependent pre-compensations to avoid or reduce the image distortion caused by these temporal deviations on the gradient waveforms and k-space trajectories, which will improve imaging quality.

This technology includes a method of correcting the motion during T1 mapping using cardiovascular magnetic resonance imaging (MRI). Ischemic heart disease is the leading cause of death in the United States. The lack of blood supply among myocardial tissue, especially for scar regions, changes the T1 relaxation value of heart muscles. The non-invasive quantification of T1 value of myocardium (T1 mapping) is therefore of great importance for the diagnosis and treatment of cardiovascular disease.