This technology includes a method that extends fluorescence polarization imaging so that the dipole moment of a fluorescent dye may be excited regardless of its 3D orientation. By exciting the dipole from multiple directions, we ensure that excitation may occur even if the dipole is unfavorably oriented along the axial (propagation) axis. If the dye can be rigidly attached to the structure of interest, our method also enables the 3D orientation of the structure to be estimated accurately.

This technology includes an illuminator and reflector that enables flexible standing wave illumination on an inverted microscope stand, and procedures for using such illumination to improve axial resolution in confocal or instant SIM imaging systems. The axial resolution in conventional fluorescence microscopy is typically limited by diffraction to ~700 nm. This method that improves axial resolution ~7-fold over the diffraction limit, and that can be applied to any fluorescence microscope.

This technology includes algorithms and software that improve the speed of iterative deconvolution, a common method for improving spatial resolution and contrast in fluorescence microscopy images. These algorithms also improve the registration of multiview datasets, and apply deep learning to accelerate spatially varying deconvolution.

This technology includes a microscopy technique that produces super-resolution images from diffraction-limited images obtained from a line scanning confocal microscope. First, the operation of the confocal microscope is modified so that images with sparse line excitation are recorded. Second, these images are processed to increase resolution in one dimension. Third, by taking a series of such super-resolved images from a given sample type, a neural network may be trained to produce images with 1D super-resolution from new diffraction-limited images.

Nuclear medicine is the second largest source of medical radiation exposure to the general population after computed tomography imaging. Imaging modalities utilizing nuclear medicine produce a more detailed view of internal structure and function and are most commonly used to diagnose diseases such as heart disease, Alzheimer’s and brain disorders. They are used to visualize tumors, abscesses due to infection or abnormalities in abdominal organs.

About half of the per capita dose of radiation due to medical exposures is provided by computed tomography (CT) examinations. Approximately 80 million CTs are performed annually in the United States. CT scans most commonly look for internal bleeding or clots, abscesses due to infection, tumors and internal structures. Although CT provides great patient benefit, concerns exist about potential associated risks from radiation doses – especially in pediatric patients more sensitive to radiation.

The National Cancer Institute (NCI) seeks parties to license software for modeling the targeted delivery of anti-cancer agents in solid tumors.

The software models the permeability and concentration of intravenously administered antibody anti-cancer agent conjugates in solid tumors.  The models can be used to determine optimal dosing regimen of a therapeutic in a particular cancer type.  Thirty factors that affect delivery rates and efficiencies are analyzed as variables in generating the models.

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 combination of protein biomarkers and clinical risk factors to be used as an In Vitro Diagnostic Multivariate Index Assay (IVDMIA) that can improve the identification of individuals at high risk for atherosclerotic cardiovascular disease (ASCVD) and myocardial infarction (MI). Incorporation of novel protein biomarkers of ASCVD risk into risk assessment algorithms may improve their ability to identify individuals at high risk for ASCVD.