Hyperspectral three-dimensional absorption imaging using snapshot optical tomography.

Hyperspectral imaging (HSI) records a series of two-dimensional (2D) images for different wavelengths to provide the chemical fingerprint at each pixel. Combining HSI with a tomographic data acquisition method, we can obtain the chemical fingerprint of a sample at each point in three-dimensional (3D) space. The so-called 3D HSI typically suffers from low imaging throughput due to the requirement of scanning the wavelength and rotating the beam or sample.

DOAC compared with warfarin for VTE in patients with obesity: a retrospective cohort study conducted through the VENUS network.

The effectiveness and safety of direct oral anticoagulants (DOAC) compared with warfarin remains uncertain in obese patients. We assessed the comparative effectiveness and safety of DOACs with warfarin for the treatment of VTE among obese patients. This multi-center retrospective cohort study included adults with a BMI ≥ 35 kg/m or weight ≥ 120 kg prescribed either DOAC (apixaban, dabigatran, edoxaban, rivaroxaban) or warfarin for a VTE diagnosis.

Synoptic reporting accuracy for computed tomography pulmonary arteriography among patients suspected of pulmonary embolism.

Background: Structured reporting is an efficient and replicable method of presenting diagnostic results that eliminates variability inherent in narrative descriptive reporting and may improve clinical decisions. Synoptic element reporting can generate discrete coded data that then may inform clinical decision support and trigger downstream actions in computerized electronic health records.

Objective: Limited evidence exists for use of synoptic reporting for computed tomography pulmonary arteriography (CTPA) among patients suspected of pulmonary embolism.

Deep-learning-assisted Fourier transform imaging spectroscopy for hyperspectral fluorescence imaging.

Hyperspectral fluorescence imaging is widely used when multiple fluorescent probes with close emission peaks are required. In particular, Fourier transform imaging spectroscopy (FTIS) provides unrivaled spectral resolution; however, the imaging throughput is very low due to the amount of interferogram sampling required. In this work, we apply deep learning to FTIS and show that the interferogram sampling can be drastically reduced by an order of magnitude without noticeable degradation in the image quality.