Abstract: Systems, methods, and apparatus are provided for generating an atlas image of a branched structure and predicting a likelihood of success of certain treatments based on the atlas image. In one example, a method includes registering a plurality of images of instances of a branched structure to generate an aligned image for a cohort, wherein the branched structure comprises a central structure and at least one primary branch connected to the central structure; for each primary branch of the branched structure, iteratively registering respective portions of a plurality of images containing the primary branch to generate an aligned image portion of the primary branch; and applying a control grid of the aligned image portion of the primary branch to respective image portions containing the central structure and the other primary branches prior to iteratively registering a next primary branch; and generating an atlas image for the cohort based on the aligned image portions.

Abstract: Embodiments discussed herein facilitate determination of risk of recurrence of atrial fibrillation (AF) after ablation based on fractal features. One example embodiment is configured to generate a binary mask of at least a portion of a CT scan of a heart of a patient with AF; compute one or more radiomic fractal-based features from at least one of the binary mask or the portion of the CT scan; provide the one or more radiomic fractal-based features to a trained machine learning (ML) classifier; and receive a prediction from the trained ML classifier of whether or not the AF will recur after AF ablation, wherein the prediction is based at least in part on the one or more radiomic fractal-based features.

Abstract: Embodiments discussed herein facilitate determination of risk of recurrence of atrial fibrillation (AF) after ablation based on fractal features. One example embodiment is configured to generate a binary mask of at least a portion of a CT scan of a heart of a patient with AF; compute one or more radiomic fractal-based features from at least one of the binary mask or the portion of the CT scan; provide the one or more radiomic fractal-based features to a trained machine learning (ML) classifier; and receive a prediction from the trained ML classifier of whether or not the AF will recur after AF ablation, wherein the prediction is based at least in part on the one or more radiomic fractal-based features.

Abstract: Systems and methods to reduce or minimize air embolisms from catheterization and other interventional procedures. Systems and methods are provided that include a chamber that can be filled with saline and hemostatically clipped to or incorporated with an open proximal end of a sheath for under saline catheter insertion, exchange, flushing or other steps that involve inserting a catheter into a patient's body.