Although it is often disappointing when LSG leaks do occur, with adherence to the basic tenets of the surgical management of enterocutaneous fistulae as well as early detection and a high index of suspicion, these complications can be successfully managed using an algorithm-based multi-disciplinary team approach.

No abstract

In medical imaging, outliers can contain hypo/hyper-intensities, minor deformations, or completely altered anatomy. To detect these irregularities it is helpful to learn the features present in both normal and abnormal images. However this is difficult because of the wide range of possible abnormalities and also the number of ways that normal anatomy can vary naturally. As such, we leverage the natural variations in normal anatomy to create a range of synthetic abnormalities. Specifically, the same patch region is extracted from two independent samples and replaced with an interpolation between both patches. The interpolation factor, patch size, and patch location are randomly sampled from uniform distributions. A wide residual encoder decoder is trained to give a pixel-wise prediction of the patch and its interpolation factor. This encourages the network to learn what features to expect normally and to identify where foreign patterns have been introduced. The estimate of the interpolation factor lends itself nicely to the derivation of an outlier score. Meanwhile the pixel-wise output allows for pixel-and subject-level predictions using the same model.

No abstract

The PCA-PDF hybrid method achieves superior artifact correction by exploiting the motion history and intrinsic magnetic susceptibility of the underlying tissue.