Radiation reduction for interventional radiology imaging: a video frame interpolation solution.

Purpose: The aim of this study was to diminish radiation exposure in interventional radiology (IR) imaging while maintaining image quality. This was achieved by decreasing the acquisition frame rate and employing a deep neural network to interpolate the reduced frames.

Methods: This retrospective study involved the analysis of 1634 IR sequences from 167 pediatric patients (March 2014 to January 2022).

qNABpredict: Quick, accurate, and taxonomy-aware sequence-based prediction of content of nucleic acid binding amino acids.

Protein sequence-based predictors of nucleic acid (NA)-binding include methods that predict NA-binding proteins and NA-binding residues. The residue-level tools produce more details but suffer high computational cost since they must predict every amino acid in the input sequence and rely on multiple sequence alignments. We propose an alternative approach that predicts content (fraction) of the NA-binding residues, offering more information than the protein-level prediction and much shorter runtime than the residue-level tools.