Septimiu E. Salcudean

TL;DR: The notion of “automation for surgical manual execution” is proposed where it is argued that autonomous robotic surgery research can be used as a tool for surgeons to discover novel manual execution models that can significantly improve their surgical practice.

TL;DR: In this paper , an image registration workflow is presented to achieve reliable alignment for subject-specific magnetic resonance (MR) and intercostal 3D ultrasound (US) images of the liver.

TL;DR: A computational motion compensation method for tomosynthesis-based reconstruction that enables 3D localization of prostate implants from C-arm images despite C- arm oscillation and sagging and is feasible for clinical use is proposed.

TL;DR: Generative adversarial networks are trained to mimic both the effect of temporal averaging and of singular value decomposition (SVD) denoising, which effectively removes noise and acquisition artifacts and improves signal-to-noise ratio (SNR) in both the radio-frequency (RF) data and in the corresponding photoacoustic reconstructions.

TL;DR: This work proposes a method for automatic segmentation of the prostate clinical target volume for brachytherapy in transrectal ultrasound (TRUS) images based on a novel convolutional neural network (CNN) architecture and suggests an adaptive sampling strategy that drives the training process to give more attention to images that are difficult to segment.