Noise-robust breathing-phase estimation on marker-free, ultra low dose X-ray projections for real-time tumor localization via surrogate structures.

Purpose: This paper presents a novel strategy for feature-based breathing-phase estimation on ultra low-dose X-ray projections for tumor motion control in radiation therapy.

Methods: Coarse-scaled Curvelet coefficients are identified as motion sensitive but noise-robust features for this purpose. For feature-based breathing-phase estimation, an ensemble strategy with two classifiers is used.

Augmented Reality with HoloLens® in Parotid Tumor Surgery: A Prospective Feasibility Study.

Introduction: Augmented reality can improve planning and execution of surgical procedures. Head-mounted devices such as the HoloLens® (Microsoft, Redmond, WA, USA) are particularly suitable to achieve these aims because they are controlled by hand gestures and enable contactless handling in a sterile environment.

Objectives: So far, these systems have not yet found their way into the operating room for surgery of the parotid gland.

Augmented reality with HoloLens in parotid surgery: how to assess and to improve accuracy.

Purpose: Augmented reality improves planning and execution of surgical procedures. The aim of this study was to evaluate the feasibility of a 3D augmented reality hologram in live parotic surgery. Another goal was to develop an accuracy measuring instrument and to determine the accuracy of the system.

Conditional random fields for phase-based lung feature tracking with ultra-low-dose x-rays.

Purpose: During radiation therapy, a continuous internal tumor monitoring without additional imaging dose is desirable. In this study, a sequential feature-based position estimation with ultra-low-dose (ULD) kV x rays using linear-chain conditional random fields (CRFs) is performed.

Methods: Four-dimensional computed tomography (4D-CTs) of eight patients serve as a-priori information from which ULD projections are simulated using a Monte Carlo method.