Electrical impedance-based tissue classification for bladder tumor differentiation.

Including sensor information in medical interventions aims to support surgeons to decide on subsequent action steps by characterizing tissue intraoperatively. With bladder cancer, an important issue is tumor recurrence because of failure to remove the entire tumor. Impedance measurements can help to classify bladder tissue and give the surgeons an indication on how much tissue to remove.

In-plane Strain Analysis by Correlating Geometry and Visual Data Through a Gradient-Based Surface Reconstruction.

Abnormalities in tissue can be detected and analyzed by evaluating mechanical properties, such as strain and stiffness. While current sensor systems are effective in measuring longitudinal properties perpendicular to the measurement sensor, identifying in-plane deformation remains a significant challenge. To address this issue, this paper presents a novel method for reconstructing in-plane deformation of observed tissue surfaces using a fringe projection sensor specifically designed for measuring tissue deformations.

An Enhanced Synthetic Cystoscopic Environment for Use in Monocular Depth Estimation.

As technology advances and sensing devices improve, it is becoming more and more pertinent to ensure accurate positioning of these devices, especially within the human body. This task remains particularly difficult during manual, minimally invasive surgeries such as cystoscopies where only a monocular, endoscopic camera image is available and driven by hand. Tracking relies on optical localization methods, however, existing classical options do not function well in such a dynamic, non-rigid environment.

Compensating the Influence of Tremors on Impedance Measurements Through Fourier Analysis.

Electrical mpedance measurements are a promising method for detecting structural changes in tissue and can be used in oncology to differentiate between healthy and tumorous tissue areas. The impedance measurements are so sensitive that they are not only affected by changes in the tissue itself, but also by a fluctuating contact force between sensor and tissue. In this work, the correlation between impedance measurements and movements during the measuring process, such as physiological tremors, are analyzed.

Cystoscopic depth estimation using gated adversarial domain adaptation.

Monocular depth estimation from camera images is very important for surrounding scene evaluation in many technical fields from automotive to medicine. However, traditional triangulation methods using stereo cameras or multiple views with the assumption of a rigid environment are not applicable for endoscopic domains. Particularly in cystoscopies it is not possible to produce ground truth depth information to directly train machine learning algorithms for using a monocular image directly for depth prediction.