[The development of real-time multispectral imaging for the diagnostics of bladder cancer]. / Entwicklung der Echtzeitmultispektralbildgebung für die Diagnostik des Harnblasenkarzinoms.

The performance of white light (WL) cystoscopy in the diagnostics of bladder cancer can be optimized by the use of modern imaging modalities, such as photodynamic diagnostics (PDD) and narrow band imaging (NBI). Real-time multispectral imaging (rMSI) enables simultaneous imaging of reflectance and fluorescence modalities in multiple spectral bands. We created a multiparametric cystoscopy image by digital overlapping of several modalities, e.g. WL, enhanced vascular contrast (EVC), raw fluorescence mode, protoporphyrin IX and autofluorescence (AF). The technical development and the subsequent clinical implementation of rMSI required a structured preclinical evaluation process, including both ex vivo and in vivo trials before the technology can be applied in patients. This review article presents the phases of testing, validation and the first clinical application of rMSI in urological endoscopy.

Tracking boundary movement and exterior shape modelling in lung EIT imaging.

Electrical impedance tomography (EIT) has shown significant promise for lung imaging. One key challenge for EIT in this application is the movement of electrodes during breathing, which introduces artefacts in reconstructed images. Various approaches have been proposed to compensate for electrode movement, but no comparison of these approaches is available. This paper analyses boundary model mismatch and electrode movement in lung EIT. The aim is to evaluate the extent to which various algorithms tolerate movement, and to determine if a patient specific model is required for EIT lung imaging. Movement data are simulated from a CT-based model, and image analysis is performed using quantitative figures of merit. The electrode movement is modelled based on expected values of chest movement and an extended Jacobian method is proposed to make use of exterior boundary tracking. Results show that a dynamical boundary tracking is the most robust method against any movement, but is computationally more expensive. Simultaneous electrode movement and conductivity reconstruction algorithms show increased robustness compared to only conductivity reconstruction. The results of this comparative study can help develop a better understanding of the impact of shape model mismatch and electrode movement in lung EIT.