Geometric modelling for virtual colon unfolding

A virtual endoscopie view is not necessarily the best way to examine a hollow organ, such us, the colon. The inner surface of the colon is where polyps are located, and therefore what is examined by the physicians. A flight through the colon using a common endoscopie view shows a smal! percentage of the inner surface. Virtually unfolding of the colon can be a more etficient way to look at the inner surface. We propose two methods to unfold the colon : a method that unfolds the colon locally using local projections, and a method that obtains global unfolding of the colon by achieving a suitable parameterization of its surface

Bladder runner:visual analytics for the exploration of RT-induced bladder toxicity in a cohort study

\u3cp\u3eWe present the Bladder Runner, a novel tool to enable detailed visual exploration and analysis of the impact of bladder shape variation on the accuracy of dose delivery, during the course of prostate cancer radiotherapy (RT). Our tool enables the investigation of individual patients and cohorts through the entire treatment process, and it can give indications of RT-induced complications for the patient. In prostate cancer RT treatment, despite the design of an initial plan prior to dose administration, bladder toxicity remains very common. The main reason is that the dose is delivered in multiple fractions over a period of weeks, during which, the anatomical variation of the bladder – due to differences in urinary filling – causes deviations between planned and delivered doses. Clinical researchers want to correlate bladder shape variations to dose deviations and toxicity risk through cohort studies, to understand which specific bladder shape characteristics are more prone to side effects. This is currently done with Dose-Volume Histograms (DVHs), which provide limited, qualitative insight. The effect of bladder variation on dose delivery and the resulting toxicity cannot be currently examined with the DVHs. To address this need, we designed and implemented the Bladder Runner, which incorporates visualization strategies in a highly interactive environment with multiple linked views. Individual patients can be explored and analyzed through the entire treatment period, while inter-patient and temporal exploration, analysis and comparison are also supported. We demonstrate the applicability of our presented tool with a usage scenario, employing a dataset of 29 patients followed through the course of the treatment, across 13 time points. We conducted an evaluation with three clinical researchers working on the investigation of RT-induced bladder toxicity. All participants agreed that Bladder Runner provides better understanding and new opportunities for the exploration and analysis of the involved cohort data.\u3c/p\u3

Exploring hemodynamics by raycasting 4D MRI flow

Flow sensitive phase-contrast magnetic resonanceimaging sequences produce three-dimensional velocityfields in time, providing quantitative information ofblood flow dynamics. Thorough understanding of thehemodynamic behavior will support physicians to diagnose and assess risk of various cardiovascular diseases. However, inspection of the complex cine flowdata, encompassing both morphology and function,is generally a troublesome and tedious task. Overthe last few decades, the field of scientific flow visualization has introduced a multitude of techniques to explore unsteady velocity fields, in order to capture and depict flow characteristics. Inspired by concepts from ultrasound imaging, we have investigated raycasting as a means to explore and visualize direction and magnitude of blood velocities, striving to reveal the blood flow behavior. In particular, we aim to depict flow patterns that deviate from the expected blood flow. For that purpose, several interaction techniques have been incorporated into the presented framework. Angles between a user-defined direction, set by an interaction widget, and the velocity field are mapped to different visual cues using a transfer function. Furthermore, we define the prevalent flow as approximate of the expected blood flow, generated based on the vessel centerline. We visualize a projection of the angles between the prevalent flow and the velocity field