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The Exoplanet Imaging Data Challenge is a community-wide effort meant to offer a platform for a fair and common comparison of image processing methods designed for exoplanet direct detection. For this purpose, it gathers on a dedicated repository (Zenodo), data from several high-contrast ground-based instruments worldwide in which we injected synthetic planetary signals. The data challenge is hosted on the CodaLab competition platform, where participants can upload their results. The specifications of the data challenge are published on our website https://exoplanet-imaging-challenge.github.io/. The first phase, launched on the 1st of September 2019 and closed on the 1st of October 2020, consisted in detecting point sources in two types of common data-set in the field of high-contrast imaging: data taken in pupil-tracking mode at one wavelength (subchallenge 1, also referred to as ADI) and multispectral data taken in pupil-tracking mode (subchallenge 2, also referred to as ADI+mSDI). In this paper, we describe the approach, organisational lessons-learnt and current limitations of the data challenge, as well as preliminary results of the participants’ submissions for this first phase. In the future, we plan to provide permanent access to the standard library of data sets and metrics, in order to guide the validation and support the publications of innovative image processing algorithms dedicated to high-contrast imaging of planetary systems.
Coagulative disorders, especially clotting during extracorporeal membrane oxygenation, are frequent complications. Direct visualization and analysis of deposits in membrane oxygenators using computed tomography (CT) may provide an insight into the underlying mechanisms causing thrombotic events. However, the already established multidetector CT1 (MDCT) method shows major limitations. Here, we demonstrate the feasibility of applying industrial micro-CT (μCT) to circumvent these restrictions. Three clinically used membrane oxygenators were investigated applying both MDCT and μCT.
The scans were analyzed in terms of clot volume and local clot distribution. As validation, the clot volume was also determined from the fluid volume, which could be filled into the respective used oxygenator compared to a new device. In addition, cross-sectional CT images were compared with crosscut oxygenators. Based on the μCT findings, a morphological measure (sphericity) for assessing clot structures in membrane oxygenators is introduced. Furthermore, by comparing MDCT and μCT results, an augmentation of the MDCT method is proposed, which allows for improved clot volume determination in a clinical setting.