The Deelen infrasound array for recording sonic booms and events of CTBT interest

The Seismology Division of the Royal Netherlands Meteorological Institute (KNMI) has build up expertise in infrasound measurements by investigating low frequency events in order to distinguish between seismic and sonic events. KNMI operates, amongst others, a sixteen element microbarometer array with an aperture of 1.5 km, the Deelen Infrasound Array (DIA). Sonic booms and events of Comprehensive Test Ban Treaty (CTBT) interest are recorded within the frequency range of 100 seconds and 40 Hertz. Recently, KNMI and Microflown Technologies B.V. started a collaboration concerning infrasound measurements. This paper reports the use of a novel sensor. The so-called Microflown [1] is an acoustic sensor, sensitive for frequencies from 0Hz up to 1kHz. The Microflown is developed at the University of Twente and commercialised by Microflown Technologies B.V [3]

Atlas-based mosaicing of 3D transesophageal echocardiography images of the left atrium

3D transesophageal echocardiography (TEE) is routinely used for planning and guidance of cardiac interventions. However, the limited field-of-view dictates the compounding of multiple images for visualization of large structures, e.g. the left atrium (LA). Previously, we developed a TEE image acquisition protocol to capture the LA in six views. This paper proposes the use of fused TEE data of other patients as atlases to guide the registration of these views in a novel method, denoted atlas-based mosaicing (ABM). In this method, each TEE view is rigidly registered to a fused TEE atlas image of another patient, followed by pairwise registration of neighboring TEE views. Experiments on ten patient data sets and five atlas sets reveal the superior performance of ABM compared to regular pairwise registration. Similar to atlas-based segmentation approaches, ABM has the power of combining the outcome of multiple atlases resulting in accurate registration of images with little overlap

Improved segmentation of multiple cavities of the heart in wide-view 3-D transesophageal echocardiograms

Minimally invasive interventions in the heart such as in electrophysiology are becoming more and more important in clinical practice. Currently, preoperative computed tomography angiography (CTA) is used to provide anatomic information during electrophysiology interventions, but this does not provide real-time feedback and burdens the patient with additional radiation and side effects of the contrast agent. Three-dimensional transesophageal echocardiography (TEE) is an excellent modality for visualization of anatomic structures and instruments in real time, but some cavities, especially the left atrium, suffer from the limited coverage of the 3-D TEE volumes. This leads to difficulty in segmenting the left atrium. We propose replacing or complementing pre-operative CTA imaging with wide-view TEE. We tested this proposal on 20 patients for which TEE image volumes covering the left atrium and CTA images were acquired. The TEE images were manually registered, and wide-view volumes were generated. Five heart cavities in single-view and wide-view TEE were segmented and compared with atlas based-segmentations derived from the CTA images. We found that the segmentation accuracy (Dice coefficients) improved relative to segmentation of single-view images by 5, 15 and 9 percentage points for the left atrium, right atrium and aorta, respectively. Average anatomic coverage was improved by 2, 29, 62 and 49 percentage points for the right ventricle, left atrium, right atrium and aorta, respectively. This finding confirms that wide-view 3-D TEE can be useful in supporting electrophysiology interventions

Segmentation of multiple heart cavities in 3-D transesophageal ultrasound images

Three-dimensional transesophageal echocardiography (TEE) is an excellent modality for real-time visualization of the heart and monitoring of interventions. To improve the usability of 3-D TEE for intervention monitoring and catheter guidance, automated segmentation is desired. However, 3-D TEE segmentation is still a challenging task due to the complex anatomy with multiple cavities, the limited TEE field of view, and typical ultrasound artifacts. We propose to segment all cavities within the TEE view with a multi-cavity active shape model (ASM) in conjunction with a tissue/blood classification based on a gamma mixture model (GMM). 3-D TEE image data of twenty patients were acquired with a Philips X7-2t matrix TEE probe. Tissue probability maps were estimated by a two-class (blood/tissue) GMM. A statistical shape model containing the left ventricle, right ventricle, left atrium, right atrium, and aorta was derived from computed tomography angiography (CTA) segmentations by principal component analysis. ASMs of the whole heart and individual cavities were generated and consecutively fitted to tissue probability maps. First, an average whole-heart model was aligned with the 3-D TEE based on three manually indicated anatomical landmarks. Second, pose and shape of the whole-heart ASM were fitted by a weighted update scheme excluding parts outside of the image sector. Third, pose and shape of ASM for individual heart cavities were initialized by the previous whole heart ASM and updated in a regularized manner to fit the tissue probability maps. The ASM segmentations were validated against manual outlines by two observers and CTA derived segmentations