Real-time multi-directional flow MRI using model-based reconstructions of undersampled radial FLASH – A feasibility study

The purpose of this work was to develop an acquisition and reconstruction technique for two- and three-directional (2d and 3d) phase-contrast flow MRI in real time. A previous real-time MRI technique for one-directional (1d) through-plane flow was extended to 2d and 3d flow MRI by introducing in-plane flow sensitivity. The method employs highly undersampled radial FLASH sequences with sequential acquisitions of two or three flow-encoding datasets and one flow-compensated dataset. Echo times are minimized by merging the waveforms of flow-encoding and radial imaging gradients. For each velocity direction individually, model-based reconstructions by regularized nonlinear inversion jointly estimate an anatomical image, a set of coil sensitivities and a phase-contrast velocity map directly. The reconstructions take advantage of a dynamic phase reference obtained by interpolating consecutive flow-compensated acquisitions. Validations include pulsatile flow phantoms as well as in vivo studies of the human aorta at 3 T. The proposed method offers cross-sectional 2d and 3d flow MRI of the human aortic arch at 53 and 67 ms resolution, respectively, without ECG synchronization and during free breathing. The in-plane resolution was 1.5 × 1.5 mm2 and the slice thickness 6 mm. In conclusion, real-time multi-directional flow MRI offers new opportunities to study complex human blood flow without the risk of combining differential phase (i.e., velocity) information from multiple heartbeats as for ECG-gated data. The method would benefit from a further reduction of acquisition time and accelerated computing to allow for extended clinical trials

Video Registration in Egocentric Vision under Day and Night Illumination Changes

With the spread of wearable devices and head mounted cameras, a wide range of application requiring precise user localization is now possible. In this paper we propose to treat the problem of obtaining the user position with respect to a known environment as a video registration problem. Video registration, i.e. the task of aligning an input video sequence to a pre-built 3D model, relies on a matching process of local keypoints extracted on the query sequence to a 3D point cloud. The overall registration performance is strictly tied to the actual quality of this 2D-3D matching, and can degrade if environmental conditions such as steep changes in lighting like the ones between day and night occur. To effectively register an egocentric video sequence under these conditions, we propose to tackle the source of the problem: the matching process. To overcome the shortcomings of standard matching techniques, we introduce a novel embedding space that allows us to obtain robust matches by jointly taking into account local descriptors, their spatial arrangement and their temporal robustness. The proposal is evaluated using unconstrained egocentric video sequences both in terms of matching quality and resulting registration performance using different 3D models of historical landmarks. The results show that the proposed method can outperform state of the art registration algorithms, in particular when dealing with the challenges of night and day sequences

Optically gated beating-heart imaging

The constant motion of the beating heart presents an obstacle to clear optical imaging, especially 3D imaging, in small animals where direct optical imaging would otherwise be possible. Gating techniques exploit the periodic motion of the heart to computationally "freeze" this movement and overcome motion artefacts. Optically gated imaging represents a recent development of this, where image analysis is used to synchronize acquisition with the heartbeat in a completely non-invasive manner. This article will explain the concept of optical gating, discuss a range of different implementation strategies and their strengths and weaknesses. Finally we will illustrate the usefulness of the technique by discussing applications where optical gating has facilitated novel biological findings by allowing 3D in vivo imaging of cardiac myocytes in their natural environment of the beating heart

Reflectance Transformation Imaging (RTI) System for Ancient Documentary Artefacts

This tutorial summarises our uses of reflectance transformation imaging in archaeological contexts. It introduces the UK AHRC funded project reflectance Transformation Imaging for Anciant Documentary Artefacts and demonstrates imaging methodologies

T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objects

We introduce T-LESS, a new public dataset for estimating the 6D pose, i.e. translation and rotation, of texture-less rigid objects. The dataset features thirty industry-relevant objects with no significant texture and no discriminative color or reflectance properties. The objects exhibit symmetries and mutual similarities in shape and/or size. Compared to other datasets, a unique property is that some of the objects are parts of others. The dataset includes training and test images that were captured with three synchronized sensors, specifically a structured-light and a time-of-flight RGB-D sensor and a high-resolution RGB camera. There are approximately 39K training and 10K test images from each sensor. Additionally, two types of 3D models are provided for each object, i.e. a manually created CAD model and a semi-automatically reconstructed one. Training images depict individual objects against a black background. Test images originate from twenty test scenes having varying complexity, which increases from simple scenes with several isolated objects to very challenging ones with multiple instances of several objects and with a high amount of clutter and occlusion. The images were captured from a systematically sampled view sphere around the object/scene, and are annotated with accurate ground truth 6D poses of all modeled objects. Initial evaluation results indicate that the state of the art in 6D object pose estimation has ample room for improvement, especially in difficult cases with significant occlusion. The T-LESS dataset is available online at cmp.felk.cvut.cz/t-less.Comment: WACV 201