Cloud-Based Automated Design and Additive Manufacturing: A Usage Data-Enabled Paradigm Shift.

Integration of sensors into various kinds of products and machines provides access to in-depth usage information as basis for product optimization. Presently, this large potential for more user-friendly and efficient products is not being realized because (a) sensor integration and thus usage information is not available on a large scale and (b) product optimization requires considerable efforts in terms of manpower and adaptation of production equipment. However, with the advent of cloud-based services and highly flexible additive manufacturing techniques, these obstacles are currently crumbling away at rapid pace. The present study explores the state of the art in gathering and evaluating product usage and life cycle data, additive manufacturing and sensor integration, automated design and cloud-based services in manufacturing. By joining and extrapolating development trends in these areas, it delimits the foundations of a manufacturing concept that will allow continuous and economically viable product optimization on a general, user group or individual user level. This projection is checked against three different application scenarios, each of which stresses different aspects of the underlying holistic concept. The following discussion identifies critical issues and research needs by adopting the relevant stakeholder perspectives.

Evaluation of a vessel-tracking-based technique for dynamic targeting in human liver.

The purpose of this study was to evaluate a novel vessel-tracking-based technique for tracking of human liver. The novelty of the proposed technique is that it measures the translation and deformation of a local tissue region based on the displacements of a set of vessels of interest instead of the entire organ. The position of the target point was estimated from the relative positions of the center-of-masses of the vessels, assuming that the topological relationship between the target point and center-of-masses is unchanged during breathing. To reduce inaccuracy due to the delay between vessel image acquisition and sonication, the near-future target position was predicted based on the vessel displacements in the images extracted from an image library acquired before the tracking stage. Experiments on healthy volunteers demonstrated that regardless of the respiratory condition, appropriate combinations of three center-of-masses from the vessels situated around the target-tissue position yielded an estimation error of less than 2 mm, which was significantly smaller than that obtained when using a single center-of-mass trio. The effect of the tracking delay was successfully compensated, with a prediction error of less than 3 mm, by using over four images selected from the image library.

Image reconstruction method with compressed sensing for high-speed MR temperature measurement of abdominal organs.

Magnetic Resonance guided High Intensity Focused Ultrasound (MRgHIFU) treatment is a low invasive tumor treatment using high energy from an ultrasound. The transducer generates sound wave and focuses a heat point within the body to eliminate the tumor. In heating, it is necessary to monitor the condition at the target area for safe and effective treatment. Magnetic Resonance Imaging(MRI) can monitor the target condition and temperature distribution during treatment. However, the acquisition time of MR data is long and has to be shortened to track the focal point. In this research, a rapid acquisition and reconstruction method using compressed sensing MRI is proposed. In order to reduce the number of phase encode times, k-space was divided into regions. Then, the value of the gradient was used to shorten the signal restoration time. In the computational experiments, image quality and temperature error were evaluated.

Method for target tracking in focused ultrasound surgery of liver using magnetic resonance filtered venography.

The purpose of this work is to develop a magnetic resonance (MR) technique for guiding a focal point created in Focused Ultrasound Surgery (FUS) onto a specific target position in an abdominal organ, such as the liver, which moves and deforms with respiratory motion. The translational distance, rotational angles, and amount of expansion and contraction of the organ tissue were measured by obtaining the gravity points of the veins filtered from the sagittal, cine MR images of healthy livers during free breathing. Using the locations of the vessels at each time point, the target position at which the ultrasound focus was to be placed was estimated. In the volunteer experiments (N = 2), the lower limit of the spatial matrix dimension for delineating the veins was 128 x 128. The average displacement of the liver was 19.6 +/- 3.6 mm in superior-inferior (SI) direction and 3.1 +/- 1.4 mm in anterior-posterior (AP) direction. The deformations were 3.7 +/- 1.1 mm in SI direction and 3.0 +/- 1.2 mm in AP direction. The error between the actual and the estimated target point was 0.7 +/- 0.5 mm in SI direction, 0.6 +/- 0.4 mm in AP direction and 1.0 +/- 0.5 mm in distance, and less than 2.1 mm in all the trials. These results suggested that the proposed technique is sufficient for targeting the focus on a specific tissue location and for tracking the slice slab for thermometry to cover the region of focus.