Accurate Surface Estimation Research Articles

Surface Estimation for Microwave Imaging.

Biomedical imaging and sensing applications in many scenarios demand accurate surface estimation from a sparse set of noisy measurements. These measurements may arise from a variety of sensing modalities, including laser or electromagnetic samples of an object’s surface. We describe a state-of-the-art microwave imaging prototype that has sensors to acquire both microwave and laser measurements. The approach developed to translate sparse samples of the breast surface into an accurate estimate of the region of interest is detailed. To evaluate the efficacy of the method, laser and electromagnetic samples are acquired by sensors from three realistic breast models with varying sizes and shapes. A set of metrics is developed to assist with the investigation and demonstrate that the algorithm is able to accurately estimate the shape of a realistic breast phantom when only a sparse set of data are available. Moreover, the algorithm is robust to the presence of measurement noise, and is effective when applied to measurement scans of patients acquired with the prototype.

Kernel based approach for accurate surface estimation

Accurate surface estimation is a critical step for autonomous robot navigation on a rough terrain. In this paper, we present a new method for estimating the surface of an unknown arbitrarily shaped terrain from the range data. The terrain modeling problem is generally formulated as the estimation of a function whose zero-set corresponds to the surface to be reconstructed. A Laser range scanner has been built for acquisition of range data. The range data from the scanner samples the terrain unevenly, and is more sparse for distant regions from the sensor. The paper describes the surface estimation problem as a max-margin based formulation of a non-stationary kernel function and minimizes the objective function using sub-gradient method. Unlike other methods, additional geometric ray based information is used to eliminate the unnecessary bumps on the surface and increase the precision. The experimental results validate the robustness of the proposed approach.

Spatial Spline Regression Models

SummaryWe describe a model for the analysis of data distributed over irregularly shaped spatial domains with complex boundaries, strong concavities and interior holes. Adopting an approach that is typical of functional data analysis, we propose a spatial spline regression model that is computationally efficient, allows for spatially distributed covariate information and can impose various conditions over the boundaries of the domain. Accurate surface estimation is achieved by the use of piecewise linear and quadratic finite elements.

Laser Surface Estimation for Microwave Breast Imaging Systems

Microwave breast imaging techniques involve collecting measurements from a breast that is positioned in a scanner. While the patient interface typically includes a hole through which the breast is placed when the patient lies in the prone position, the exact location and shape of breast are not known. In this paper, we explore the addition of a laser sensor and associated algorithms in order to provide a rapid and accurate estimate of the breast surface location. We demonstrate that the laser is capable of estimating surfaces with improved accuracy compared to microwave measurements. The impact of accurate surface estimation on images is shown, and results obtained from human scans are presented.