Optimal surface segmentation with convex priors in irregularly sampled space
نویسندگان
چکیده
منابع مشابه
Optimal Multiple Surface Segmentation with Convex Priors in Irregularly Sampled Space
Optimal surface segmentation is a state-of-the-art method used for segmentation of multiple globally optimal surfaces in volumetric datasets. The method is widely used in numerous medical image segmentation applications. However, nodes in the graph based optimal surface segmentation method typically encode uniformly distributed orthogonal voxels of the volume. Thus the segmentation cannot attai...
متن کاملConvex Modeling with Priors
As the study of complex interconnected networks becomes widespread across disciplines, modeling the large-scale behavior of these systems becomes both increasingly important and increasingly difficult. In particular, it is of tantamount importance to utilize available prior information about the system's structure when building data-driven models of complex behavior. This thesis provides a fram...
متن کاملOptimal space coverage with white convex polygons
Assume that we are given a set of points some of which are black and the rest are white. The goal is to find a set of convex polygons with maximum total area that cover all white points and exclude all black points. We study the problem on three different settings (based on overlapping between different convex polygons): (1) In case convex polygons are permitted to have common area, we present ...
متن کاملTime Series Analysis for Irregularly Sampled Data
Many spectral estimation methods for irregularly sampled data tend to be heavily biased at higher frequencies or fail to produce a spectrum that is positive for all frequencies. A time series spectral estimator is introduced that applies the principles of a new automatic equidistant missing data algorithm to unevenly spaced data. This time series estimator approximates the irregular data by a n...
متن کاملWavelet Sampling Theorems for Irregularly Sampled Signals
In digital signal and image processing, digital communications, and so forth, a continuous signal is usually represented and processed by using its discrete samples. How, then, are we to reconstruct the original signal from its discrete samples? The classical Shannon sampling theorem gives the following formula for band-limited finite energy signals. For a finite energy s-band continuous signal...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Medical Image Analysis
سال: 2019
ISSN: 1361-8415
DOI: 10.1016/j.media.2019.02.004