30 research outputs found
Phase retrieval for characteristic functions of convex bodies and reconstruction from covariograms
We propose strongly consistent algorithms for reconstructing the
characteristic function 1_K of an unknown convex body K in R^n from possibly
noisy measurements of the modulus of its Fourier transform \hat{1_K}. This
represents a complete theoretical solution to the Phase Retrieval Problem for
characteristic functions of convex bodies. The approach is via the closely
related problem of reconstructing K from noisy measurements of its covariogram,
the function giving the volume of the intersection of K with its translates. In
the many known situations in which the covariogram determines a convex body, up
to reflection in the origin and when the position of the body is fixed, our
algorithms use O(k^n) noisy covariogram measurements to construct a convex
polytope P_k that approximates K or its reflection -K in the origin. (By recent
uniqueness results, this applies to all planar convex bodies, all
three-dimensional convex polytopes, and all symmetric and most (in the sense of
Baire category) arbitrary convex bodies in all dimensions.) Two methods are
provided, and both are shown to be strongly consistent, in the sense that,
almost surely, the minimum of the Hausdorff distance between P_k and K or -K
tends to zero as k tends to infinity.Comment: Version accepted on the Journal of the American Mathematical Society.
With respect to version 1 the noise model has been greatly extended and an
appendix has been added, with a discussion of rates of convergence and
implementation issues. 56 pages, 4 figure
Convergence of algorithms for reconstructing convex bodies and directional measures
We investigate algorithms for reconstructing a convex body in from noisy measurements of its support function or its brightness
function in directions . The key idea of these algorithms is
to construct a convex polytope whose support function (or brightness
function) best approximates the given measurements in the directions
(in the least squares sense). The measurement errors are assumed
to be stochastically independent and Gaussian. It is shown that this procedure
is (strongly) consistent, meaning that, almost surely, tends to in
the Hausdorff metric as . Here some mild assumptions on the
sequence of directions are needed. Using results from the theory of
empirical processes, estimates of rates of convergence are derived, which are
first obtained in the metric and then transferred to the Hausdorff
metric. Along the way, a new estimate is obtained for the metric entropy of the
class of origin-symmetric zonoids contained in the unit ball. Similar results
are obtained for the convergence of an algorithm that reconstructs an
approximating measure to the directional measure of a stationary fiber process
from noisy measurements of its rose of intersections in directions
. Here the Dudley and Prohorov metrics are used. The methods are
linked to those employed for the support and brightness function algorithms via
the fact that the rose of intersections is the support function of a projection
body.Comment: Published at http://dx.doi.org/10.1214/009053606000000335 in the
Annals of Statistics (http://www.imstat.org/aos/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Efficacy of Off-Label Anti-Amoebic Agents to Suppress Trophozoite Formation of Acanthamoeba spp. on Non-Nutrient Agar Escherichia Coli Plates
Acanthamoeba keratitis (AK) is a dangerous infectious disease, which is associated with
a high risk of blindness for the infected patient, and for which no standard therapy exists thus far.
Patients suffering from AK are thus treated, out of necessity, with an off-label therapy, using drugs
designed and indicated for other diseases/purposes. Here, we tested the capability of the off-label
anti-amoebic drugs chlorhexidine (CH; 0.1%), dibromopropamidine diisethionate (DD; 0.1%), hexamidine diisethionate (HD; 0.1%), miltefosine (MF; 0.0065%), natamycin (NM; 5%), polyhexamethylene
biguanide (PHMB; 0.02%), povidone iodine (PVPI; 1%), and propamidine isethionate (PD; 0.1%)
to suppress trophozoite formation of Acantamoeba castellanii and Acanthamoeba hatchetti cysts on
non-nutrient agar Escherichia coli plates. Of the eight off-label anti-amoebic drugs tested, only PVPI
allowed for a complete suppression of trophozoite formation by drug-challenged cysts for all four
Acanthamoeba isolates in all five biological replicates. Drugs such as NM, PD, and PHMB repeatedly
suppressed trophozoite formation with some, but not all, tested Acanthamoeba isolates, while other
drugs such as CH, DD, and MF failed to exert a relevant effect on the excystation capacities of
the tested Acanthamoeba isolates in most, if not all, of our repetitions. Our findings suggest that
pre-testing of the AK isolate with the non-nutrient agar E. coli plate assay against the anti-amoebic
drug intended for treatment should be performed to confirm that the selected drug is cysticidal for
the Acanthamoeba isolate
Tensor valuations and their applications in stochastic geometry and imaging
The purpose of this volume is to give an up-to-date introduction to tensor valuations and their applications. Starting with classical results concerning scalar-valued valuations on the families of convex bodies and convex polytopes, it proceeds to the modern theory of tensor valuations. Product and Fourier-type transforms are introduced and various integral formulae are derived. New and well-known results are presented, together with generalizations in several directions, including extensions to the non-Euclidean setting and to non-convex sets. A variety of applications of tensor valuations to models in stochastic geometry, to local stereology and to imaging are also discussed