10,483 research outputs found
Unsupervised Body Part Regression via Spatially Self-ordering Convolutional Neural Networks
Automatic body part recognition for CT slices can benefit various medical
image applications. Recent deep learning methods demonstrate promising
performance, with the requirement of large amounts of labeled images for
training. The intrinsic structural or superior-inferior slice ordering
information in CT volumes is not fully exploited. In this paper, we propose a
convolutional neural network (CNN) based Unsupervised Body part Regression
(UBR) algorithm to address this problem. A novel unsupervised learning method
and two inter-sample CNN loss functions are presented. Distinct from previous
work, UBR builds a coordinate system for the human body and outputs a
continuous score for each axial slice, representing the normalized position of
the body part in the slice. The training process of UBR resembles a
self-organization process: slice scores are learned from inter-slice
relationships. The training samples are unlabeled CT volumes that are abundant,
thus no extra annotation effort is needed. UBR is simple, fast, and accurate.
Quantitative and qualitative experiments validate its effectiveness. In
addition, we show two applications of UBR in network initialization and anomaly
detection.Comment: Oral presentation in ISBI1
K-quantum Nonlinear Jaynes-Cummings Model in Two Trapped Ions
A k-quantum nonlinear Jaynes-Cummings model for two trapped ions interacting
with laser beams resonant to k-th red side-band of center-of-mass mode, far
from Lamb-Dicke regime, has been obtained. The exact analytic solution showed
the existence of quantum collapses and revivals of the occupation of two atoms.Comment: 8 pages, 3 figure
Quantum-State Engineering of Multiple Trapped Ions for Center-of-Mass Mode
We propose a scheme to generate a superposition with arbitrary coefficients
on a line in phase space for the center-of-mass vibrational mode of N ions by
means of isolating all other spectator vibrational modes from the
center-of-mass mode. It can be viewed as the generation of previous methods for
preparing motional states of one ion. For large number of ions, we need only
one cyclic operatin to generate such a superposition of many coherent states.Comment: 14 pages, revte
Constraints on the Local Cosmic Void from the Pantheon Supernovae Data
In principle, the local cosmic void can be simply modeled by the spherically
symmetric Lemaitre-Tolman-Bondi (LTB) metric. In practice, the real local
cosmic void is probably not spherically symmetric. In this paper, to
reconstruct a more realistic profile of the local cosmic void, we divide it
into several segments. Each segment with certain solid angle is modeled by its
own LTB metric. Meanwhile, we divide the 1048 type Ia supernovae (SNIa) of the
Pantheon Survey into corresponding subsets according to their distribution in
the galactic coordinate system. Obviously, each SNIa subset can only be used to
reconstruct the profile of one segment. Finally, we can patch together an
irregular profile for the local cosmic void with the whole Pantheon sample.
Note that, the paucity of each data subset lead us to focus on the inner part
of each void segment and assume that the half radii of the void segments are
sufficient to constrain the whole segment. We find that, despite
signals of anisotropy limited to the depth of the void segments, the
constraints on every void segment are consistent with CDM model at
CL. Moreover, our constraints are too weak to challenge the cosmic
homogeneity and isotropy.Comment: 12 pages, 9 figure
Probabilistic Risk Assessment of Reservoir Operation
Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchive
- …