Full Body Virtual Autopsies using a State-of-the-art Volume Rendering Pipeline

2006 ◽  
Vol 12 (5) ◽  
pp. 869-876 ◽  
Author(s):  
Patric Ljung ◽  
Calle Winskog ◽  
Anders Persson ◽  
Claes Lundstrom ◽  
Anders Ynnerman
Author(s):  
Kun Yuan ◽  
Qian Zhang ◽  
Chang Huang ◽  
Shiming Xiang ◽  
Chunhong Pan

Person Re-identification (ReID) is a challenging retrieval task that requires matching a person's image across non-overlapping camera views. The quality of fulfilling this task is largely determined on the robustness of the features that are used to describe the person. In this paper, we show the advantage of jointly utilizing multi-scale abstract information to learn powerful features over full body and parts. A scale normalization module is proposed to balance different scales through residual-based integration. To exploit the information hidden in non-rigid body parts, we propose an anchor-based method to capture the local contents by stacking convolutions of kernels with various aspect ratios, which focus on different spatial distributions. Finally, a well-defined framework is constructed for simultaneously learning the representations of both full body and parts. Extensive experiments conducted on current challenging large-scale person ReID datasets, including Market1501, CUHK03 and DukeMTMC, demonstrate that our proposed method achieves the state-of-the-art results.


2016 ◽  
Vol 35 (3) ◽  
pp. 669-691 ◽  
Author(s):  
Patric Ljung ◽  
Jens Krüger ◽  
Eduard Groller ◽  
Markus Hadwiger ◽  
Charles D. Hansen ◽  
...  

2014 ◽  
Author(s):  
Ievgeniia Gutenko ◽  
Kaloian Petkov ◽  
Charilaos Papadopoulos ◽  
Xin Zhao ◽  
Ji Hwan Park ◽  
...  

2005 ◽  
Vol 05 (04) ◽  
pp. 699-714 ◽  
Author(s):  
JIANLONG ZHOU ◽  
ANDREAS DÖRING ◽  
KLAUS D. TÖNNIES

Volume data often have redundant information for clinical uses. The essence of volume rendering can be regarded as a mechanism to determine visibility of redundant information and structures of interest using different approaches. Controlling the visibility of these structures in volume rendering depends on the following factors in existing rendering algorithms: The data value of current voxel and its derivatives (used in transfer function based approaches), and the voxel position (used in volume clipping). This paper introduces the distance which is defined by the user into volume rendering pipeline to control the visibility of structures. The distance based approach, which is named as distance transfer function, has the flexibility of transfer functions for depicting data information and the advantages of volume clippings for visualizing inner structures. The results show that the distance based approach is a powerful tool for volume data information depiction.


2014 ◽  
Vol 33 (6) ◽  
pp. 77-100 ◽  
Author(s):  
M. Balsa Rodríguez ◽  
E. Gobbetti ◽  
J.A. Iglesias Guitián ◽  
M. Makhinya ◽  
F. Marton ◽  
...  

2022 ◽  
Vol 65 (1) ◽  
pp. 99-106
Author(s):  
Ben Mildenhall ◽  
Pratul P. Srinivasan ◽  
Matthew Tancik ◽  
Jonathan T. Barron ◽  
Ravi Ramamoorthi ◽  
...  

We present a method that achieves state-of-the-art results for synthesizing novel views of complex scenes by optimizing an underlying continuous volumetric scene function using a sparse set of input views. Our algorithm represents a scene using a fully connected (nonconvolutional) deep network, whose input is a single continuous 5D coordinate (spatial location ( x , y , z ) and viewing direction ( θ, ϕ )) and whose output is the volume density and view-dependent emitted radiance at that spatial location. We synthesize views by querying 5D coordinates along camera rays and use classic volume rendering techniques to project the output colors and densities into an image. Because volume rendering is naturally differentiable, the only input required to optimize our representation is a set of images with known camera poses. We describe how to effectively optimize neural radiance fields to render photorealistic novel views of scenes with complicated geometry and appearance, and demonstrate results that outperform prior work on neural rendering and view synthesis.


Author(s):  
T. A. Welton

Various authors have emphasized the spatial information resident in an electron micrograph taken with adequately coherent radiation. In view of the completion of at least one such instrument, this opportunity is taken to summarize the state of the art of processing such micrographs. We use the usual symbols for the aberration coefficients, and supplement these with £ and 6 for the transverse coherence length and the fractional energy spread respectively. He also assume a weak, biologically interesting sample, with principal interest lying in the molecular skeleton remaining after obvious hydrogen loss and other radiation damage has occurred.


Author(s):  
Carl E. Henderson

Over the past few years it has become apparent in our multi-user facility that the computer system and software supplied in 1985 with our CAMECA CAMEBAX-MICRO electron microprobe analyzer has the greatest potential for improvement and updating of any component of the instrument. While the standard CAMECA software running on a DEC PDP-11/23+ computer under the RSX-11M operating system can perform almost any task required of the instrument, the commands are not always intuitive and can be difficult to remember for the casual user (of which our laboratory has many). Given the widespread and growing use of other microcomputers (such as PC’s and Macintoshes) by users of the microprobe, the PDP has become the “oddball” and has also fallen behind the state-of-the-art in terms of processing speed and disk storage capabilities. Upgrade paths within products available from DEC are considered to be too expensive for the benefits received. After using a Macintosh for other tasks in the laboratory, such as instrument use and billing records, word processing, and graphics display, its unique and “friendly” user interface suggested an easier-to-use system for computer control of the electron microprobe automation. Specifically a Macintosh IIx was chosen for its capacity for third-party add-on cards used in instrument control.


Sign in / Sign up

Export Citation Format

Share Document