Hybrid Volumes
نویسندگان
چکیده
منابع مشابه
A Hybrid 3D Learning-and-Interaction-based Segmentation Approach Applied on CT Liver Volumes
Medical volume segmentation in various imaging modalities using real 3D approaches (in contrast to sliceby-slice segmentation) represents an actual trend. The increase in the acquisition resolution leads to large amount of data, requiring solutions to reduce the dimensionality of the segmentation problem. In this context, the real-time interaction with the large medical data volume represents a...
متن کامل3D Anisotropic Hybrid Network: Transferring Convolutional Features from 2D Images to 3D Anisotropic Volumes
While deep convolutional neural networks (CNN) have been successfully applied for 2D image analysis, it is still challenging to apply them to 3D anisotropic volumes, especially when the within-slice resolution is much higher than the between-slice resolution and when the amount of 3D volumes is relatively small. On one hand, direct learning of CNN with 3D convolution kernels suffers from the la...
متن کاملHybrid Collision Culling by Bounding Volumes Manipulation in Massive Rigid Body Simulation
Collision detection is an important aspect in many real-time simulation environments. Due to its nature of high Computation involved, collision detection can contribute to the bottleneck on the system involving large number of interacting objects. This paper focuses on finding options to efficiently cull away object pairs that are not likely to collide in large-scale dynamic rigid-body simulati...
متن کاملUsing a Classification Tree to Speed up Rendering of Hybrid Surface and Volumes Models
Hybrid rendering of volume and polygonal model is an interesting feature of visualization systems, since it helps users to better understand the relationships between internal structures of the volume and fitted surfaces as well as external surfaces. Most of the existing bibliography focuses at the problem of correctly integrating in depth both types of information. The rendering method propose...
متن کاملH-DenseUNet: Hybrid Densely Connected UNet for Liver and Liver Tumor Segmentation from CT Volumes
Liver and liver tumor segmentation plays an important role in hepatocellular carcinoma diagnosis and treatment planning. Recently, fully convolutional neural networks (FCNs) serve as the back-bone in many volumetric medical image segmentation tasks, including 2D and 3D FCNs. However, 2D convolutions can not fully leverage the spatial information along the z-axis direction while 3D convolutions ...
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: Journal of the Visualization Society of Japan
سال: 2008
ISSN: 0916-4731,1884-037X
DOI: 10.3154/jvs.28.79