Results 101 to 110 of about 4,020,070 (373)

Volume visualization of time-varying data using parallel, multiresolution and adaptive-resolution techniques [PDF]

open access: yes, 2006
This paper presents a parallel rendering approach that allows high-quality visualization of large time-varying volume datasets. Multiresolution and adaptive-resolution techniques are also incorporated to improve the efficiency of the rendering.
Shams, Sadaf
core   +2 more sources

Feasibility of a ctDNA multigenic panel for non‐small‐cell lung cancer early detection and disease surveillance

open access: yesMolecular Oncology, EarlyView.
Plasma‐based detection of actionable mutations is a promising approach in lung cancer management. Analysis of ctDNA with a multigene NGS panel identified TP53, KRAS, and EGFR as the most frequently altered, with TP53 and KRAS in treatment‐naïve patients and TP53 and EGFR in previously treated patients.
Giovanna Maria Stanfoca Casagrande   +11 more
wiley   +1 more source

Achieving Better Energy Efficiency in Volume Analysis and Direct Volume Rendering Descriptor Computation

open access: yesComputers
Approaches aimed at achieving improved energy efficiency for determination of descriptors—used in volumetric data analysis and one common mode of scientific visualisation—in one x86-class setting are described and evaluated.
Jacob D. Hauenstein, Timothy S. Newman
doaj   +1 more source

TetSplat: Real-time Rendering and Volume Clipping of Large Unstructured Tetrahedral Meshes [PDF]

open access: yes, 2004
We present a novel approach to interactive visualization and exploration of large unstructured tetrahedral meshes. These massive 3D meshes are used in mission-critical CFD and structural mechanics simulations, and typically sample multiple field values ...
Lombeyda, Santiago, Museth, Ken
core   +2 more sources

Aggressive prostate cancer is associated with pericyte dysfunction

open access: yesMolecular Oncology, EarlyView.
Tumor‐produced TGF‐β drives pericyte dysfunction in prostate cancer. This dysfunction is characterized by downregulation of some canonical pericyte markers (i.e., DES, CSPG4, and ACTA2) while maintaining the expression of others (i.e., PDGFRB, NOTCH3, and RGS5).
Anabel Martinez‐Romero   +11 more
wiley   +1 more source

Hybrid shear-warp rendering [PDF]

open access: yes, 1999
Shear-warp rendering is a fast and efficient method for visualizing a volume of sampled data based on a factorization of the viewing transformation into a shear and a warp. In shear-warp rendering, the volume is resampled, composited and warped to obtain
Selvanathan, N., Zakaria, Mohamed Nordin
core  

MFA-DVR: Direct Volume Rendering of MFA Models [PDF]

open access: green, 2022
Jianxin Sun   +3 more
openalex   +1 more source

Tumor and germline testing with next generation sequencing in epithelial ovarian cancer: a prospective paired comparison using an 18‐gene panel

open access: yesMolecular Oncology, EarlyView.
Genetic testing in epithelial ovarian cancer includes both germline and tumor‐testing. This approach often duplicates resources. The current prospective study assessed the feasibility of tumor‐first multigene testing by comparing tumor tissue with germline testing of peripheral blood using an 18‐gene NGS panel in 106 patients.
Elisabeth Spenard   +12 more
wiley   +1 more source

Screening for lung cancer: A systematic review of overdiagnosis and its implications

open access: yesMolecular Oncology, EarlyView.
Low‐dose computed tomography (CT) screening for lung cancer may increase overdiagnosis compared to no screening, though the risk is likely low versus chest X‐ray. Our review of 8 trials (84 660 participants) shows added costs. Further research with strict adherence to modern nodule management strategies may help determine the extent to which ...
Fiorella Karina Fernández‐Sáenz   +12 more
wiley   +1 more source

Single-image Tomography: 3D Volumes from 2D Cranial X-Rays [PDF]

open access: yes, 2018
As many different 3D volumes could produce the same 2D x-ray image, inverting this process is challenging. We show that recent deep learning-based convolutional neural networks can solve this task. As the main challenge in learning is the sheer amount of
Henzler, Philipp   +3 more
core   +1 more source

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