Skip to main content
CenXiv.org
This website is in trial operation, support us!
We gratefully acknowledge support from all contributors.
Contribute
Donate
cenxiv logo > math > arXiv:1212.3967

Help | Advanced Search

Mathematics > Numerical Analysis

arXiv:1212.3967 (math)
[Submitted on 17 Dec 2012 ]

Title: Compartmental analysis of renal physiology using nuclear medicine data and statistical optimization

Title: 肾生理学的分室分析,使用核医学数据和统计优化

Authors:Sara Garbarino, Giacomo Caviglia, Massimo Brignone, Michela Massollo, Gianmario Sambuceti, Michele Piana
Abstract: This paper describes a general approach to the compartmental modeling of nuclear data based on spectral analysis and statistical optimization. We utilize the renal physiology as test case and validate the method against both synthetic data and real measurements acquired during two micro-PET experiments with murine models.
Abstract: 本文描述了一种基于谱分析和统计优化的核数据隔室建模的一般方法。 我们以肾生理学作为测试案例,并利用两种微PET实验中获得的合成数据和实际测量结果对该方法进行验证。
Comments: submitted to SIAM Journal on Applied Mathematics
Subjects: Numerical Analysis (math.NA) ; Medical Physics (physics.med-ph); Tissues and Organs (q-bio.TO); Applications (stat.AP)
MSC classes: 65L09, 62P10
Cite as: arXiv:1212.3967 [math.NA]
  (or arXiv:1212.3967v1 [math.NA] for this version)
  https://doi.org/10.48550/arXiv.1212.3967
arXiv-issued DOI via DataCite

Submission history

From: Michele Piana [view email]
[v1] Mon, 17 Dec 2012 12:04:33 UTC (3,247 KB)
Full-text links:

Access Paper:

    View a PDF of the paper titled
  • View Chinese PDF
  • View PDF
  • TeX Source
view license
Current browse context:
math.NA
< prev   |   next >
new | recent | 2012-12
Change to browse by:
math
physics
physics.med-ph
q-bio
q-bio.TO
stat
stat.AP

References & Citations

  • NASA ADS
  • Google Scholar
  • Semantic Scholar
a export BibTeX citation Loading...

BibTeX formatted citation

×
Data provided by:

Bookmark

BibSonomy logo Reddit logo

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
Papers with Code (What is Papers with Code?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
IArxiv Recommender (What is IArxiv?)
  • Author
  • Venue
  • Institution
  • Topic

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
  • About
  • Help
  • contact arXivClick here to contact arXiv Contact
  • subscribe to arXiv mailingsClick here to subscribe Subscribe
  • Copyright
  • Privacy Policy
  • Web Accessibility Assistance
  • arXiv Operational Status
    Get status notifications via email or slack

京ICP备2025123034号