Assessing biological self-organization patterns using statistical complexity characteristics: a tool for diffusion tensor imaging analysis.

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Bibliographic Details
Title: Assessing biological self-organization patterns using statistical complexity characteristics: a tool for diffusion tensor imaging analysis.
Authors: da S Senra Filho AC; Department of Cosmic Rays and Chronology, University of Campinas, São Paulo, Brazil. acsenrafilho@alumni.usp.br., Murta Junior LO; Department of Computing and Mathematics, University of Sao Paulo, São Paulo, Brazil., Monteiro Paschoal A; Department of Cosmic Rays and Chronology, University of Campinas, São Paulo, Brazil.
Source: Magma (New York, N.Y.) [MAGMA] 2025 Aug; Vol. 38 (4), pp. 653-663. Date of Electronic Publication: 2024 Jul 28.
Publication Type: Journal Article
Journal Info: Publisher: Springer Country of Publication: Germany NLM ID: 9310752 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1352-8661 (Electronic) Linking ISSN: 09685243 NLM ISO Abbreviation: MAGMA Subsets: MEDLINE
Database: MEDLINE Ultimate
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