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  1. Article: The Fractal Geometry of the Brain: AnOverview.

    Di Ieva, Antonio

    Advances in neurobiology

    2024  Volume 36, Page(s) 3–13

    Abstract: The first chapter of this book introduces some history, philosophy, and basic concepts of fractal geometry and discusses how the neurosciences can benefit from applying computational fractal-based analysis. Further, it compares fractal with Euclidean ... ...

    Abstract The first chapter of this book introduces some history, philosophy, and basic concepts of fractal geometry and discusses how the neurosciences can benefit from applying computational fractal-based analysis. Further, it compares fractal with Euclidean approaches to analyzing and quantifying the brain in its entire physiopathological spectrum and presents an overview of the first section of this book as well.
    Language English
    Publishing date 2024-03-11
    Publishing country United States
    Document type Journal Article
    ISSN 2190-5215
    ISSN 2190-5215
    DOI 10.1007/978-3-031-47606-8_1
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article: Fractal Analysis in Clinical Neurosciences: An Overview.

    Di Ieva, Antonio

    Advances in neurobiology

    2024  Volume 36, Page(s) 261–271

    Abstract: Over the last years, fractals have entered into the realms of clinical neurosciences. The whole brain and its components (i.e., neurons and astrocytes) have been studied as fractal objects, and even more relevant, the fractal-based quantification of the ... ...

    Abstract Over the last years, fractals have entered into the realms of clinical neurosciences. The whole brain and its components (i.e., neurons and astrocytes) have been studied as fractal objects, and even more relevant, the fractal-based quantification of the geometrical complexity of histopathological and neuroradiological images as well as neurophysiopathological time series has suggested the existence of a gradient in the pattern representation of neurological diseases. Computational fractal-based parameters have been suggested as potential diagnostic and prognostic biomarkers in different brain diseases, including brain tumors, neurodegeneration, epilepsy, demyelinating diseases, cerebrovascular malformations, and psychiatric disorders as well. This chapter and the entire third section of this book are focused on practical applications of computational fractal-based analysis into the clinical neurosciences, namely, neurology and neuropsychiatry, neuroradiology and neurosurgery, neuropathology, neuro-oncology and neurorehabilitation, neuro-ophthalmology, and cognitive neurosciences, with special emphasis on the translation of the fractal dimension and other fractal parameters as clinical biomarkers useful from bench to bedside.
    MeSH term(s) Humans ; Biomarkers ; Brain/pathology ; Brain Neoplasms/diagnostic imaging ; Epilepsy ; Fractals
    Chemical Substances Biomarkers
    Language English
    Publishing date 2024-03-11
    Publishing country United States
    Document type Journal Article ; Review
    ISSN 2190-5215
    ISSN 2190-5215
    DOI 10.1007/978-3-031-47606-8_13
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: Fractals in Neuroanatomy and Basic Neurosciences: An Overview.

    Di Ieva, Antonio

    Advances in neurobiology

    2024  Volume 36, Page(s) 141–147

    Abstract: The introduction of fractal geometry to the neurosciences has been a major paradigm shift over the last decades as it has helped overcome approximations and limitations that occur when Euclidean and reductionist approaches are used to analyze neurons or ... ...

    Abstract The introduction of fractal geometry to the neurosciences has been a major paradigm shift over the last decades as it has helped overcome approximations and limitations that occur when Euclidean and reductionist approaches are used to analyze neurons or the entire brain. Fractal geometry allows for quantitative analysis and description of the geometric complexity of the brain, from its single units to the neuronal networks.As illustrated in the second section of this book, fractal analysis provides a quantitative tool for the study of the morphology of brain cells (i.e., neurons and microglia) and its components (e.g., dendritic trees, synapses), as well as the brain structure itself (cortex, functional modules, neuronal networks). The self-similar logic which generates and shapes the different hierarchical systems of the brain and even some structures related to its "container," that is, the cranial sutures on the skull, is widely discussed in the following chapters, with a link between the applications of fractal analysis to the neuroanatomy and basic neurosciences to the clinical applications discussed in the third section.
    MeSH term(s) Humans ; Brain/physiology ; Fractals ; Neuroanatomy ; Neurons
    Language English
    Publishing date 2024-03-11
    Publishing country United States
    Document type Journal Article ; Review
    ISSN 2190-5215
    ISSN 2190-5215
    DOI 10.1007/978-3-031-47606-8_6
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article: Fractals, Pattern Recognition, Memetics, and AI: A Personal Journal in the Computational Neurosurgery.

    Di Ieva, Antonio

    Advances in neurobiology

    2024  Volume 36, Page(s) 273–283

    Abstract: In this chapter, the personal journey of the author in many countries, including Italy, Germany, Austria, the United Kingdom, Switzerland, the United States, Canada, and Australia, is summarized, aimed to merge different translational fields (such as ... ...

    Abstract In this chapter, the personal journey of the author in many countries, including Italy, Germany, Austria, the United Kingdom, Switzerland, the United States, Canada, and Australia, is summarized, aimed to merge different translational fields (such as neurosurgery and the clinical neurosciences in general, biomedical engineering, mathematics, computer science, and cognitive sciences) and lay the foundations of a new field defined computational neurosurgery, with fractals, pattern recognition, memetics, and artificial intelligence as the common key words of the journey.
    MeSH term(s) United States ; Humans ; Fractals ; Artificial Intelligence ; Neurosurgery
    Language English
    Publishing date 2024-03-12
    Publishing country United States
    Document type Journal Article
    ISSN 2190-5215
    ISSN 2190-5215
    DOI 10.1007/978-3-031-47606-8_14
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article: Computational Fractal-Based Analysis of MR Susceptibility-Weighted Imaging (SWI) in Neuro-Oncology and Neurotraumatology.

    Di Ieva, Antonio

    Advances in neurobiology

    2024  Volume 36, Page(s) 445–468

    Abstract: Susceptibility-weighted imaging (SWI) is a magnetic resonance imaging (MRI) technique able to depict the magnetic susceptibility produced by different substances, such as deoxyhemoglobin, calcium, and iron. The main application of SWI in clinical ... ...

    Abstract Susceptibility-weighted imaging (SWI) is a magnetic resonance imaging (MRI) technique able to depict the magnetic susceptibility produced by different substances, such as deoxyhemoglobin, calcium, and iron. The main application of SWI in clinical neuroimaging is detecting microbleedings and venous vasculature. Quantitative analyses of SWI have been developed over the last few years, aimed to offer new parameters, which could be used as neuroimaging biomarkers. Each technique has shown pros and cons, but no gold standard exists yet. The fractal dimension (FD) has been investigated as a novel potential objective parameter for monitoring intratumoral space-filling properties of SWI patterns. We showed that SWI patterns found in different tumors or different glioma grades can be represented by a gradient in the fractal dimension, thereby enabling each tumor to be assigned a specific SWI fingerprint. Such results were especially relevant in the differentiation of low-grade versus high-grade gliomas, as well as from high-grade gliomas versus lymphomas.Therefore, FD has been suggested as a potential image biomarker to analyze intrinsic neoplastic architecture in order to improve the differential diagnosis within clinical neuroimaging, determine appropriate therapy, and improve outcome in patients.These promising preliminary findings could be extended into the field of neurotraumatology, by means of the application of computational fractal-based analysis for the qualitative and quantitative imaging of microbleedings in traumatic brain injury patients. In consideration of some evidences showing that SWI signals are correlated with trauma clinical severity, FD might offer some objective prognostic biomarkers.In conclusion, fractal-based morphometrics of SWI could be further investigated to be used in a complementary way with other techniques, in order to form a holistic understanding of the temporal evolution of brain tumors and follow-up response to treatment, with several further applications in other fields, such as neurotraumatology and cerebrovascular neurosurgery as well.
    MeSH term(s) Humans ; Fractals ; Brain Neoplasms/diagnostic imaging ; Glioma ; Magnetic Resonance Imaging/methods ; Biomarkers
    Chemical Substances Biomarkers
    Language English
    Publishing date 2024-03-12
    Publishing country United States
    Document type Journal Article
    ISSN 2190-5215
    ISSN 2190-5215
    DOI 10.1007/978-3-031-47606-8_23
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article: Computational and Translational Fractal-Based Analysis in the Translational Neurosciences: An Overview.

    Di Ieva, Antonio

    Advances in neurobiology

    2024  Volume 36, Page(s) 781–793

    Abstract: After the previous sections on "Fractals: What and Why?," the last section of this book covers the software tools necessary to perform computational fractal-based analysis, with special emphasis on its applications into the neurosciences. The use of ... ...

    Abstract After the previous sections on "Fractals: What and Why?," the last section of this book covers the software tools necessary to perform computational fractal-based analysis, with special emphasis on its applications into the neurosciences. The use of ImageJ and MATLAB, as well as other software packages, is reviewed. The current and future applications of fractal modeling in bioengineering and biotechnology are discussed as well. Perspectives on the translation of merging fractals with artificial intelligence-based methods with the final aim of pattern discrimination in neurological diseases by means of a unified fractal model of the brain are also given. Moreover, some new translational applications of fractal analysis to the neurosciences are presented, including eye tracking analysis, cognitive neuroscience, and music.
    MeSH term(s) Humans ; Fractals ; Artificial Intelligence ; Software ; Brain
    Language English
    Publishing date 2024-03-12
    Publishing country United States
    Document type Review ; Journal Article
    ISSN 2190-5215
    ISSN 2190-5215
    DOI 10.1007/978-3-031-47606-8_39
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  7. Article: Fractal-Based Analysis of Arteriovenous Malformations (AVMs).

    Di Ieva, Antonio / Reishofer, Gernot

    Advances in neurobiology

    2024  Volume 36, Page(s) 413–428

    Abstract: Arteriovenous malformations (AVMs) are cerebrovascular lesions consisting of a pathologic tangle of the vessels characterized by a core termed the nidus, which is the "nest" where the fistulous connections occur. AVMs can cause headache, stroke, and/or ... ...

    Abstract Arteriovenous malformations (AVMs) are cerebrovascular lesions consisting of a pathologic tangle of the vessels characterized by a core termed the nidus, which is the "nest" where the fistulous connections occur. AVMs can cause headache, stroke, and/or seizures. Their treatment can be challenging requiring surgery, endovascular embolization, and/or radiosurgery as well. AVMs' morphology varies greatly among patients, and there is still a lack of standardization of angioarchitectural parameters, which can be used as morphometric parameters as well as potential clinical biomarkers (e.g., related to prognosis).In search of new diagnostic and prognostic neuroimaging biomarkers of AVMs, computational fractal-based models have been proposed for describing and quantifying the angioarchitecture of the nidus. In fact, the fractal dimension (FD) can be used to quantify AVMs' branching pattern. Higher FD values are related to AVMs characterized by an increased number and tortuosity of the intranidal vessels or to an increasing angioarchitectural complexity as a whole. Moreover, FD has been investigated in relation to the outcome after Gamma Knife radiosurgery, and an inverse relationship between FD and AVM obliteration was found.Taken altogether, FD is able to quantify in a single and objective value what neuroradiologists describe in qualitative and/or semiquantitative way, thus confirming FD as a reliable morphometric neuroimaging biomarker of AVMs and as a potential surrogate imaging biomarker. Moreover, computational fractal-based techniques are under investigation for the automatic segmentation and extraction of the edges of the nidus in neuroimaging, which can be relevant for surgery and/or radiosurgery planning.
    MeSH term(s) Humans ; Intracranial Arteriovenous Malformations/diagnostic imaging ; Intracranial Arteriovenous Malformations/surgery ; Fractals ; Retrospective Studies ; Prognosis ; Biomarkers
    Chemical Substances Biomarkers
    Language English
    Publishing date 2024-03-12
    Publishing country United States
    Document type Journal Article
    ISSN 2190-5215
    ISSN 2190-5215
    DOI 10.1007/978-3-031-47606-8_21
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article: Debunking the debulking in glioma surgery.

    Di Ieva, Antonio

    Neuro-oncology practice

    2022  Volume 10, Issue 1, Page(s) 104–105

    Language English
    Publishing date 2022-10-26
    Publishing country England
    Document type Journal Article
    ZDB-ID 2768945-1
    ISSN 2054-2585 ; 2054-2577
    ISSN (online) 2054-2585
    ISSN 2054-2577
    DOI 10.1093/nop/npac083
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Book: Handbook of skull base surgery

    Di Ieva, Antonio / Lee, John M. / Cusimano, Michael D.

    2016  

    Language English
    Size XXVI, 978 S. : Ill., graph. Darst., 15.2 cm x 22.9 cm
    Publisher Thieme
    Publishing place New York u.a.
    Publishing country Germany
    Document type Book
    HBZ-ID HT018929362
    ISBN 978-1-62623-025-5 ; 978-1-62623-026-2 ; 1-62623-025-0 ; 1-62623-026-9
    Database Catalogue ZB MED Medicine, Health

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    In stock of ZB MED Cologne/Königswinter

    Shelf markLoan statusLocation
    2016 A 777 on loan 0 Vormerkungen

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  10. Article: Analyzing Eye Paths Using Fractals.

    Newport, Robert Ahadizad / Liu, Sidong / Di Ieva, Antonio

    Advances in neurobiology

    2024  Volume 36, Page(s) 827–848

    Abstract: Visual patterns reflect the anatomical and cognitive background underlying process governing how we perceive information, influenced by stimulus characteristics and our own visual perception. These patterns are both spatially complex and display self- ... ...

    Abstract Visual patterns reflect the anatomical and cognitive background underlying process governing how we perceive information, influenced by stimulus characteristics and our own visual perception. These patterns are both spatially complex and display self-similarity seen in fractal geometry at different scales, making them challenging to measure using the traditional topological dimensions used in Euclidean geometry.However, methods for measuring eye gaze patterns using fractals have shown success in quantifying geometric complexity, matchability, and implementation into machine learning methods. This success is due to the inherent capabilities that fractals possess when reducing dimensionality using Hilbert curves, measuring temporal complexity using the Higuchi fractal dimension (HFD), and determining geometric complexity using the Minkowski-Bouligand dimension.Understanding the many applications of fractals when measuring and analyzing eye gaze patterns can extend the current growing body of knowledge by identifying markers tied to neurological pathology. Additionally, in future work, fractals can facilitate defining imaging modalities in eye tracking diagnostics by exploiting their capability to acquire multiscale information, including complementary functions, structures, and dynamics.
    MeSH term(s) Humans ; Fractals
    Language English
    Publishing date 2024-03-12
    Publishing country United States
    Document type Journal Article
    ISSN 2190-5215
    ISSN 2190-5215
    DOI 10.1007/978-3-031-47606-8_42
    Database MEDical Literature Analysis and Retrieval System OnLINE

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