Encoding Neuroanatomical Information using Weighted Spherical Harmonic Representation

Chung, Moo K.; Dalton, Kim M.; Davidson, Richard J.

doi:10.1109/ssp.2007.4301236

Cited by 6 publications

(6 citation statements)

References 14 publications

(19 reference statements)

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“…Spherical harmonics have been extensively researched for the description of cortical surfaces (Fig. 8) [135,136,137]. An advantage of this representation is its robustness to noise when using lower frequency bands only, as noise is generally represented by higher frequencies.…”

Section: Descriptor Representationmentioning

confidence: 99%

A review of Surface Matching models: perspectives and challenges for Automatic Soft-Tissue Registration in Computer-assisted Interventions

Ramos¹

2015

E-Tech

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One of the main challenges related to Computer-Assisted Surgery (CAS) is the registration of multi-modal patient specific data to enhance the surgeon’s navigation capabilities by observing beyond the exposed tissue surface. One increasingly popular approach involves capturing the organ surface with a range imaging device and performing a shape-based registration. This paper (1) discusses the major challenges related to surface matching in the operating theater and (2) provides a general review of state-of-the-art methods in shape matching.

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Section: Descriptor Representationmentioning

confidence: 99%

A review of Surface Matching models: perspectives and challenges for Automatic Soft-Tissue Registration in Computer-assisted Interventions

Ramos¹

2015

E-Tech

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“…The method is applicable to the prostate (39), and also to breast cancer tumor (40), liver (41), kidney (42), heart (43), cortical surface of brain (44), and possibly others. Evidently, only linear deformation and isotropic conditions have been investigated and in order for the method to be more flexible, nonlinear and anisotropic situations have to be included in the model.…”

Section: Advantages and Limitationsmentioning

confidence: 99%

Haptic interaction of organs based on the spherical harmonic representation

Yang

Vegh

Tieng

et al. 2010

Concepts Magn Reson

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Visual and haptic organ interactions in real time are essential in virtual reality-based medical simulations to provide training, early diagnosis, and improved treatment planning. This work presents a robust method of computing the deformation of an elastic object when external forces are applied. Point-based haptic interaction between the user of the haptic device and an object is outlined and is formulated as a deformation problem over the surface. The model is expressed in the spherical harmonic basis, from which both haptic device force feedback and object surface updates are calculated. Haptic and visual updates are performed in the same basis, in turn providing significant benefits of computing efficiency and multiresolution modeling. Partially, this is due to the fact that in the model the objects are represented as surfaces. A haptic device is used to probe different prostates that have been segmented and reconstructed from MR images to validate the findings. The calculated deformation and feedback force is further validated against the established finite element method.

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“…Spherical Harmonics (SPHARM), a popular method of shape analysis, can be used to improve alignment accuracy and speed. Spherical harmonic analysis [131,132] considers 3D surface data as a linear combination of specific basis functions. Additionally, SPHARM provides a rotation invariant common coordinate system in which shapes can be analyzed.…”

Section: Spherical Harmonicsmentioning

confidence: 99%

“…The more coefficients used in the reconstruction, the more detail is present in the final constructed shape. Gerig et al [131], which have shown SPHARM as a potential method for classifying neurolog- [133] 1999 A 3D 21 N Gerig et al [131] 2001 A 3D 20 C Chung et al [132] 2007 A 3D 28 C Uthama et al [134] 2007 A 3D 40 C Abdallah et al [135] 2008 A 3D 18 C Chung et al [136] 2008 A 3D 28 C Uthama et al [137] 2008 A 3D 20 C Esmaeil-Zadeh et al [138] 2010 A 3D 95 N Nitzken et al [139] 2011 A 3D 45 C Nitzken et al [140] 2011 [142] 2011 A 3D n/a C Paniagua et al [86] 2013 A 3D 90 C Hosseinbor et al [143] 2013 A 3D 69 C ical disorders. SPHARM has been widely applied as a method for potential diagnosis.…”

Section: Spherical Harmonicsmentioning

confidence: 99%

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Shape analysis of the human brain.

Nitzken¹,

Joseph²

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DEDICATIONSometimes our light goes out but is blown into flame by another human being.Each of us owes deepest thanks to those who have rekindled this light. Autism is a complex developmental disability that has dramatically increased in prevalence, having a decisive impact on the health and behavior of children. Methods used to detect and recommend therapies have been much debated in the medical community because of the subjective nature of diagnosing autism. In order to provide an alternative method for understanding autism, the current work has developed a 3-dimensional state-of-the-art shape based analysis of the human brain to aid in creating more accurate diagnostic assessments and guided risk analyses for individuals with neurological conditions, such as autism. Methods:The aim of this work was to assess whether the shape of the human brain can be used as a reliable source of information for determining whether an individual will be diagnosed with autism. The study was conducted using multi-center databases of magnetic resonance images of the human brain. The subjects in the databases were analyzed using a series of algorithms consisting of bias correction, skull stripping, multi-label brain segmentation, 3-dimensional mesh construction, spherical harmonic decomposition, registration, and classification. The software algorithms were developed as an original contribution of this dissertation in collaboration with the BioImaging Laboratory at the University of Louisville Speed School of Engineering. The classification of each subject was used to construct diagnoses v and therapeutic risk assessments for each patient.Results: A reliable metric for making neurological diagnoses and constructing therapeutic risk assessment for individuals has been identified. The metric was explored in populations of individuals having autism spectrum disorders, dyslexia, Alzheimers disease, and lung cancer. Conclusion:Currently, the clinical applicability and benefits of the proposed software approach are being discussed by the broader community of doctors, therapists, and parents for use in improving current methods by which autism spectrum disorders are diagnosed and understood.vi

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Encoding Neuroanatomical Information using Weighted Spherical Harmonic Representation

Cited by 6 publications

References 14 publications

A review of Surface Matching models: perspectives and challenges for Automatic Soft-Tissue Registration in Computer-assisted Interventions

A review of Surface Matching models: perspectives and challenges for Automatic Soft-Tissue Registration in Computer-assisted Interventions

Haptic interaction of organs based on the spherical harmonic representation

Shape analysis of the human brain.

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