Fully Automated Hybrid Segmentation of the Brain

Atkins, M. Stella; Mackiewich, Blair T.

doi:10.1016/b978-012077790-7/50015-1

Cited by 8 publications

(5 citation statements)

References 23 publications

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“…How these variables are addressed influences the relationships found between quantitative magnetic resonance (MR) imaging and neuropsychological performance. With current quantification techniques, measurement of brain volume has become relatively straightforward and is usually based on the sum of total brain parenchymal volume determined by pixel counts within a region of interest (ROI) multiplied by slice thickness and gap between slices (Atkins & Mackiewich, 2000;Robb, 1995b;Schultz & Chakraborty, 1996). As a measure of cerebral atrophy, reduced brain volume generally is negatively associated with cognitive performance (Bigler et al, 2000;Gur et al, 2000), but it remains unclear whether there is a preferred method to measure atrophy or correct for head-size0brain size differences when investigating neuropsychological correlates.…”

Section: Introductionmentioning

confidence: 99%

Cerebral volume loss, cognitive deficit and neuropsychological performance: Comparative measures of brain atrophy: I. Dementia

Bigler

Neeley

Miller

et al. 2004

J. Inter. Neuropsych. Soc.

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There are several magnetic resonance (MR) imaging methods to measure brain volume and cerebral atrophy; however, the best measure for examining potential relationships between such measures and neuropsychological performance has not been established. Relationships between seven measures of MR derived brain volume or indices of atrophy and neuropsychological performance in the elderly subjects of the population-based Cache County, Utah Study of Aging and Memory (n = 195) were evaluated. The seven MR measures included uncorrected total brain volume (TBV), TBV corrected by total intracranial volume (TICV), TBV corrected by the ratio of the individuals TICV by group TICV (TBVC), a ventricle-to-brain ratio (VBR), total ventricular volume (TVV), TVV corrected by TICV, and a measure of parenchymal volume loss. The cases from the Cache County Study were comprised of elderly individuals classified into one of four subject groups based on a consensus diagnostic process, independent of quantitative MR imaging findings. The groups included subjects with Alzheimer's disease (AD, n = 85), no dementia but mild/ambiguous (M/A) deficits (n = 30), a group of subjects with non-AD dementia or neuropsychiatric disorder including vascular dementia (n = 60), and control subjects (n = 20). Neuropsychological performance was based on the Mini-Mental Status Exam (MMSE) and an expanded neuropsychological test battery (consortium to establish a registry for Alzheimer's disease (CERAD). The results demonstrated that the various quantitative MR measures were highly interrelated and no single measure was statistically superior. However, TBVC, TBV/TICV and VBR consistently exhibited the more robust relationships with neuropsychological performance. These results suggest that a single corrected brain volume measure or index is sufficient in studies examining global MR indicators of cerebral atrophy in relation to cognitive function and recommends use of either TBVC, TBV/TICV, or VBR.

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Section: Introductionmentioning

confidence: 99%

Cerebral volume loss, cognitive deficit and neuropsychological performance: Comparative measures of brain atrophy: I. Dementia

Bigler

Neeley

Miller

et al. 2004

J. Inter. Neuropsych. Soc.

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“…Here thresholding and active contour method can produce a good segmentation algorithm. Thresholding is used to find the edges in the image [6]. Finally two contours are merged together and form a common segmented image.…”

Section: Introductionmentioning

confidence: 99%

Automatic segmentation of chondroblastoma from X-ray images using active contour and levelset method

Anshad¹,

Kumar²

2018

IJET

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Chondroblastoma is a benign but locally aggressive bone tumor found usually in the age below 25 years. Chondroblastoma is a destructive type of lesion with a thin radio dense border which is normally seen in the epiphysis of long bones. The benign tumors have similarities in pathology and could be related with histogenic similarity. This tumor reduces the strength of affected bone and may leads to death if not treated early. Chondroblastoma can be diagnosed from X-ray/CT/MRI images and the treatment is its removal by surgical methods. Diagnosis of Chondroblastoma is difficult due to the similarities with other benign tumors like chondromyxoid fibroma. To reduce diagnostic errors, computer aided methods can adopt. This work focuses on automatic segmentation of Chondroblastoma using active contour and level set method which gives better segmentation results and a mild stone to CAD design.

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“…Yopak et al, 2009], subsequent inflation of the extracted surface onto a sphere to produce a single-valued function of the radial coordinate, and then fitting this surface with spherical harmonics up to some maximum order [Brechbuhler et al, 1995; Kazhdan et al, 2003]. Moreover, as demonstrated previously [Galinsky and Frank, 2014], this methodology is highly error-prone, because partial voluming (i.e., averaging of the intensities of different tissue types within a voxel) can blur tissue borders, complicating edge separation, resulting in topological defects in the inflated surface, which severely compromises the fitting process [Atkins and Mackiewich, 2000; Pham et al, 2000] and limits its utility in characterizing foliation. Galinsky and Frank [2014] have recently addressed this general problem of shape characterization of 3D volumetric data and demonstrated that a spherical wave decomposition (SWD) improves upon many of these limitations, as it facilitates automatic segmentation of high contrast data and allows for shape characterization of an entire volume, eliminating the need for manual segmentation and subsequent surface inflation.…”

Section: Introductionmentioning

confidence: 99%

Quantitative Classification of Cerebellar Foliation in Cartilaginous Fishes (Class: Chondrichthyes) Using Three-Dimensional Shape Analysis and Its Implications for Evolutionary Biology

et al. 2016

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A true cerebellum appeared at the onset of the chondrichthyan (sharks, batoids, and chimaerids) radiation and is known to be essential for executing fast, accurate, and efficient movement. In addition to a high degree of variation in size, the corpus cerebellum in this group has a high degree of variation in convolution (or foliation) and symmetry, which ranges from a smooth cerebellar surface to deep, branched convexities and folds, although the functional significance of this trait is unclear. As variation in the degree of foliation similarly exists throughout vertebrate evolution, it becomes critical to understand this evolutionary process in a wide variety of species. However, current methods are either qualitative and lack numerical rigor or they are restricted to two dimensions. In this paper, a recently developed method for the characterization of shapes embedded within noisy, three-dimensional data called spherical wave decomposition (SWD) is applied to the problem of characterizing cerebellar foliation in cartilaginous fishes. The SWD method provides a quantitative characterization of shapes in terms of well-defined mathematical functions. An additional feature of the SWD method is the construction of a statistical criterion for the optimal fit, which represents the most parsimonious choice of parameters that fits to the data without overfitting to background noise. We propose that this optimal fit can replace a previously described qualitative visual foliation index (VFI) in cartilaginous fishes with a quantitative analog, i.e. the cerebellar foliation index (CFI). The capability of the SWD method is demonstrated in a series of volumetric images of brains from different chondrichthyan species that span the range of foliation gradings currently described for this group. The CFI is consistent with the qualitative grading provided by the VFI, delivers a robust measure of cerebellar foliation, and can provide a quantitative basis for brain shape characterization across taxa.

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Fully Automated Hybrid Segmentation of the Brain

Cited by 8 publications

References 23 publications

Cerebral volume loss, cognitive deficit and neuropsychological performance: Comparative measures of brain atrophy: I. Dementia

Cerebral volume loss, cognitive deficit and neuropsychological performance: Comparative measures of brain atrophy: I. Dementia

Automatic segmentation of chondroblastoma from X-ray images using active contour and levelset method

Quantitative Classification of Cerebellar Foliation in Cartilaginous Fishes (Class: Chondrichthyes) Using Three-Dimensional Shape Analysis and Its Implications for Evolutionary Biology

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