Journal ArticleDOI
Hough transform detection of the longitudinal fissure in tomographic head images
TLDR
The Sobel magnitude edge operator, used for preprocessing, proved adequate for magnetic resonance scans with positive and negative brain/cerebrospinal fluid contrast and is a three-dimensional variant of the Hough transform principle.Abstract:
A technique is presented for automatic detection of the longitudinal fissure in tomographic scans of the brain. The technique utilizes the planar nature of the fissure and is a three-dimensional variant of the Hough transform principle. Algorithmic and computational aspects of the technique are discussed. Results and performance on coronal and transaxial magnetic resonance data show that the algorithm is robust with respect to variations in image contrast in the data and to slight anatomic anomalies. A crucial resolution requirement in the data for accurate parameter estimations is a sufficient number of slices covering the whole brain. The Sobel magnitude edge operator, used for preprocessing, proved adequate for magnetic resonance scans with positive and negative brain/cerebrospinal fluid contrast. >read more
Citations
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Journal ArticleDOI
A survey of Hough Transform
TL;DR: A survey of Hough Transform and its variants, their limitations and the modifications made to overcome them, the implementation issues in software and hardware, and applications in various fields is done.
Journal ArticleDOI
volBrain: An Online MRI Brain Volumetry System
José V. Manjón,Pierrick Coupé +1 more
TL;DR: In this article, the authors present a fully automatic pipeline for volumetric brain analysis based on multi-atlas label fusion technology, which is able to provide accurate information at different levels of detail in a short time.
Journal ArticleDOI
A modality-independent approach to spatial normalization of tomographic images of the human brain
Jack L. Lancaster,T. Glass,Bhujanga R. Lankipalli,Hunter Downs,Helen S. Mayberg,Peter T. Fox +5 more
TL;DR: A modality‐independent approch for interactive spatial normalization of tomographic images of the human brain is described and its performance evaluated.
Book ChapterDOI
ANIMAL+INSECT: Improved Cortical Structure Segmentation
TL;DR: An algorithm for improved automatic segmentation of gross anatomical structures of the human brain is presented that merges the output of a tissue classification process with gross anatomical region masks, automatically defined by non-linear registration of a given data set with a probabilistic anatomical atlas.
Journal ArticleDOI
Computation of the mid-sagittal plane in 3-D brain images
TL;DR: A new method to automatically compute, reorient, and recenter the mid-sagittal plane in anatomical and functional three-dimensional (3-D) brain images, which is fast and accurate, even for strongly tilted heads, and even in presence of high acquisition noise and bias field.
References
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Snakes : Active Contour Models
TL;DR: This work uses snakes for interactive interpretation, in which user-imposed constraint forces guide the snake near features of interest, and uses scale-space continuation to enlarge the capture region surrounding a feature.
Journal ArticleDOI
Use of the Hough transformation to detect lines and curves in pictures
Richard O. Duda,Peter E. Hart +1 more
TL;DR: It is pointed out that the use of angle-radius rather than slope-intercept parameters simplifies the computation further, and how the method can be used for more general curve fitting.
Journal ArticleDOI
Generalizing the hough transform to detect arbitrary shapes
TL;DR: It is shown how the boundaries of an arbitrary non-analytic shape can be used to construct a mapping between image space and Hough transform space, which makes the generalized Houghtransform a kind of universal transform which can beused to find arbitrarily complex shapes.
Journal ArticleDOI
Distance transformations in arbitrary dimensions
TL;DR: The purpose of this paper is to generalize these distance transformation families to higher dimensions and to compare the computed distances with the Euclidean distance.