2006
DOI: 10.1109/tmi.2005.862151
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Super-resolution registration using tissue-classified distance fields

Abstract: Abstract-We present a method for registering the position and orientation of bones across multiple computed-tomography (CT) volumes of the same subject. The method is subvoxel accurate, can operate on multiple bones within a set of volumes, and registers bones that have features commensurate in size to the voxel dimension. First, a geometric object model is extracted from a reference volume image. We use then unsupervised tissue classification to generate from each volume to be registered a super-resolution di… Show more

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Cited by 46 publications
(38 citation statements)
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“…The absolute positions of the trapezium and first metacarpal within the global imaging space were computed with an established automatic markerless bone registration algorithm [20]. Kinematic transforms for motion of the first metacarpal with respect to the trapezium were then computed for ten separate pairs of positions: neutral to flexion, neutral to adduction, neutral to extension, neutral to abduction, extension to flexion, abduction to adduction, extension to abduction, abduction to flexion, adduction to extension, and flexion to adduction.…”
Section: Methodsmentioning
confidence: 99%
“…The absolute positions of the trapezium and first metacarpal within the global imaging space were computed with an established automatic markerless bone registration algorithm [20]. Kinematic transforms for motion of the first metacarpal with respect to the trapezium were then computed for ten separate pairs of positions: neutral to flexion, neutral to adduction, neutral to extension, neutral to abduction, extension to flexion, abduction to adduction, extension to abduction, abduction to flexion, adduction to extension, and flexion to adduction.…”
Section: Methodsmentioning
confidence: 99%
“…1B). Six-degree-offreedom kinematics from the neutral position to each of the remaining six positions were determined for each bone with a markerless bone registration algorithm [22]. Kinematics of the first metacarpal with respect to the trapezium were then expressed in terms of a CMC joint coordinate system that describes flexion/extension about an anatomically oriented ulnar-radial axis embedded in the trapezium (X TPM ), adduction/abduction about an anatomicallyoriented dorsal-volar axis embedded in the metacarpal (Z MC1 ), and internal/external rotation about a distalproximal axis (Y) perpendicular to both of the body-fixed Values are expressed as mean ± one SD.…”
Section: Bone Kinematicsmentioning
confidence: 99%
“…Here we present an analysis of normal CMC joint kinematics during high-demand functional tasks, using established CT-based markerless bone registration methods of submillimeter and subdegree accuracy [22]. Grasping and precision handling manipulations constitute 40% of hand function [30] and rely heavily on thumb support; therefore, three tasks that utilize those maneuvers were chosen for the study: lateral key pinch, jar grasp, and jar twist.…”
Section: Introductionmentioning
confidence: 99%
“…[12][13][14] To simplify comparison of the malunited and uninjured wrists, the CT volume of the left wrist from each subject was mathematically transformed so that it looked like a right wrist. [12][13][14] In brief, the transformation involved multiplication of the X coordinate of the bone surface contours by À1 and reversing the direction of the contours in each CT image slice. This transformation made the bone shapes and motions of the left wrists directly comparable to the right wrists.…”
Section: Kinematic Analysismentioning
confidence: 99%