Scan-conversion algorithm for ridge point detection on tubular objects

Sukmoon Chang, Dimitris N. Metaxas, Leon Axel

Research output: Contribution to journalConference article

10 Citations (Scopus)

Abstract

Anatomical structures contain various types of curvilinear or tube-like structures such as blood vessels and bronchial trees. In medical imaging, the extraction and representation of such structures are of clinical importance. Complex curvilinear structures can be best represented by their center lines (or skeletons) along their elongated direction. In this paper, & gradient-based method for ridge point extraction on tubular objects is presented. Using the gradients of distance maps or intensity profiles usually generates skeleton surfaces for 3D objects, which is not desirable for representing tubular objects. To extract only the points on the centerline, we first employ the gradient vector flow (GVF) technique and then apply eigenanalysis of the Hessian matrix to remove false positive points. We present various results of the method using CLSM (Confocal Laser Scanning Microscopy) images of blood fibrins and CT images of a skull and lungs. Our method is efficient and allows for completely automatic extraction of points along the centerline of a tubular object in its elongated direction.

Original languageEnglish (US)
Pages (from-to)158-165
Number of pages8
JournalLecture Notes in Computer Science
Volume2879
Issue numberPART 2
StatePublished - Dec 1 2003
EventMedical Image Computing and Computer-Assisted Intervention, MICCAI 2003 - 6th International Conference Proceedings - Montreal, Que., Canada
Duration: Nov 15 2003Nov 18 2003

Fingerprint

Ridge
Skeleton
Gradient Vector Flow
Blood vessels
Medical imaging
Gradient
Hessian matrix
CT Image
Laser Scanning
Confocal
Blood Vessels
Medical Imaging
Microscopic examination
Blood
Lung
False Positive
Microscopy
Scanning
Tube
Lasers

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Chang, Sukmoon ; Metaxas, Dimitris N. ; Axel, Leon. / Scan-conversion algorithm for ridge point detection on tubular objects. In: Lecture Notes in Computer Science. 2003 ; Vol. 2879, No. PART 2. pp. 158-165.
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Scan-conversion algorithm for ridge point detection on tubular objects. / Chang, Sukmoon; Metaxas, Dimitris N.; Axel, Leon.

In: Lecture Notes in Computer Science, Vol. 2879, No. PART 2, 01.12.2003, p. 158-165.

Research output: Contribution to journalConference article

TY - JOUR

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AU - Metaxas, Dimitris N.

AU - Axel, Leon

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N2 - Anatomical structures contain various types of curvilinear or tube-like structures such as blood vessels and bronchial trees. In medical imaging, the extraction and representation of such structures are of clinical importance. Complex curvilinear structures can be best represented by their center lines (or skeletons) along their elongated direction. In this paper, & gradient-based method for ridge point extraction on tubular objects is presented. Using the gradients of distance maps or intensity profiles usually generates skeleton surfaces for 3D objects, which is not desirable for representing tubular objects. To extract only the points on the centerline, we first employ the gradient vector flow (GVF) technique and then apply eigenanalysis of the Hessian matrix to remove false positive points. We present various results of the method using CLSM (Confocal Laser Scanning Microscopy) images of blood fibrins and CT images of a skull and lungs. Our method is efficient and allows for completely automatic extraction of points along the centerline of a tubular object in its elongated direction.

AB - Anatomical structures contain various types of curvilinear or tube-like structures such as blood vessels and bronchial trees. In medical imaging, the extraction and representation of such structures are of clinical importance. Complex curvilinear structures can be best represented by their center lines (or skeletons) along their elongated direction. In this paper, & gradient-based method for ridge point extraction on tubular objects is presented. Using the gradients of distance maps or intensity profiles usually generates skeleton surfaces for 3D objects, which is not desirable for representing tubular objects. To extract only the points on the centerline, we first employ the gradient vector flow (GVF) technique and then apply eigenanalysis of the Hessian matrix to remove false positive points. We present various results of the method using CLSM (Confocal Laser Scanning Microscopy) images of blood fibrins and CT images of a skull and lungs. Our method is efficient and allows for completely automatic extraction of points along the centerline of a tubular object in its elongated direction.

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