&lt;title&gt;3D catheter path reconstruction from biplane angiograms&lt;/title&gt;

Molina, M.C.; Prause, Guido P. M.; Radeva, Petia; Sonka, Milan

doi:10.1117/12.310929

Cited by 27 publications

(11 citation statements)

References 9 publications

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“…However, problems may still occur if the cost matrix approach is applied to self-intersecting or highly ambiguous vessels. Thus, possible future extensions may include the development of a knowledge-based graph-oriented search along epipolar planes [58], or may utilize active contours (snakes) for extraction of the catheter path in the angiograms and the 3-D reconstruction in a single step [59].…”

Section: Discussionmentioning

confidence: 99%

Geometrically correct 3-D reconstruction of intravascular ultrasound images by fusion with biplane angiography-methods and validation

Wahle

Prause

DeJong

et al. 1999

IEEE Trans. Med. Imaging

159

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Abstract-In the rapidly evolving field of intravascular ultrasound (IVUS), the assessment of vessel morphology still lacks a geometrically correct 3-D reconstruction. The IVUS frames are usually stacked up to form a straight vessel, neglecting curvature and the axial twisting of the catheter during the pullback. Our method combines the information about vessel cross-sections obtained from IVUS with the information about the vessel geometry derived from biplane angiography. First, the catheter path is reconstructed from its biplane projections, resulting in a spatial model. The locations of the IVUS frames are determined and their orientations relative to each other are calculated using a discrete approximation of the Frenet-Serret formulas known from differential geometry. The absolute orientation of the frame set is established utilizing the imaging catheter itself as an artificial landmark. The IVUS images are segmented using our previously developed algorithm. The fusion approach has been extensively validated in computer simulations, phantoms, and cadaveric pig hearts.

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Section: Discussionmentioning

confidence: 99%

Geometrically correct 3-D reconstruction of intravascular ultrasound images by fusion with biplane angiography-methods and validation

Wahle

Prause

DeJong

et al. 1999

IEEE Trans. Med. Imaging

159

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“…(B-Spline) space curve snakes have been chosen as basis for centerline determination in 3D MRA [29], and for reconstruction of catheter paths [67] or the whole vessel topology [12,83] from bi-plane angiograms. Frangi et al [29] also propose surface snakes represented by tensor product B-spline surfaces to model vessel walls.…”

Section: Snakesmentioning

confidence: 99%

Geometric Methods for Vessel Visualization and Quantification — A Survey

Bühler

Felkel

Cruz

2004

Geometric Modeling for Scientific Visualization

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Summary. Visualization and quantitative analysis of vessel data is an important preprocessing step in diagnosis of vascular diseases, monitoring, surgery planning, blood flow simulation, education and training of surgeons. This paper surveys several geometrie methods to solve basie visualization and quantification problems like centerline computation, boundary detection, projection teehniques, and geometrie model generation.

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“…There are several existing segmentation methods but all of them failed to extract the blood vessel from every single medical image. However, some methods make use of pure intensity-based pattern recognition techniques, such as threshold, followed by the connected neighborhood component analysis [5,6] and some other techniques incorporate explicit vessel models for the extraction of vessel contours [7][8][9]. Prior to applying segmentation algorithm, some methods may possibly need image pre-processing depending on the image characteristics and the general image artifacts, for example noise [10,11].…”

Section: Introductionmentioning

confidence: 99%

A New Blood Vessel Extraction Technique Using Edge Enhancement and Object Classification

et al. 2013

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Diabetic retinopathy (DR) is increasing progressively pushing the demand of automatic extraction and classification of severity of diseases. Blood vessel extraction from the fundus image is a vital and challenging task. Therefore, this paper presents a new, computationally simple, and automatic method to extract the retinal blood vessel. The proposed method comprises several basic image processing techniques, namely edge enhancement by standard template, noise removal, thresholding, morphological operation, and object classification. The proposed method has been tested on a set of retinal images. The retinal images were collected from the DRIVE database and we have employed robust performance analysis to evaluate the accuracy. The results obtained from this study reveal that the proposed method offers an average accuracy of about 97 %, sensitivity of 99 %, specificity of 86 %, and predictive value of 98 %, which is superior to various wellknown techniques.

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<title>3D catheter path reconstruction from biplane angiograms</title>

Cited by 27 publications

References 9 publications

Geometrically correct 3-D reconstruction of intravascular ultrasound images by fusion with biplane angiography-methods and validation

Geometrically correct 3-D reconstruction of intravascular ultrasound images by fusion with biplane angiography-methods and validation

Geometric Methods for Vessel Visualization and Quantification — A Survey

A New Blood Vessel Extraction Technique Using Edge Enhancement and Object Classification

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