Fast Detection and Processing of Arbitrary Contrast Agent Injections in Coronary Angiography and Fluoroscopy

Condurache, Alexandru Paul; Aach, Til; Eck, Kai; Bredno, Joerg

doi:10.1007/978-3-642-18536-6_2

Cited by 13 publications

(25 citation statements)

References 6 publications

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“…4. In order to provide automatic roadmapping [2], the algorithm needs to know when the contrast agent appears in the fluoroscopy to disable the overlay. All these interventional procedures can be streamlined with a robust and automatic contrast inflow detection algorithm such that the physician can obtain desired information with less interactions or constraints.…”

Section: Introductionmentioning

confidence: 99%

“…Nevertheless, this works poorly in practice since moving diaphragm and other darker regions can often appear in cardiac Xray images and mislead the algorithm. Condurache [2] et al proposed a method which applies morphological operations and a difference of Gaussians (DoG) filter to generate a vessel map. A threshold is then applied to the histogram of the vessel map to decide whether contrast medium appears.…”

Section: Introductionmentioning

confidence: 99%

“…Previous methods such as [2] were evaluated only on a limited number of data sets and are with empirically set parameters. They can hardly be generalized to work in different clinical applications.…”

Section: Introductionmentioning

confidence: 99%

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Robust and Fast Contrast Inflow Detection for 2D X-ray Fluoroscopy

Chen

Funka-Lea

Comanicìu

2011

Lecture Notes in Computer Science

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Abstract. 2D X-ray fluoroscopy is widely used in computer assisted and image guided interventions because of the real time visual guidance it can provide to the physicians. During cardiac interventions, acquisitions of angiography are often used to assist the physician in visualizing the blood vessel structures, guide wires, or catheters, localizing bifurcations, estimating severity of a lesion, or observing the blood flow. Computational algorithms often need to process differently to frames with or without contrast medium. In order to automate this process and streamline the clinical workflow, a fully automatic contrast inflow detection algorithm is proposed. The robustness of the algorithm is validated by more than 1300 real fluoroscopic scenes. The algorithm is computationally efficient; a sequence with 100 frames can be processed within a second.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Robust and Fast Contrast Inflow Detection for 2D X-ray Fluoroscopy

Chen

Funka-Lea

Comanicìu

2011

Lecture Notes in Computer Science

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“…Enhanced contrasted aortic root shows up dark pixels in the entire aorta roadmap if the contrast agent is injected. By analyzing the histogram and using the 98-percentile as a threshold measure of contrast agent, the enhanced contrast image is automatically detected after learning histogram feature curve of the first 20 images of sequence without contrast agent (Condurache et al, 2004). The aortic mesh model, valve landmarks and target area of implantation are projected to the fluoroscopic image plane using the transformation matrix of interventional C-arm imaging system.…”

Section: Contrast Image Detection and Aortic Mesh Model Alignmentmentioning

confidence: 99%

Image-Guided Transcatheter Aortic Valve Implantation Assistance System

Karar¹,

Holzhey²,

John³

et al. 2011

Aortic Valve

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“…The proposed tracking algorithm automatically detects the images in which the aortic root and the coronary arteries are filled with contrast agent using histogram-based feature of the images [13]. The image sequence is frozen as soon as the contrast agent is detected in this image to provide the manual initialization of coronary ostia locations.…”

Section: ) Avp Trackingmentioning

confidence: 99%

Towards a new image guidance system for assisting transapical minimally invasive aortic valve implantation

Karar

Gessat

Walther

et al. 2009

2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society

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We propose a new image guidance system for assisting transapical minimally invasive aortic valve implantation. The goal is to define the exact positioning of aortic valve prosthesis, preventing the misplacement of the valve. The proposed system consists of two stand-alone modules. First, preoperative planning software uses DynaCT images with manual anatomical landmarks to calculate the size and optimal position of the prosthesis. Second, an intraoperative system is developed for tracking of the prosthesis and the coronary ostia in 2-D fluoroscopic images. Then the safe area of implantation is defined. The preliminary experimental results of preoperative planning and intraoperative tracking system are promising.Abstract-We propose a new image guidance system for assisting transapical minimally invasive aortic valve implantation. The goal is to define the exact positioning of aortic valve prosthesis, preventing the misplacement of the valve. The proposed system consists of two stand-alone modules. First, preoperative planning software uses DynaCT images with manual anatomical landmarks to calculate the size and optimal position of the prosthesis. Second, an intraoperative system is developed for tracking of the prosthesis and the coronary ostia in 2-D fluoroscopic images. Then the safe area of implantation is defined. The preliminary experimental results of preoperative planning and intraoperative tracking system are promising.

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Fast Detection and Processing of Arbitrary Contrast Agent Injections in Coronary Angiography and Fluoroscopy

Cited by 13 publications

References 6 publications

Robust and Fast Contrast Inflow Detection for 2D X-ray Fluoroscopy

Robust and Fast Contrast Inflow Detection for 2D X-ray Fluoroscopy

Image-Guided Transcatheter Aortic Valve Implantation Assistance System

Towards a new image guidance system for assisting transapical minimally invasive aortic valve implantation

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