Uncluttered single‐image visualization of the abdominal aortic vessel tree: Method and evaluation

Won, Joong-Ho; Rosenberg, Jarrett; Rubin, Geoffrey D.; Napel, Sandy

doi:10.1118/1.3243866

Cited by 8 publications

(16 citation statements)

References 24 publications

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“…It also significantly reduced the average and the maximum overlap proportion metrics. Both the quantitative results and the visual outcomes are almost identical to those of the SA-based method (See Table IV and Figure 5 of [1]).…”

Section: Resultsmentioning

confidence: 53%

“…We used the same dataset as for the evaluation of the SA-based method in [1]. Briefly summarized, we retrospectively collected five patient scans, chosen to contain normal and typical anatomic variation, from our CTA archive.…”

Section: Discussionmentioning

confidence: 99%

“…Introduced in [1], USIV presents all branches in a single image without misleading overlap, with minimal distortion, thus preventing unnecessary user interaction and enhancing the readability of the two-dimensional (2D) visualization. In addition, USIV makes the visualization independent of user interface devices.…”

Section: Introductionmentioning

confidence: 99%

“…This idea motivates the development of USIV. The evaluation conducted in [1] provides an evidence that USIV is capable of producing images that are recognizable as a map of the underlying anatomy of the abdominal aortic vessel tree.…”

Section: Introductionmentioning

confidence: 99%

“…Using this connection we adopt a method developed for SCP to USIV: the minimization of the score function, solved using simulated annealing (SA) in [1], is reformulated as an integer linear programming (ILP) over precomputed samples from the optimization search space. The precomputation can be massively parallelized using graphics processing units (GPUs), achieving a significant performance gain over [1]. This precomputation method for the ILP, together with the identification of the connection between USIV and SCP, constitutes the main contribution of the paper.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Uncluttered Single-Image Visualization of Vascular Structures Using GPU and Integer Programming

Won

Jeon

Rosenberg

et al. 2013

IEEE Trans. Visual. Comput. Graphics

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Direct projection of three-dimensional branching structures, such as networks of cables, blood vessels, or neurons onto a 2D image creates the illusion of intersecting structural parts and creates challenges for understanding and communication. We present a method for visualizing such structures, and demonstrate its utility in visualizing the abdominal aorta and its branches, whose tomographic images might be obtained by computed tomography or magnetic resonance angiography, in a single two-dimensional stylistic image, without overlaps among branches. The visualization method, termed uncluttered single-image visualization (USIV), involves optimization of geometry. This paper proposes a novel optimization technique that utilizes an interesting connection of the optimization problem regarding USIV to the protein structure prediction problem. Adopting the integer linear programming-based formulation for the protein structure prediction problem, we tested the proposed technique using 30 visualizations produced from five patient scans with representative anatomical variants in the abdominal aortic vessel tree. The novel technique can exploit commodity-level parallelism, enabling use of general-purpose graphics processing unit (GPGPU) technology that yields a significant speedup. Comparison of the results with the other optimization technique previously reported elsewhere suggests that, in most aspects, the quality of the visualization is comparable to that of the previous one, with a significant gain in the computation time of the algorithm.

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Section: Resultsmentioning

confidence: 53%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Uncluttered Single-Image Visualization of Vascular Structures Using GPU and Integer Programming

Won

Jeon

Rosenberg

et al. 2013

IEEE Trans. Visual. Comput. Graphics

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Automated Nomenclature of Upper Abdominal Arteries for Displaying Anatomical Names on Virtual Laparoscopic Images

Mori

Oda

Egusa

et al. 2010

Lecture Notes in Computer Science

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DWT-Based Segmentation Method for Coronary Arteries

Hsu

Hung

Lin³

et al. 2014

J Med Syst

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This work presents a new method for segmenting coronary arteries automatically in computed tomography angiography (CTA) data sets. The method automatically isolates heart and coronary arteries from surrounding structures and search for the probable location of coronary arteries by 3D region growing. Based on the dilation of the probable location, discrete wavelet transformation (DWT) and λ - mean operation complete accurate detection of coronary arties. Finally, the proposed method is tested on clinical CTA data-sets. The results on clinical datasets show that the proposed method is able to extract each branch of arteries when comparing to commercial software GE Healthcare and delineated ground truth.

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Uncluttered single‐image visualization of the abdominal aortic vessel tree: Method and evaluation

Abstract: The method for eliminating misleading false intersections in 2D projections of the abdominal aortic tree conserves the overall shape and does not diminish accurate identifiability of the branches.

Cited by 8 publications

References 24 publications

Uncluttered Single-Image Visualization of Vascular Structures Using GPU and Integer Programming

Uncluttered Single-Image Visualization of Vascular Structures Using GPU and Integer Programming

Automated Nomenclature of Upper Abdominal Arteries for Displaying Anatomical Names on Virtual Laparoscopic Images

DWT-Based Segmentation Method for Coronary Arteries

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