Image Processing

ART 3.5D: an algorithm to label arteries and veins from three-dimensional angiography

[+] Author Affiliations
Beatrice Barra, Elena De Momi, Giancarlo Ferrigno, Giuseppe Baselli

Politecnico di Milano, Electronic Information and Bioengineering Department, Piazza Leonardo da Vinci, 32, Milano 20133, Italy

Guglielmo Pero, Francesco Cardinale

Niguarda Hospital, “Claudio Munari” Center for Epilepsy Surgery, Piazza Ospedale Maggiore 3, Milano 20162, Italy

Niguarda Hospital, Department of Neuroradiology, Piazza Ospedale Maggiore, 3, Milano 20162, Italy

J. Med. Imag. 3(4), 044002 (Nov 29, 2016). doi:10.1117/1.JMI.3.4.044002
History: Received June 1, 2016; Accepted November 1, 2016
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Abstract.  Preoperative three-dimensional (3-D) visualization of brain vasculature by digital subtraction angiography from computerized tomography (CT) in neurosurgery is gaining more and more importance, since vessels are the primary landmarks both for organs at risk and for navigation. Surgical embolization of cerebral aneurysms and arteriovenous malformations, epilepsy surgery, and stereoelectroencephalography are a few examples. Contrast-enhanced cone-beam computed tomography (CE-CBCT) represents a powerful facility, since it is capable of acquiring images in the operation room, shortly before surgery. However, standard 3-D reconstructions do not provide a direct distinction between arteries and veins, which is of utmost importance and is left to the surgeon’s inference so far. Pioneering attempts by true four-dimensional (4-D) CT perfusion scans were already described, though at the expense of longer acquisition protocols, higher dosages, and sensible resolution losses. Hence, space is open to approaches attempting to recover the contrast dynamics from standard CE-CBCT, on the basis of anomalies overlooked in the standard 3-D approach. This paper aims at presenting algebraic reconstruction technique (ART) 3.5D, a method that overcomes the clinical limitations of 4-D CT, from standard 3-D CE-CBCT scans. The strategy works on the 3-D angiography, previously segmented in the standard way, and reprocesses the dynamics hidden in the raw data to recover an approximate dynamics in each segmented voxel. Next, a classification algorithm labels the angiographic voxels and artery or vein. Numerical simulations were performed on a digital phantom of a simplified 3-D vasculature with contrast transit. CE-CBCT projections were simulated and used for ART 3.5D testing. We achieved up to 90% classification accuracy in simulations, proving the feasibility of the presented approach for dynamic information recovery for arteries and veins segmentation.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Beatrice Barra ; Elena De Momi ; Giancarlo Ferrigno ; Guglielmo Pero ; Francesco Cardinale, et al.
"ART 3.5D: an algorithm to label arteries and veins from three-dimensional angiography", J. Med. Imag. 3(4), 044002 (Nov 29, 2016). ; http://dx.doi.org/10.1117/1.JMI.3.4.044002


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