Prior-based automatic segmentation of the carotid artery lumen in TOF MRA (PASCAL)

TY - CHAP

T1 - Prior-based automatic segmentation of the carotid artery lumen in TOF MRA (PASCAL)

AU - Hutter, Jana

AU - Hofmann, Hannes G

AU - Grimm, Robert

AU - Greiser, Andreas

AU - Saake, Marc

AU - Hornegger, Joachim

AU - Dörfler, Arnd

AU - Schmitt, Peter

PY - 2012

Y1 - 2012

N2 - In current clinical practice, examinations of the carotid artery bifurcation are commonly carried out with Computed Tomography Angiography (CTA) or contrast-enhanced Magnetic Resonance Angiography (ceMRA). Quantitative information about vessel morphology, extracted from segmentations, is promising for diagnosis of vessel pathologies. However, both above-mentioned techniques require the administration of contrast media. In contrary, non-ceMRA methods such as Time-of-Flight (TOF) provide fully non-invasive imaging without any exogenous contrast agent. The diagnostic value of TOF MRA, however, for assessment of the carotid bifurcation area can be hampered due to its susceptibility to irregular blood flow patterns. Conventional methods for lumen segmentation are very sensitive to such signal voids and produce inaccurate results. In this work, a novel, fully automatic 3D segmentation algorithm is proposed which uses prior knowledge about irregular flow patterns. The presented technique has been successfully tested on eleven volunteer datasets as well as in a patient case, offering the comparison to CTA images. The sensitivity could be increased by 29.2% to 85.6% compared to standard level set methods. The root mean squared error in diameter measurements was reduced from 4.85 mm to 1.44 mm.

AB - In current clinical practice, examinations of the carotid artery bifurcation are commonly carried out with Computed Tomography Angiography (CTA) or contrast-enhanced Magnetic Resonance Angiography (ceMRA). Quantitative information about vessel morphology, extracted from segmentations, is promising for diagnosis of vessel pathologies. However, both above-mentioned techniques require the administration of contrast media. In contrary, non-ceMRA methods such as Time-of-Flight (TOF) provide fully non-invasive imaging without any exogenous contrast agent. The diagnostic value of TOF MRA, however, for assessment of the carotid bifurcation area can be hampered due to its susceptibility to irregular blood flow patterns. Conventional methods for lumen segmentation are very sensitive to such signal voids and produce inaccurate results. In this work, a novel, fully automatic 3D segmentation algorithm is proposed which uses prior knowledge about irregular flow patterns. The presented technique has been successfully tested on eleven volunteer datasets as well as in a patient case, offering the comparison to CTA images. The sensitivity could be increased by 29.2% to 85.6% compared to standard level set methods. The root mean squared error in diameter measurements was reduced from 4.85 mm to 1.44 mm.

KW - Algorithms

KW - Carotid Arteries

KW - Carotid Stenosis

KW - Humans

KW - Image Enhancement

KW - Image Interpretation, Computer-Assisted

KW - Magnetic Resonance Angiography

KW - Pattern Recognition, Automated

KW - Reproducibility of Results

KW - Sensitivity and Specificity

KW - Subtraction Technique

U2 - 10.1007/978-3-642-33418-4_63

DO - 10.1007/978-3-642-33418-4_63

M3 - Conference paper

C2 - 23286087

SN - 9783642334177

VL - 15

T3 - Lecture Notes in Computer Science

SP - 511

EP - 518

BT - Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012

PB - Springer Berlin Heidelberg

ER -