Literature DB >> 16768233

Augmented vessels for quantitative analysis of vascular abnormalities and endovascular treatment planning.

Wilbur C K Wong1, Albert C S Chung.   

Abstract

Endovascular treatment plays an important role in the minimally invasive treatment of patients with vascular diseases, a major cause of morbidity and mortality worldwide. Given a segmentation of an angiography, quantitative analysis of abnormal structures can aid radiologists in choosing appropriate treatments and apparatuses. However, effective quantitation is only attainable if the abnormalities are identified from the vasculature. To achieve this, a novel method is developed, which works on the simpler shape of normal vessels to identify different vascular abnormalities (viz. stenotic atherosclerotic plaque, and saccular and fusiform aneurysmal lumens) in an indirect fashion, instead of directly manipulating the complex-shaped abnormalities. The proposed method has been tested on three synthetic and 17 clinical data sets. Comparisons with two related works are also conducted. Experimental results show that our method can produce satisfactory identification of the abnormalities and approximations of the ideal post-treatment vessel lumens. In addition, it can help increase the repeatability of the measurement of clinical parameters significantly.

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Year:  2006        PMID: 16768233     DOI: 10.1109/tmi.2006.873300

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  3 in total

1.  Automatic detection of abnormal vascular cross-sections based on density level detection and support vector machines.

Authors:  Maria A Zuluaga; Isabelle E Magnin; Marcela Hernández Hoyos; Edgar J F Delgado Leyton; Fernando Lozano; Maciej Orkisz
Journal:  Int J Comput Assist Radiol Surg       Date:  2010-06-13       Impact factor: 2.924

2.  Performance assessment of isolation methods for geometrical cerebral aneurysm analysis.

Authors:  Rubén Cárdenes; Ignacio Larrabide; Luis San Román; Alejandro F Frangi
Journal:  Med Biol Eng Comput       Date:  2012-12-06       Impact factor: 2.602

3.  Vessel network extraction and analysis of mouse pulmonary vasculature via X-ray micro-computed tomographic imaging.

Authors:  Eric A Chadwick; Takaya Suzuki; Michael G George; David A Romero; Cristina Amon; Thomas K Waddell; Golnaz Karoubi; Aimy Bazylak
Journal:  PLoS Comput Biol       Date:  2021-04-20       Impact factor: 4.475

  3 in total

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