Literature DB >> 3626994

Image feature analysis and computer-aided diagnosis in digital radiography. 2. Computerized determination of vessel sizes in digital subtraction angiography.

H Fujita, K Doi, L E Fencil, K G Chua.   

Abstract

We developed an iterative deconvolution technique to determine the size of a "blurred" vessel in a digital subtraction angiographic (DSA) image by taking into account the unsharpness of the DSA system. Initially, a region of interest over a small segment of the contrast-filled vessel was selected in a DSA image, and the center line of the opacified vessel was determined by polynomial curve fitting of the locations of the peak pixel values along the vessel image. The blurred image profile was then obtained from pixel values across the vessel in a direction perpendicular to the center line. This measured profile was compared iteratively with a calculated profile for various size vessels, which was obtained from a cylindrical vessel model and from the line spread function, until the root-mean-square difference between the two profiles was minimized. The size of a cylindrical vessel yielding the matched profile was considered the best estimate of the unknown vessel size. Studies with a blood vessel phantom indicated that vessels larger than 0.5 mm could be measured with an accuracy and precision of approximately 0.1 mm, which is about 1/3 of the pixel size used in our DSA system. Details of our approach and some clinical vessel images with and without simulated stenotic lesions are presented.

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Year:  1987        PMID: 3626994     DOI: 10.1118/1.596066

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  9 in total

1.  A system for determination of 3D vessel tree centerlines from biplane images.

Authors:  K R Hoffmann; A Sen; L Lan; K G Chua; J Esthappan; M Mazzucco
Journal:  Int J Card Imaging       Date:  2000-10

Review 2.  Computer-aided diagnosis in medical imaging: historical review, current status and future potential.

Authors:  Kunio Doi
Journal:  Comput Med Imaging Graph       Date:  2007-03-08       Impact factor: 4.790

Review 3.  Anniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM.

Authors:  Maryellen L Giger; Heang-Ping Chan; John Boone
Journal:  Med Phys       Date:  2008-12       Impact factor: 4.071

4.  Clinical evaluation of angiographic multiple-view 3D reconstruction.

Authors:  Peter B Noël; Kenneth R Hoffmann; Snehal Kasodekar; Alan M Walczak; Sebastian Schafer; Jacek Dmochowski
Journal:  Int J Comput Assist Radiol Surg       Date:  2009-06-04       Impact factor: 2.924

5.  New microangiography system development providing improved small vessel imaging, increased contrast to noise ratios, and multi-view 3D reconstructions.

Authors:  Andrew T Kuhls; Vikas Patel; Ciprian Ionita; Peter B Noël; Alan M Walczak; Hussain S Rangwala; Kenneth R Hoffmann; Stephen Rudin
Journal:  Proc SPIE Int Soc Opt Eng       Date:  2006

Review 6.  Potential usefulness of digital imaging in clinical diagnostic radiology: computer-aided diagnosis.

Authors:  K Doi; M L Giger; R M Nishikawa; K R Hoffmann; H MacMahon; R A Schmidt
Journal:  J Digit Imaging       Date:  1995-02       Impact factor: 4.056

7.  In-vivo validation of videodensitometric coronary cross-sectional area measurement using dual-energy digital subtraction angiography.

Authors:  S Molloi; A Ersahin; J Hicks; J Wallis
Journal:  Int J Card Imaging       Date:  1995-12

8.  A review of computer-aided diagnosis in thoracic and colonic imaging.

Authors:  Kenji Suzuki
Journal:  Quant Imaging Med Surg       Date:  2012-09

9.  Improved method of magnification factor calculation for the angiographic measurement of neurovascular lesion dimensions.

Authors:  Zhou Wang; Stephen Rudin; Daniel R Bednarek; Laszlo Miskolczi
Journal:  J Appl Clin Med Phys       Date:  2002       Impact factor: 2.102

  9 in total

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