Literature DB >> 9034666

An algorithm for real-time vessel enhancement and detection.

R Poli1, G Valli.   

Abstract

In this paper we present an algorithm for the real-time enhancement and detection of blood vessels in medical images. The algorithm is based on a set of linear filters sensitive to vessels of different orientation and thickness. Such filters are obtained as linear combinations of properly shifted Gaussian kernels. The output of multiple oriented vessel-enhancing filters can be integrated to obtain images in which vessels are highly enhanced independently of their direction and thickness. To avoid spurious responses in the presence of step edges or to enhance the skeletons of vessels, the output of directional filters can be validated before integration. Skeleton detection and vessel segmentation can be performed via thresholding with hysteresis. Experimental results on synthetic images and real coronary arteriograms are reported.

Mesh:

Year:  1997        PMID: 9034666     DOI: 10.1016/s0169-2607(96)01773-7

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  6 in total

1.  Automated neurite extraction using dynamic programming for high-throughput screening of neuron-based assays.

Authors:  Yong Zhang; Xiaobo Zhou; Alexei Degterev; Marta Lipinski; Donald Adjeroh; Junying Yuan; Stephen T C Wong
Journal:  Neuroimage       Date:  2007-01-27       Impact factor: 6.556

2.  Segmentation of arteries in MPRAGE images of the ventral medial prefrontal cortex.

Authors:  N Penumetcha; B Jedynak; M Hosakere; E Ceyhan; K N Botteron; J T Ratnanather
Journal:  Comput Med Imaging Graph       Date:  2007-10-26       Impact factor: 4.790

Review 3.  Progress towards automated diabetic ocular screening: a review of image analysis and intelligent systems for diabetic retinopathy.

Authors:  T Teng; M Lefley; D Claremont
Journal:  Med Biol Eng Comput       Date:  2002-01       Impact factor: 2.602

4.  A review of coronary vessel segmentation algorithms.

Authors:  Maryam Taghizadeh Dehkordi; Saeed Sadri; Alimohamad Doosthoseini
Journal:  J Med Signals Sens       Date:  2011-01

5.  Automatic vasculature identification in coronary angiograms by adaptive geometrical tracking.

Authors:  Ruoxiu Xiao; Jian Yang; Mahima Goyal; Yue Liu; Yongtian Wang
Journal:  Comput Math Methods Med       Date:  2013-10-22       Impact factor: 2.238

6.  Coronary angiography video segmentation method for assisting cardiovascular disease interventional treatment.

Authors:  Dongxue Liang; Jing Qiu; Lu Wang; Xiaolei Yin; Junhui Xing; Zhiyun Yang; Jiangzeng Dong; Zhaoyuan Ma
Journal:  BMC Med Imaging       Date:  2020-06-16       Impact factor: 1.930

  6 in total

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