Vascular Tree Segmentation in Medical Images Using Hessian-Based Multiscale Filtering and Level Set Method

Jin, Junyang; Yang, Linjun; Zhang, Xuming; Ding, Mingyue

doi:10.1155/2013/502013

Cited by 31 publications

(27 citation statements)

References 22 publications

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“…Table 2 specifies obtained values for the four metrics. From this table it could be observed that the introduced fuzzy algorithm achieves less MSE when compared to Jin manual method 4 and when compared with PSO algorithm presented in Ref. 5.…”

Section: Comparison Criteriamentioning

confidence: 92%

“…The proposed fuzzy-rule based algorithm results will be compared with two methods: manual Jin's algorithm 4 and the automatic PSO-based algorithm 5 .…”

Section: Comparison Criteriamentioning

confidence: 99%

“…In Ref. 4, Morphological top hat transformation, Hessian filtering followed by Chan-Vese level set has been used to extract vascular structures from the enhanced image. A common problem with this filter is how to find the parameters of Frangi filter.…”

Section: Introductionmentioning

confidence: 99%

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An Advanced Automatic Fuzzy Rule-Based Algorithm for 3D Vessel Segmentation

Abdou¹,

Elsayed²,

Ali³

2018

IJCIS

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Fuzzy Logic has played an important role in medical image (MI) segmentation in the last decade. Automatic blood vessel segmentation from 3D medical images is an emerging area where segmentation algorithms could be combined with evolutionary computation methods for better diagnosis and higher decision accuracy. This paper introduces an automatic blood vessel segmentation algorithm from 3D images using Fuzzy logic. The proposed fuzzy system decides degree of Vesselness according to Eigen values of Hessian matrix. 3D synthetic and real CTA clinical image database are used to test the proposed algorithm and show a correct voxel classification. The proposed method shows better segmentation results compared to manual and swarm intelligence methods. Furthermore, fuzzy has led to better time improvement.

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Section: Comparison Criteriamentioning

confidence: 92%

“…The proposed fuzzy-rule based algorithm results will be compared with two methods: manual Jin's algorithm 4 and the automatic PSO-based algorithm 5 .…”

Section: Comparison Criteriamentioning

confidence: 99%

See 1 more Smart Citation

An Advanced Automatic Fuzzy Rule-Based Algorithm for 3D Vessel Segmentation

Abdou¹,

Elsayed²,

Ali³

2018

IJCIS

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show abstract

“…The algorithm locates the points of maximum curvature in the DEM which correspond to the surface trace of dykes. One common approach to analyze the curvature of elevation data is to use an eigenvalue analysis of the Hessian matrix [56,57]. The Hessian matrix is a 2 × 2 matrix composed of second-order partial derivatives of the input image, whereas the second-order partial derivatives are defined as a convolution with derivatives of Gaussian filter at scale σ.…”

Section: Extraction Of Structural Featuresmentioning

confidence: 99%

Towards Multiscale and Multisource Remote Sensing Mineral Exploration Using RPAS: A Case Study in the Lofdal Carbonatite-Hosted REE Deposit, Namibia

et al. 2019

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Traditional exploration techniques usually rely on extensive field work supported by geophysical ground surveying. However, this approach can be limited by several factors such as field accessibility, financial cost, area size, climate, and public disapproval. We recommend the use of multiscale hyperspectral remote sensing to mitigate the disadvantages of traditional exploration techniques. The proposed workflow analyzes a possible target at different levels of spatial detail. This method is particularly beneficial in inaccessible and remote areas with little infrastructure, because it allows for a systematic, dense and generally noninvasive surveying. After a satellite regional reconnaissance, a target is characterized in more detail by plane-based hyperspectral mapping. Subsequently, Remotely Piloted Aircraft System (RPAS)-mounted hyperspectral sensors are deployed on selected regions of interest to provide a higher level of spatial detail. All hyperspectral data are corrected for radiometric and geometric distortions. End-member modeling and classification techniques are used for rapid and accurate lithological mapping. Validation is performed via field spectroscopy and portable XRF as well as laboratory geochemical and spectral analyses. The resulting spectral data products quickly provide relevant information on outcropping lithologies for the field teams. We show that the multiscale approach allows defining the promising areas that are further refined using RPAS-based hyperspectral imaging. We further argue that the addition of RPAS-based hyperspectral data can improve the detail of field mapping in mineral exploration, by bridging the resolution gap between airplane-and ground-based data. RPAS-based measurements can supplement and direct geological observation rapidly in the field and therefore allow better integration with in situ ground investigations. We demonstrate the efficiency of the proposed approach at the Lofdal Carbonatite Complex in Namibia, which has been previously subjected to rare earth elements exploration. The deposit is located in a remote environment and characterized by difficult terrain which limits ground surveys. 2 of 28 increased demand for Rare Earth Elements (REEs). As a result, the exploration of new and promising REE deposits is of economic importance in view of the current dependence of the world market on imports from a limited number of countries.Carbonatites, rocks comprising more than 50 modal-% carbonate minerals, are the main source of REEs [1]. The typical ore minerals for light rare earth elements (LREEs) are monazite, bastnaesite, and parisite, and for the heavy rare earth elements (HREEs), is xenotime [1]. Hyperspectral remote sensing has been recently suggested to detect and identify carbonatites as potential REE deposits [2][3][4], due to the distinctive absorption feature of carbonates (CO 3 ) around 2300 to 2350 nm [5]. At a sufficient grade, REEs can be detected directly due to their characteristic narrow absorption features in the VNIR and SWIR [3,6]. Neodymium...

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“…Hessian matrix (ℋ ఙ ‫,ܫ(‬ ‫))ݔ‬ is a second-order partial derivation which is a convolution of input image (I) at point ‫ݔ‬ and Gaussian (࣡ ఙ ) filter, as in Eq. 1 [8] [9]. ROI image is read in green channel and then the vessel tracking is applied, as in Fig.…”

Section: Vessel Trackingmentioning

confidence: 99%

Glaucoma screening using rim width based on ISNT rule

Ruengkitpinyo

Kongprawechnon

Kondo

et al. 2015

2015 6th International Conference of Information and Communication Technology for Embedded Systems (IC-ICTES)

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This paper introduces an screening method for detecting glaucoma using rim width indicator. Due to some special cases, such as myopia eye, only cup-to-disc ratio may not efficient for screening glaucoma. Rim width based on ISNT rule can be a feature for classification. Rim width in each section of optic nerve will be measured and then we compare them with ISNT rule for glaucoma classification. According to our results, we can show that the proposed method is an efficient feature for screening glaucoma.

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Vascular Tree Segmentation in Medical Images Using Hessian-Based Multiscale Filtering and Level Set Method

Cited by 31 publications

References 22 publications

An Advanced Automatic Fuzzy Rule-Based Algorithm for 3D Vessel Segmentation

An Advanced Automatic Fuzzy Rule-Based Algorithm for 3D Vessel Segmentation

Towards Multiscale and Multisource Remote Sensing Mineral Exploration Using RPAS: A Case Study in the Lofdal Carbonatite-Hosted REE Deposit, Namibia

Glaucoma screening using rim width based on ISNT rule

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