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gradient vector flow with mean shift for skin lesion segmentation

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS 2011年第2期35卷 121-127页

作者： Zhou, Huiyu Schaefer, Gerald Celebi, M. Emre Lin, Faquan Liu, Tangwei Queens Univ Belfast Belfast BT3 9DT Antrim North Ireland Univ Loughborough Loughborough LE11 3TU Leics England Louisiana State Univ Shreveport LA 71115 USA Guangxi Med Univ Nanning 530021 Peoples R China

Image segmentation is an important task in the analysis of dermoscopy images since the extraction of skin lesion borders provides important cues for accurate diagnosis. In recent years, gradient vector flow based algorithms have demonstrated their merits in image segmentation. However, due to the compromise of internal and external energy forces within the partial differential equation these methods commonly lead to under- or over-segmentation problems. In this paper, we introduce a new mean shift based gradient vector flow (GVF) algorithm that drives the internal/external energies towards the correct direction. The proposed segmentation method incorporates a mean shift operation within the standard GVF cost function. Theoretical analysis proves that the proposed algorithm converges rapidly, while experimental results on a large set of diverse dermoscopy images demonstrate that the presented method accurately determines skin lesion borders in dermoscopy images. (C) 2010 Elsevier Ltd. All rights reserved.

关键词： Image segmentation gradient vector flow Mean shift Convergence Accuracy

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gradient vector flow active contours with prior directional information

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PATTERN RECOGNITION LETTERS 2010年第9期31卷 845-856页

作者： Zhu, Guopu Zhang, Shuqun Zeng, Qingshuang Wang, Changhong CUNY Coll Staten Isl Dept Comp Sci Staten Isl NY 10314 USA Sun Yat Sen Univ GuangDong Key Lab Informat Secur Guangzhou 510006 Guangdong Peoples R China Harbin Inst Technol Space Control & Inertial Technol Res Ctr Harbin 150001 Peoples R China

Active contours, or snakes, have been widely used in image processing and computer vision for image segmentation and object tracking. However, they usually have poor performance in segmenting images with complex object shape and complex background, and also in dealing with the issue of weak-edge-leakage. To guide the front of active contour toward the desired object boundary and prevent it from moving over the weak edges with strong neighbors, we present a novel external force field, referred to as gradient and direction vector flow (G&DVF), which integrates the gradient vector flow (GVF) and the prior directional information provided by a user. The proposed method is sufficiently general and simple to implement. The experiments conducted on image segmentation demonstrate that the proposed method is insensitive to image clutters/noise and capable of driving the fronts of active contours to conform to complex shapes and addressing the issue of weak-edge-leakage in some cases. (c) 2010 Elsevier B.V. All rights reserved.

关键词： Active contours Snakes gradient vector flow Image segmentation

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gradient vector flow fast geometric active contours

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2004年第3期26卷 402-407页

作者： Paragios, N Mellina-Gottardo, O Ramesh, V Siemens Corp Res Real Time Vis & Modeling Dept Princeton NJ 08540 USA

In this paper, we propose an edge-driven bidirectional geometric flow for boundary extraction. To this end, we combine the geodesic active contour flow [3] and the gradient vector flow external force for snakes [25]. The resulting motion equation is considered within a level set formulation [19], can deal with topological changes and important shape deformations. An efficient numerical schema is used for the flow implementation that exhibits robust behavior and has fast convergence rate [8], [23]. Promising results on real and synthetic images demonstrate the potentials of the flow.

关键词： boundary extraction image segmentation gradient vector flow geodesic active contours level set methods additive operator splitting

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gradient vector flow over Manifold for Active Contours

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9th Asian Conference on Computer Vision

作者： Lu, Shaopei Wang, Yuanquan Tianjin Univ Technol Tianjin Key Lab Intelligent Comp & Novel Software Tianjin 300191 Peoples R China

ISBN: (纸本)9783642123061

The gradient vector flow (GVF) snake shows high performance at concavity convergence and initialization insensitivity, but the two components of GVF field are treated isolatedly during diffusion, this leads to the failure of GVF snake at weak edge preserving and deep and narrow concavity convergence. In this study, a novel external force for active contours named gradient vector flow over manifold (GVFOM) is proposed that couples the two components during diffusion by generalizing the Laplacian operator from flat space to manifold. The specific operator is Beltrami operator. This proposed GVFOM snake has been assessed on synthetic and real images;experimental results show that the GVFOM snake behaves similarly to the GVF snake in terms of capture range enlarging, initialization insensitivity, while provides much better results than GVF snake for weak edge preserving, objects separation, narrow and deep concavity convergence.

关键词： image segmentation active contour gradient vector flow manifold beltrami operator gradient vector flow over manifold

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gradient vector flow Field and Fast Marching Based Method for Centerline Computation of Coronary Arteries 7th

Gradient Vector Flow Field and Fast Marching Based Method fo...

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7th International Conference on Intelligence Science and Big Data Engineering (IScIDE)

作者： Cui, Hengfei Xia, Yong Northwestern Polytech Univ Sch Comp Sci & Engn Shaanxi Key Lab Speech & Image Informat Proc SAII Xian 710072 Shaanxi Peoples R China Northwestern Polytech Univ Sch Comp Sci & Engn CMCC Xian 710072 Shaanxi Peoples R China

ISBN: (纸本)9783319677774;9783319677767

This paper develops new concept of validating centerline extraction method of coronary arteries. The approach is based on the gradient vector flow (GVF) filed of the 3D segmented coronary arteries models. It is implemented with the Gaussian based speed image. The approach was validated over 3 three-dimensional synthetic vessel models and further tested in 3 clinical coronary arteries models reconstructed from computed tomography coronary angiography (CTCA) in human patients. The results showed an excellent agreement between the proposed method and ground truth centerline in synthetic vessel models. Second, the proposed method was applicable in both left coronary arteries and right coronary arteries with average processing time of 25.7 min per case. In conclusion, the proposed gradient vector flow field and fast marching based method should have more routine clinical applicability.

关键词： gradient vector flow Fast marching method Coronary centerline

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Design and implementation of gradient vector flow snake to detect a reference object in pelvic x-rays for preoperative total hip arthroplasty planning application

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JOURNAL OF DIGITAL IMAGING 2007年第4期20卷 373-380页

作者： Kristanto, W. van Ooijen, P. M. A. The, B. Duifhuis, H. Mengko, T. R. Oudkerk, M. Univ Med Ctr Groningen Dept Radiol NL-9700 RB Groningen Netherlands Univ Groningen Dept Biomed Engn NL-9700 RB Groningen Netherlands Inst Teknol Bandung Biomed Engn Elect Engn Dept Bandung 40132 Indonesia Univ Med Ctr Groningen Dept Orthoped NL-9700 RB Groningen Netherlands

The main interest of this research project is to promote automation in performing preoperative planning for hip joint replacement surgery using a special medical image viewing software, ViewPro (TM). Preoperative planning is performed to carefully prepare the surgery and to accurately select the hip implants. The first step of preoperative planning is to calibrate the x-ray image to adjust the magnification factor. A femoral head implant is used as magnification factor reference. Automation is introduced by developing an algorithm to automatically detect this reference object in the image. The algorithm used for performing the automatic detection of the reference object is gradient vector flow (GVF) snake. A study has been performed to compare the newly developed semiautomatic algorithm to the old manual calibration algorithm. The results show a close relation between the two algorithms (less than 1% of average relative difference). It is concluded that the developed semiautomated algorithm can be used as an alternative for performing the manual calibration.

关键词： preoperative planning total hip arthroplasty snake algorithm gradient vector flow

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Snakes, shapes, and gradient vector flow

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IEEE TRANSACTIONS ON IMAGE PROCESSING 1998年第3期7卷 359-369页

作者： Xu, CY Prince, JL Johns Hopkins Univ Dept Elect & Comp Engn Image Anal & Commun Lab Baltimore MD 21218 USA

Snakes, or active contours, are used extensively in computer vision and image processing applications, particularly to locate object boundaries, problems associated with initialization and poor convergence to boundary concavities, however, have limited their utility, This paper presents a new external force for active contours, largely solving both problems. This external forte, which we call gradient vector flow (GVF), is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image. It differs fundamentally from traditional snake external forces in that it cannot be written as the negative gradient of a potential function, and the corresponding snake is formulated directly from a force balance condition rather than a variational formulation. Using several two-dimensional (2-D) examples and one three-dimensional (3-D) example, we show that GVF has a large capture range and is able to move snakes into boundary concavities.

关键词： active contour models deformable surface models edge detection gradient vector flow image segmentation shape representation and recovery snakes

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Generalized gradient vector flow external forces for active contours

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SIGNAL PROCESSING 1998年第2期71卷 131-139页

作者： Xu, CY Prince, JL Johns Hopkins Univ Dept Elect & Comp Engn Image Anal & Commun Lab Baltimore MD 21218 USA

Active contours, or snakes, are used extensively in computer vision and image processing applications, particularly to locate object boundaries. A new type of external force for active contours, called gi adient vector flow (GVF) was introduced recently to address problems associated with initialization and poor convergence to boundary concavities. GVF is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image. In this paper, we generalize the GVF formulation to include two spatially varying weighting functions. This improves active contour convergence to long, thin boundary indentations, while maintaining other desirable properties of GVF, such as an extended capture range. The original GVF is a special case of this new generalized GVF (GGVF) model. An error analysis for active contour results on simulated test images is also presented. (C) 1998 Elsevier Science B.V. All rights reserved.

关键词： Edge detection Image segmentation Shape representation and recovery Deformable models Active contour models gradient vector flow

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Active contours with neighborhood-extending and noise-smoothing gradient vector flow external force

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EURASIP JOURNAL ON IMAGE AND VIDEO PROCESSING 2012年第1期2012卷 1-6页

作者： Liu, Lixiong Bovik, Alan C. Beijing Inst Technol Sch Comp Sci Beijing Lab Intelligent Informat Technol Beijing 100081 Peoples R China Univ Texas Austin Dept Elect & Comp Engn Lab Image & Video Engn Austin TX 78712 USA

We propose a novel external force for active contours, which we call neighborhood-extending and noise-smoothing gradient vector flow (NNGVF). The proposed NNGVF snake expresses the gradient vector flow (GVF) as a convolution with a neighborhood-extending Laplacian operator augmented by a noise-smoothing mask. We find that the NNGVF snake provides better segmentation than the GVF snake in terms of noise resistance, weak edge preservation, and an enlarged capture range. The NNGVF snake accomplishes this with a reduced computational cost while maintaining other desirable properties of the GVF snake, such as initialization insensitivity and good convergences at concavities. We demonstrate the advantages of NNGVF on synthetic and real images.

关键词： image segmentation active contour gradient vector flow Laplacian operator neighborhood-extending and noise-smoothing gradient vector flow

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Vessel boundary tracking for intravital Microscopy via multiscale gradient vector flow snakes

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IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING 2004年第2期51卷 316-324页

作者： Tang, JS Acton, ST Univ Virginia Dept Elect & Comp Engn Charlottesville VA 22904 USA Univ Virginia Dept Biomed Engn Charlottesville VA 22904 USA

Due to movement of the specimen, vasodilation, and intense clutter, the intravital location of a vessel boundary from video microscopy is a difficult but necessary task in analyzing the mechanics of inflammation and the structure of the microvasculature. This paper details an active contour model for vessel boundary detection and tracking. In developing the method, two innovations are introduced. First, the B-spline model is combined with the gradient vector flow (GVF) external force. Second, a multiscale gradient vector flow (MSGVF) is employed to elude clutter and to reliably localize the vessel boundaries. Using synthetic experiments and video microscopy obtained via transillumination of the mouse cremaster muscle, we demonstrate that the MSGVF approach is superior to the fixed-scale GVF approach in terms of boundary localization. In each experiment, the fixed scale approach yielded at least a 50% increase in root mean squared error over the multiscale approach. In addition to delineating the vessel boundary so that cells can be detected and tracked, we demonstrate the boundary location technique enables automatic blood flow velocity computation in vivo.

关键词： active contour model B-splines gradient vector flow intravital microscopy snakes tracking vessel boundary detection

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