Snakes, shapes, and gradient vector flow

Snakes: Active contour models

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Geodesic Active Contours

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Shape modeling with front propagation: a level set approach

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Statistical textural feature and deformable model based brain tumor segmentation and volume estimation

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Segmentation of medical images using mean value guided contour

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Iodine and freeze-drying enhanced high-resolution MicroCT imaging for reconstructing 3D intraneural topography of human peripheral nerve fascicles

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Efficient Segmentation of a Breast in B-Mode Ultrasound Tomography Using Three-Dimensional GrabCut (GC3D)

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Automatic aortic root segmentation and anatomical landmarks detection for TAVI procedure planning

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Integrated Four Dimensional Registration and Segmentation of Dynamic Renal MR Images

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Active Contour Method Combining Local Fitting Energy and Global Fitting Energy Dynamically

Yu, Y., Zhang, C., Yu, W., & Li, X. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-13923-9_17 · Cited by 25

A hybrid boundary detection algorithm based on watershed and snake

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A wavelet-frame based image force model for active contouring algorithms

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Fast image-based object localization in natural scenes

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ACCURATE LOCALIZATION OF CELL NUCLEI IN PAP SMEAR IMAGES USING GRADIENT VECTOR FLOW DEFORMABLE MODELS

Plissiti, M. E., Nikou, C., & Charchanti, A. V. (2010) · International Conference on Bio-inspired Systems and Signal Processing · doi:10.5220/0002746702840289 · Cited by 25

Structure-adaptive B-snake for segmenting complex objects

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Convergence Condition and Efficient Implementation of the Fuzzy Curve-Tracing (FCT) Algorithm

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Proceedings of the MICCAI Challenge on Multimodal Brain Tumor Image Segmentation (BRATS) 2012

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Correction of oral contrast artifacts in CT-based attenuation correction of PET images using an automated segmentation algorithm

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Frequency-tuned active contour model

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A Hybrid Level Set With Semantic Shape Constraint for Object Segmentation

Wang, B., Yuan, X., Gao, X., Li, X., & Tao, D. (2018) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2018.2799999 · Cited by 24

Layer boundary evolution method for macular OCT layer segmentation

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Quantitative magnetic resonance imaging measures as biomarkers of disease progression in boys with Duchenne muscular dystrophy: a phase 2 trial of domagrozumab

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Robust Extraction of the Optic Nerve Head in Optical Coherence Tomography

Herzog, A., Boyer, K. L., & Roberts, C. J. (2004) · Lecture notes in computer science · doi:10.1007/978-3-540-27816-0_34 · Cited by 24

Variational Guidewire Tracking Using Phase Congruency

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Head tracking and flagellum tracing for sperm motility analysis

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Multi-component image segmentation in homogeneous regions based on description length minimization: Application to speckle, Poisson and Bernoulli noise

Galland, F., Bertaux, N., & Réfrégier, P. (2005) · Pattern Recognition · doi:10.1016/j.patcog.2004.10.002 · Cited by 24

Electroporation-Based Treatment Planning for Deep-Seated Tumors Based on Automatic Liver Segmentation of MRI Images

Pavliha, D., Mušič, M. M., Serša, G., & Damijan Miklavčič, A. (2013) · PLoS ONE · doi:10.1371/journal.pone.0069068 · Cited by 24

Active contour model driven by Globally Signed Region Pressure Force

Abdelsamea, M. M., & Tsaftaris, S. A. (2013) · IEEE International Conference on Digital Signal Processing (DSP) · doi:10.1109/icdsp.2013.6622691 · Cited by 24

Supervised Self-Organizing Classification of Superresolution ISAR Images: An Anechoic Chamber Experiment

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Cerebral white matter segmentation from MRI using probabilistic graph cuts and geometric shape priors

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Snake model for the extraction of loess shoulder-line from DEMs

Yan, S.-J., Tang, G., Li, F., & Zhang, L. (2014) · Journal of Mountain Science · doi:10.1007/s11629-013-2484-0 · Cited by 24

Object Contour Extraction Using Adaptive B-Snake Model

Wang, Y., & Teoh, E. K. (2006) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-005-3629-8 · Cited by 24

Automatic identification of cochlear implant electrode arrays for post-operative assessment

Noble, J. H., Schuman, T. A., Wright, C. G., Labadie, R. F., & Dawant, B. M. (2011) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.878490 · Cited by 24

A hybrid active contour model with structured feature for image segmentation

Ge, Q., Li, C., Shao, W., & Li, H. (2014) · Signal Processing · doi:10.1016/j.sigpro.2014.09.007 · Cited by 24

ArtiSketch: A System for Articulated Sketch Modeling

Levi, Z., & Gotsman, C. (2013) · Computer Graphics Forum · doi:10.1111/cgf.12043 · Cited by 24

Image Techniques for Identifying Sea-Ice Parameters

Zhang, Q., & Skjetne, R. (2014) · Modeling Identification and Control A Norwegian Research Bulletin · doi:10.4173/mic.2014.4.6 · Cited by 24

Segmentation of brain tumors in MRI images using multi-scale gradient vector flow

Kazerooni, A. F., Ahmadian, A., Serej, N. D., Rad, H. S., Saberi, H., Yousefi, H., & Farnia, P. (2011) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2011.6091966 · Cited by 24

A New Image-Based Framework for Analyzing Cine Images

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Slic-Seg: Slice-by-Slice Segmentation Propagation of the Placenta in Fetal MRI Using One-Plane Scribbles and Online Learning

Wang, G., Zuluaga, M. A., Pratt, R., Aertsen, M., David, A. L., Deprest, J. A., Vercauteren, T. K., & Sebastien Ourselin, A. (2015) · Lecture notes in computer science · doi:10.1007/978-3-319-24574-4_4 · Cited by 24

Recent Advances in Multi Robot Systems

Lazinica, A. (2008) · doi:10.5772/63 · Cited by 24

A Tongue Image Segmentation Method Based on Enhanced HSV Convolutional Neural Network

Jiang, L., Xu, B., Ban, X., Tai, P., & Ma, B. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66805-5_32 · Cited by 24

The application of gray-scale level-set method in segmentation of concrete deck delamination using infrared images

Cheng, C., & Shen, Z. (2020) · Construction and Building Materials · doi:10.1016/j.conbuildmat.2019.117974 · Cited by 24

A Generalized Asymmetric Dual-Front Model for Active Contours and Image Segmentation

Chen, D., Spencer, J., Mirebeau, J., Chen, K., Shu, M., & Cohen, L. D. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3078102 · Cited by 24

Automated Segmentation of the Cerebellar Lobules Using Boundary Specific Classification and Evolution

Bogovic, J., Bazin, P., Ying, S. H., & Prince, J. L. (2013) · Lecture notes in computer science · doi:10.1007/978-3-642-38868-2_6 · Cited by 24

Surface Extraction from Volumetric Images Using Deformable Meshes: A Comparative Study

Tohka, J. (2002) · Lecture notes in computer science · doi:10.1007/3-540-47977-5_23 · Cited by 24

Comparison of active contour models for image segmentation in X-ray coronary angiogram images

Devi, S. N., & Kumaravel, N. (2008) · Journal of Medical Engineering & Technology · doi:10.1080/09687630801889440 · Cited by 24

Automatic Delineation of the Diaphragm in Computed Tomographic Images

Rangayyan, R. M., Vu, R. H., & Boag, G. S. (2008) · Journal of Imaging Informatics in Medicine · doi:10.1007/s10278-007-9091-y · Cited by 24

Deformable model with adaptive mesh and automated topology changes

Lachaud, J., & Taton, B. (2004) · International Conference on 3-D Digital Imaging and Modeling (3DIM) · doi:10.1109/im.2003.1240227 · Cited by 24

Nitrate‐induced coronary vasodilation by stress‐magnetic resonance imaging: A novel noninvasive test of coronary vasomotion

Pepe, A., Lombardi, M., Takacs, I., Positano, V., Panzarella, G., & Picano, E. (2004) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.20136 · Cited by 24

Efficient Surface Reconstruction From Noisy Data Using Regularized Membrane Potentials

Jalba, A. C., & Roerdink, J. B. T. M. (2009) · IEEE Transactions on Image Processing · doi:10.1109/tip.2009.2016141 · Cited by 24

Segmenting reliefs on triangle meshes

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A Novel Method for the Separation of Overlapping Pollen Species for Automated Detection and Classification

Tello-Mijares, S., & Flores, F. (2016) · Computational and Mathematical Methods in Medicine · doi:10.1155/2016/5689346 · Cited by 23

ResD-Unet Research and Application for Pulmonary Artery Segmentation

Yuan, H., Liu, Z., Shao, Y., & Liu, M. (2021) · IEEE Access · doi:10.1109/access.2021.3073051 · Cited by 23

Leaf vein segmentation with self-supervision

Li, L., Hu, W., Lu, J., & Zhang, C. (2022) · Computers and Electronics in Agriculture · doi:10.1016/j.compag.2022.107352 · Cited by 23

Homogeneity- and density distance-driven active contours for medical image segmentation

Truc, P. T. H., Kim, T., Lee, S., & Lee, Y.-K. (2011) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2011.03.006 · Cited by 23

A coarse-to-fine approach for segmenting melanocytic skin lesions in standard camera images

Cavalcanti, P. G., & Scharcanski, J. (2013) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2013.08.010 · Cited by 23

A method based on rank-ordered filter to detect edges in cellular image

Xu, X., Yang, Z., & Wang, Y. (2009) · Pattern Recognition Letters · doi:10.1016/j.patrec.2008.12.009 · Cited by 23

The influence of tibial morphology on the design of an anatomical tibial baseplate for TKA

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Intrinsic Bayesian Active Contours for Extraction of Object Boundaries in Images

Joshi, S. H., & Srivastava, A. (2008) · International Journal of Computer Vision · doi:10.1007/s11263-008-0179-8 · Cited by 23

Estimation of Two-Dimensional Affine Transformations Through Polar Curve Matching and Its Application to Image Mosaicking and Remote-Sensing Data Registration

Lucchese, L., Leorin, S., & Cortelazzo, G. M. (2006) · IEEE Transactions on Image Processing · doi:10.1109/tip.2006.877519 · Cited by 23

A modified adaptive differential evolution algorithm for color image segmentation

Khan, A., Jaffar, M. A., & Shao, L. (2014) · Knowledge and Information Systems · doi:10.1007/s10115-014-0741-3 · Cited by 23

Localization and quantification of intramuscular damage using statistical parametric mapping and skeletal muscle parcellation

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Retinex theory based active contour model for segmentation of inhomogeneous images

Wang, G., Dong, Q., Pan, Z., Zhang, W., Duan, J., Bai, L., & Zhang, J. (2015) · Digital Signal Processing · doi:10.1016/j.dsp.2015.12.011 · Cited by 23

Matching Contours in Images through the use of Curvature, Distance to Centroid and Global Optimization with Order-Preserving Constraint

Oliveira, F. P. M., & Tavares, J. M. R. S. (2009) · Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · doi:10.3970/cmes.2009.043.091 · Cited by 23

Cell Segmentation Based on FOPSO Combined With Shape Information Improved Intuitionistic FCM

Bai, X., Sun, C., & Sun, C. (2018) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2018.2803020 · Cited by 23

Geodesic Paths for Image Segmentation With Implicit Region-Based Homogeneity Enhancement

Chen, D., Zhu, J., Zhang, X., Shu, M., & Cohen, L. D. (2021) · IEEE Transactions on Image Processing · doi:10.1109/tip.2021.3078106 · Cited by 23

Cross Modality Deformable Segmentation Using Hierarchical Clustering and Learning

Zhan, Y., Dewan, M., & Zhou, X. S. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-04271-3_125 · Cited by 23

Spatiotemporal relationships between the cell shape and the actomyosin cortex of periodically protruding cells

Driscoll, M., Losert, W., Jacobson, K., & Kapustina, M. (2015) · Cytoskeleton · doi:10.1002/cm.21229 · Cited by 23

Optical wear assessment system for grinding tools

Heger, T., & Pandit, M. C. (2004) · Journal of Electronic Imaging · doi:10.1117/1.1760757 · Cited by 23

Textline information extraction from grayscale camera-captured document images

Bukhari, S. S., Breuel, T. M., & Faisal Shafait, B. (2009) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2009.5413799 · Cited by 23

A New Deformable Model for Boundary Tracking in Cardiac MRI and Its Application to the Detection of Intra-Ventricular Dyssynchrony

Gotardo, P. F. U., Boyer, K. L., Saltz, J., & Raman, S. V. (2006) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2006.34 · Cited by 23

DEFORMABLE MESH FOR AUTOMATED SURFACE EXTRACTION FROM NOISY IMAGES

Tohka, J., & Mykkänen, J. M. (2004) · International Journal of Image and Graphics · doi:10.1142/s0219467804001488 · Cited by 23

Description of brain internal structures by means of spatial relations for MR image segmentation

Colliot, O., Cámara, Ó., Dewynter, R., & Isabelle Bloch, A. (2004) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.535216 · Cited by 23

A PDE approach for measuring tissue thickness

Yezzi, A. J., & Prince, J. L. (2005) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2001.990460 · Cited by 23

Towards building computerized image analysis framework for nucleus discrimination in microscopy images of diffuse glioma

Kong, J., Cooper, L., Kurç, T., Brat, D. J., & Saltz, J. (2011) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2011.6091629 · Cited by 22

Active contour driven by multi-scale local binary fitting and Kullback-Leibler divergence for image segmentation

Liu, L., Cheng, D., Tian, F., Shi, D., & Wu, R. (2016) · Multimedia Tools and Applications · doi:10.1007/s11042-016-3603-z · Cited by 22

Sobolev Active Contours

Sundaramoorthi, G., Yezzi, A. J., & Mennucci, A. (2005) · Lecture notes in computer science · doi:10.1007/11567646_10 · Cited by 22

Snake-assisted quality-guided phase unwrapping for discontinuous phase fields

Zhao, M., Wang, H., & Kemao, Q. (2015) · Applied Optics · doi:10.1364/ao.54.007462 · Cited by 22

Real-time gradient vector flow on GPUs using OpenCL

Smistad, E., Elster, A. C., & Lindseth, F. (2012) · Journal of Real-Time Image Processing · doi:10.1007/s11554-012-0257-6 · Cited by 22

Unsupervised active contours driven by density distance and local fitting energy with applications to medical image segmentation

Shyu, K., Pham, V.-T., Tran, T.-T., & Lee, P. (2011) · Machine Vision and Applications · doi:10.1007/s00138-011-0373-5 · Cited by 22

Active volume models for 3D medical image segmentation

Shen, T., Li, H., Qian, Z. Y., & Huang, X. (2009) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2009.5206563 · Cited by 22

Self-affine snake for medical image segmentation

Saadatmand‐Tarzjan, M. (2015) · Pattern Recognition Letters · doi:10.1016/j.patrec.2015.03.006 · Cited by 22

Improving pollen classification with less training effort

Nguyen, N. R., Donalson-Matasci, M., & Shin, M. C. (2013) · Proceedings · doi:10.1109/wacv.2013.6475049 · Cited by 22

Gradient Vector Flow Field and Mass Region Extraction in Digital Mammograms

Zou, F., Zheng, Y., Zhou, Z., & Agyepong, K. (2008) · Proceedings - IEEE Symposium on Computer-Based Medical Systems · doi:10.1109/cbms.2008.117 · Cited by 22

Improved semi-automated segmentation of cardiac CT and MR images

Li, C., Jia, X. W., & Sun, Y. (2009) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2009.5192974 · Cited by 22

Expectations of Random Sets and Their Boundaries Using Oriented Distance Functions

Jankowski, H., & Stanberry, L. I. (2010) · Journal of Mathematical Imaging and Vision · doi:10.1007/s10851-009-0186-6 · Cited by 22

Automatic 3D segmentation of CT images based on active contour models

Jiang, H., & Cheng, Q. (2009) · International Conference on Computer-Aided Design and Computer Graphics (CAD/Graphics) · doi:10.1109/cadcg.2009.5246845 · Cited by 22

Extraction of the optic disk boundary in digital fundus images

Mendels, F., Heneghan, C., Harper, P. D., Reilly, R. B., & Thiran, J. (2003) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.1999.804304 · Cited by 22

Segmentation of the Left Ventricle from Cardiac MR Images Based on Radial GVF Snake

Liang, J., Ding, G., & Wu, Y. (2008) · International Conference on Biomedical Engineering and Informatics (BMEI) · doi:10.1109/bmei.2008.188 · Cited by 22

A novel automatic tongue image segmentation algorithm: Color enhancement method based on L*a*b* color space

Chen, L., Wang, D., Liu, Y., Gao, X., & Shang, H. (2015) · IEEE International Conference on Bioinformatics and Biomedicine (BIBM) · doi:10.1109/bibm.2015.7359818 · Cited by 22

Level set evolution model for image segmentation based on variable exponent p-Laplace equation

Huang, C., & Zeng, L. (2016) · Applied Mathematical Modelling · doi:10.1016/j.apm.2016.03.039 · Cited by 22

The Potential of Active Contour Models in Extracting Road Edges from Mobile Laser Scanning Data

Kumar, P., Lewis, P., & McCarthy, T. (2017) · Infrastructures · doi:10.3390/infrastructures2030009 · Cited by 22

A lumped parameter model of endoplasm flow in Physarum polycephalum explains migration and polarization-induced asymmetry during the onset of locomotion

Oettmeier, C., & Döbereiner, H.-G. (2019) · PLoS ONE · doi:10.1371/journal.pone.0215622 · Cited by 22

Using Dirichlet Free Form Deformation to Fit Deformable Models to Noisy 3-D Data

Ilić, S., & Fua, P. (2002) · Lecture notes in computer science · doi:10.1007/3-540-47967-8_47 · Cited by 22

Generalized sparse MRF appearance models

Donner, R., Langs, G., Mičušík, B., & Bischof, H. (2009) · Image and Vision Computing · doi:10.1016/j.imavis.2009.07.010 · Cited by 22

Using GVF Snake to Segment Liver from CT Images

Huang, S., Wang, B., & Huang, X. (2006) · IEEE/EMBS International Summer School on Medical Devices and Biosensors (ISSS-MDBS) · doi:10.1109/issmdbs.2006.360120 · Cited by 22

Fast edge integration based active contours for color images

Zheng, Y., Li, G., Sun, X., & Zhou, X. (2008) · Computers & Electrical Engineering · doi:10.1016/j.compeleceng.2008.09.006 · Cited by 22

Robust B-spline Snakes For Ultrasound Image Segmentation

Tauber, C., Batatia, H., & Ayache, A. (2008) · Journal of Signal Processing Systems · doi:10.1007/s11265-008-0186-6 · Cited by 22

Quantification of transcription factor expression from Arabidopsis images

Mace, D., Lee, J., Twigg, R. W., Colinas, J., Benfey, P. N., & Ohler, U. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl228 · Cited by 22

Computerized analysis of 3-D pulmonary nodule images in surrounding and internal structure feature spaces

Kawata, Y., Niki, N., Ohmatsu, H., Kusumoto, M., Kakinuma, R., Mori, K., Nishiyama, H., Eguchi, K., Kaneko, M., & Moriyama, N. (2002) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2001.958637 · Cited by 22

Automatic Segmentation and classification of Skin Lesion Images

Taouil, K., & Romdhane, N. B. (2006) · Distributed Frameworks for Multimedia Applications · doi:10.1109/dfma.2006.296918 · Cited by 22

Brain tumor segmentation based on GMM and active contour method with a model-aware edge map

Zhao, L., Wu, W., & Corso, J. J. (2012) · Cited by 22

Automatic segmentation of zona pellucida in HMC images of human embryos

Karlsson, A., Overgaard, N. C., & Heyden, A. (2004) · Proceedings - International Conference on Pattern Recognition/Proceedings/International Conference on Pattern Recognition · doi:10.1109/icpr.2004.1334580 · Cited by 22

Gradient vector flow: a new external force for snakes

Xu, C., & Prince, J. L. (2002) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.1997.609299 · Cited by 756

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