Snakes, shapes, and gradient vector flow

Snakes: Active contour models

Kass, M., Witkin, A., & Terzopoulos, D. (1988) · International Journal of Computer Vision · doi:10.1007/bf00133570 · Cited by 17,330

Methods of Theoretical Physics

Morse, P. M., Feshbach, H., & Hill, E. L. (1954) · American Journal of Physics · doi:10.1119/1.1933765 · Cited by 13,197

Determining optical flow

Horn, B. K. P., & Schunck, B. G. (1981) · Artificial Intelligence · doi:10.1016/0004-3702(81)90024-2 · Cited by 10,312

Methods of Mathematical Physics

Courant, R., & Hilbert, D. R. (1989) · Wiley eBooks · doi:10.1002/9783527617210 · Cited by 8,151

Determining Optical Flow

Horn, B. K. P., & Schunck, B. G. (1981) · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · doi:10.1117/12.965761 · Cited by 7,443

Fundamentals of digital image processing

Jain, A. K. (1988) · Cited by 7,000

Geodesic Active Contours

Caselles, V., Kimmel, R., & Sapiro, G. (1997) · International Journal of Computer Vision · doi:10.1023/a:1007979827043 · Cited by 5,285

Methods of theoretical physics

Domenicali, C. A. (1954) · Journal of the Franklin Institute · doi:10.1016/0016-0032(54)90634-1 · Cited by 4,893

Fundamentals of digital image processing

(1989) · Computer Vision Graphics and Image Processing · doi:10.1016/0734-189x(89)90041-8 · Cited by 4,703

Shape modeling with front propagation: a level set approach

Malladi, R., Sethian, J. A., & Vemuri, B. C. (1995) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/34.368173 · Cited by 3,166

Active contours driven by local and global probability distributions

Li, D., Li, W., & Liao, Q. (2013) · Journal of Visual Communication and Image Representation · doi:10.1016/j.jvcir.2013.03.007 · Cited by 32

Surface-based analysis methods for high-resolution functional magnetic resonance imaging

Khan, R., Zhang, Q., Darayan, S., Dhandapani, S., Katyal, S., Greene, C. A., Bajaj, C., & Ress, D. B. (2010) · Graphical Models · doi:10.1016/j.gmod.2010.11.002 · Cited by 32

Cell image recognition and visual servo control for automated cell injection

Ghanbari, A., Wang, W., Hann, C. E., Chase, J. G., & Chen, X. (2009) · International Conference on Autonomous Robots and Agents (ICARA) · doi:10.1109/icara.2000.4803986 · Cited by 32

A semi-automatic method for robust and efficient identification of neighboring muscle cells

Wang, Z. (2015) · Pattern Recognition · doi:10.1016/j.patcog.2015.12.009 · Cited by 32

Nonparametric Statistical Active Contour Based on Inclusion Degree of Fuzzy Sets

Gong, M., Li, H., Zhang, X., Zhao, Q., & Wang, B. (2015) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2015.2505328 · Cited by 32

A Novel Radiometric Control Set Sample Selection Strategy for Relative Radiometric Normalization of Multitemporal Satellite Images

Moghimi, A., Mohammadzadeh, A., Çelik, T., & Amani, M. (2020) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2020.2995394 · Cited by 32

Automatic quantification of epicardial adipose tissue volume

Li, X., Sun, Y., Xu, L., Greenwald, S. E., Zhang, L., Zhang, R., You, H., & Yang, B. (2021) · Medical Physics · doi:10.1002/mp.15012 · Cited by 33

Quantitative Muscle Mri Biomarkers in Duchenne Muscular Dystrophy: Cross-Sectional Correlations with Age and Functional Tests

Sherlock, S. P., Zhang, Y., Binks, M. H., & Marraffino, S. (2021) · Biomarkers in Medicine · doi:10.2217/bmm-2020-0801 · Cited by 32

An Optimal Unsupervised Satellite Image Segmentation Approach Based On Pearson System And K-Means Clustering Algorithm Initialization

Rekik, A., Zribi, M., Hamida, A. B., & Benjelloun, M. (2009) · doi:10.5281/zenodo.1085478 · Cited by 32

An active-contour based algorithm for the automated segmentation of dense yeast populations on transmission microscopy images

Bredies, K., & Wolinski, H. (2011) · Computing and Visualization in Science · doi:10.1007/s00791-012-0178-8 · Cited by 32

Alpha shape theory for 3D visualization and volumetric measurement of brain tumor progression using magnetic resonance images

Al-Tamimi, M. S. H., Sulong, G., & Shuaib, I. L. (2015) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2015.03.008 · Cited by 32

The Brain MR Image Segmentation Techniques and use of Diagnostic Packages

Dubey, R. B., Hanmandlu, M., Gupta, S. K., & Gupta, S. K. (2010) · Academic Radiology · doi:10.1016/j.acra.2009.12.017 · Cited by 32

3-D reconstruction of tissue components for atherosclerotic human arteries using ex vivo high-resolution MRI

Auer, M., Stollberger, R., Regitnig, P., Ebner, F., & Holzapfel, G. A. (2006) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2006.870485 · Cited by 32

Active contours for cell tracking

Ray, N., & Acton, S. T. (2003) · IEEE Southwest Symposium on Image Analysis and Interpretation (SSIAI) · doi:10.1109/iai.2002.999932 · Cited by 32

Interactive Medical Image Segmentation with United Snakes

Liang, J., McInerney, T., & Terzopoulos, D. (1999) · Lecture notes in computer science · doi:10.1007/10704282_13 · Cited by 32

Segmentation of Brain MRI

Xu, R., Luo, L., & Ohy, J. (2012) · InTech eBooks · doi:10.5772/27596 · Cited by 31

Automated cell segmentation with 3D fluorescence microscopy images

Kong, J., Wang, F., Teodoro, G., Liang, Y., Zhu, Y., Tucker‐Burden, C., & Brat, D. J. (2015) · IEEE International Symposium on Biomedical Imaging (ISBI) · doi:10.1109/isbi.2015.7164091 · Cited by 31

Detection of the intima and media layer thickness of ultrasound common carotid artery image using efficient active contour segmentation technique

Santhiyakumari, N., Rajendran, P. S., Madheswaran, M., & Suresh, S. (2011) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-011-0800-9 · Cited by 31

Fast numerical scheme for gradient vector flow computation using a multigrid method

Han, X., Xu, C., & Prince, J. L. (2007) · IET Image Processing · doi:10.1049/iet-ipr:20050225 · Cited by 31

Edge Probability and Pixel Relativity-Based Speckle Reducing Anisotropic Diffusion

Mishra, D., Chaudhury, S., Sarkar, M., Soin, A. S., & Sharma, V. (2017) · IEEE Transactions on Image Processing · doi:10.1109/tip.2017.2762590 · Cited by 31

Feature fusion and non-negative matrix factorization based active contours for texture segmentation

Gao, M., Chen, H., Zheng, S., & Fang, B. (2019) · Signal Processing · doi:10.1016/j.sigpro.2019.01.021 · Cited by 31

CVNet: Contour Vibration Network for Building Extraction

Xu, Z., Xu, C., Cui, Z., Zheng, X., & Yang, J. J. (2022) · 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/cvpr52688.2022.00144 · Cited by 31

Local Statistic Based Region Segmentation with Automatic Scale Selection

Piovano, J., & Papadopoulo, T. (2008) · Lecture notes in computer science · doi:10.1007/978-3-540-88688-4_36 · Cited by 31

Coupled snakelets for curled text-line segmentation from warped document images

Bukhari, S. S., Faisal Shafait, B., & Breuel, T. M. (2011) · International Journal on Document Analysis and Recognition (IJDAR) · doi:10.1007/s10032-011-0176-2 · Cited by 31

Nucleus and cytoplast contour detector from a cervical smear image

Pai, P.-Y., Chang, C., & Chan, Y. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2011.06.034 · Cited by 31

Automated Contour Mapping With a Regional Deformable Model

Chao, M., Li, T., Schreibmann, E., Koong, A. C., & Xing, L. (2008) · International Journal of Radiation Oncology*Biology*Physics · doi:10.1016/j.ijrobp.2007.09.057 · Cited by 31

Image denoising using anisotropic second and fourth order diffusions based on gradient vector convolution

Wang, H., Wang, Y., & Ren, W. (2012) · Computer Science and Information Systems · doi:10.2298/csis120219060w · Cited by 31

Geometry-Driven Polarity in Motile Amoeboid Cells

Nagel, O., Güven, C., Theves, M., Driscoll, M., Losert, W., & Beta, C. (2014) · PLoS ONE · doi:10.1371/journal.pone.0113382 · Cited by 31

Automatic classification of atypical lymphoid B cells using digital blood image processing

Alférez, S., Merino, A., Delgado, L. E. M., Ordóñez, M. R., Bigorra, L., & Rodellar, J. (2013) · International Journal of Laboratory Hematology · doi:10.1111/ijlh.12175 · Cited by 31

Image Segmentation Techniques

Zheng, C., & Sun, D. (2008) · Elsevier eBooks · doi:10.1016/b978-012373642-0.50005-3 · Cited by 31

Generating discriminating cartoon faces using interacting snakes

Hsu, R.-L., & Jain, A. K. (2003) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2003.1240113 · Cited by 31

A variational approach for the segmentation of the left ventricle in MR cardiac images

Nikos Paragios, A. (2002) · doi:10.1109/vlsm.2001.938894 · Cited by 31

Universal consensus 3D segmentation of cells from 2D segmented stacks

Zhou, F., Marin, Z., Yapp, C., Zou, Q., Nanes, B. A., Daetwyler, S., Jamieson, A. R., Islam, M. T., Jenkins, E. M., Gihana, G. M., et al. (2025) · Nature Methods · doi:10.1038/s41592-025-02887-w · Cited by 32

Enhanced Decoupled Active Contour Using Structural and Textural Variation Energy Functionals

Lui, D., Scharfenberger, C., Fergani, K., Wong, A. K. C., & Clausi, D. A. (2014) · IEEE Transactions on Image Processing · doi:10.1109/tip.2013.2295752 · Cited by 30

The automated detection and recognition of internal waves

Simonin, D., Tatnall, A. R. L., & Robinson, I. S. (2009) · International Journal of Remote Sensing · doi:10.1080/01431160802621218 · Cited by 30

Genetic algorithm and self organizing map based fuzzy hybrid intelligent method for color image segmentation

Khan, A., & Jaffar, M. A. (2015) · Applied Soft Computing · doi:10.1016/j.asoc.2015.03.029 · Cited by 30

A New Region-Based Active Contour Model with Skewness Wavelet Energy for Segmentation of SAR Images

Akbarizadeh, G., Rezai-Rad, G. A., & Shokouhi, S. B. (2010) · IEICE Transactions on Information and Systems · doi:10.1587/transinf.e93.d.1690 · Cited by 30

Automated analysis of retinal vascular network connectivity

Al-Diri, B., Hunter, A., STEEL, D. H., & Habib, M. (2010) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2009.12.013 · Cited by 30

Assistive system based on nerve detection and needle navigation in ultrasound images for regional anesthesia

Hadjerci, O., Hafiane, A., Morette, N., Novales, C., Vieyres, P., & Delbos, A. (2016) · Expert Systems with Applications · doi:10.1016/j.eswa.2016.05.002 · Cited by 30

Simultaneous left and right ventricle segmentation using topology preserving level sets

Arrieta, C., Uribe, S. A., Sing‐Long, C., Hurtado, D. E., Andía, M. E., Pablo Irarrázaval, M., & Cristián Tejos, N. (2016) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2016.11.002 · Cited by 30

Thermal Infrared Pedestrian Image Segmentation Using Level Set Method

Qiao, Y., Wei, Z., & Zhao, Y. J. (2017) · Sensors · doi:10.3390/s17081811 · Cited by 30

Fast segmentation of the left ventricle in cardiac MRI using dynamic programming

Santiago, C., Nascimento, J. C., & Marques, J. S. (2017) · Computer Methods and Programs in Biomedicine · doi:10.1016/j.cmpb.2017.10.028 · Cited by 30

Ultrasound image segmentation with multilevel threshold based on differential search algorithm

Shao, D., Chunrong, X., Xiang, Y., Gui, P., Xiaofang, Z., Zhang, C., & Yu, Z. (2019) · IET Image Processing · doi:10.1049/iet-ipr.2018.6150 · Cited by 30

Automatic Detection and Measurement of Spinous Process Curve on Clinical Ultrasound Spine Images

Zeng, H., Lou, E. H. M., Ge, S., Liu, Z., & Zheng, R. (2020) · IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control · doi:10.1109/tuffc.2020.3047622 · Cited by 30

Salmonella Typhimurium Triggers Extracellular Traps Release in Murine Macrophages

Mónaco, A., Canales-Huerta, N., de la Jara, J. J., Härtel, S., Chabalgoity, J. A., Moreno, M. C., & Scavone, P. (2021) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2021.639768 · Cited by 31

Beyond automatic medical image segmentation—the spectrum between fully manual and fully automatic delineation

Trimpl, M. J., Primakov, S. P., Lambin, P., Stride, E., Vallis, K. A., & Gooding, M. J. (2022) · Physics in Medicine and Biology · doi:10.1088/1361-6560/ac6d9c · Cited by 31

Quantification of aortic compliance in mice using radial phase contrast MRI

Zhao, X., Pratt, R., & Wansapura, J. P. (2009) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.21846 · Cited by 30

An adaptive level set method for interactive segmentation of intracranial tumors

Droske, M., Meyer, B., Rumpf, M., & Schaller, C. (2005) · Neurological Research · doi:10.1179/016164105x48842 · Cited by 30

Comparison of two‐dimensional and three‐dimensional iterative watershed segmentation methods in hepatic tumor volumetrics

Ray, S., Hagge, R. J., Gillen, M. A., Cerejo, M. C., Shakeri, S., Beckett, L. A., Greasby, T. A., & Badawi, R. D. (2008) · Medical Physics · doi:10.1118/1.3013561 · Cited by 30

A Diffusion Tensor Imaging Tractography Algorithm Based on Navier–Stokes Fluid Mechanics

Hageman, N. S., Toga, A. W., Narr, K. L., & Shattuck, D. W. (2008) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2008.2004403 · Cited by 30

Improved interactive medical image segmentation using Enhanced Intelligent Scissors (EIS)

Mishra, A. K., Wong, A. K. C., Zhang, W., Clausi, D. A., & Fieguth, P. (2008) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2008.4649855 · Cited by 30

Segmentation of Brain MR Images Using a Charged Fluid Model

Chang, H.-H., Valentino, D. J., Duckwiler, G., & Toga, A. W. (2007) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2007.895104 · Cited by 30

Coupled Snakelet Model for Curled Textline Segmentation of Camera-Captured Document Images

Bukhari, S. S., Faisal Shafait, B., & Breuel, T. M. (2009) · IAPR International Conference on Document Analysis and Recognition (ICDAR) · doi:10.1109/icdar.2009.204 · Cited by 30

A Novel Algorithm for Extraction of the Layers of the Cornea

Eichel, J. A., Mishra, A. K., Fieguth, P., Clausi, D. A., & Bizheva, K. K. (2009) · Canadian Conference on Computer and Robot Vision · doi:10.1109/crv.2009.22 · Cited by 30

Cutting tool wear measurement by using active contour model based image processing

Xiong, G., Liu, J., & Avila, A. (2011) · IEEE International Conference on Mechatronics and Automation (ICMA) · doi:10.1109/icma.2011.5985741 · Cited by 30

Automatic Image Processing Algorithm to Detect Hard Exudates based on Mixture Models

Sá‎nchez, C. I., Mayo-Íscar, A., García, M., López, M. I., & Hornero, R. (2006) · Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) · doi:10.1109/iembs.2006.260434 · Cited by 30

Automated cervical cancer detection through RGVF segmentation and SVM classification

Sajeena, T. A., & Jereesh, A. S. (2015) · International Conference on Computing and Network Communications · doi:10.1109/coconet.2015.7411260 · Cited by 30

Detection of Sinkhole Hazards using Airborne Laser Scanning Data

Filin, S., & Baruch, A. (2010) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.76.5.577 · Cited by 30

3D exemplar‐based random walks for tooth segmentation from cone‐beam computed tomography images

Pei, Y., Ai, X., Zha, H., Xu, T., & Ma, G. (2016) · Medical Physics · doi:10.1118/1.4960364 · Cited by 31

A deep Boltzmann machine-driven level set method for heart motion tracking using cine MRI images

Wu, J., Mazur, T. R., Ruan, S., Lian, C., Daniel, N., Lashmett, H., Ochoa, L., Zoberi, I., Anastasio, M. A., Gach, H. M., et al. (2018) · Medical Image Analysis · doi:10.1016/j.media.2018.03.015 · Cited by 30

A new fast morphological geodesic active contour method for lung CT image segmentation

Medeiros, A. G., Guimarães, M. T., Peixoto, S. A., Santos, L. D. O., Barros, A. C. D. S., Rebouças, E. D. S., de Albuquerque, V. H. C., & Filho, P. P. R. (2019) · Measurement · doi:10.1016/j.measurement.2019.05.078 · Cited by 30

Leaf Segmentation and Tracking Using Probabilistic Parametric Active Contours

Vylder, J. D., Ochoa, D., Philips, W. R., Chaerle, L., & Straeten, D. V. D. (2011) · Lecture notes in computer science · doi:10.1007/978-3-642-24136-9_7 · Cited by 30

Curvelet-based geodesic snakes for image segmentation with multiple objects

Shan, H., & Ma, J. (2009) · Pattern Recognition Letters · doi:10.1016/j.patrec.2009.10.018 · Cited by 30

Segmentation of Drosophila RNAI Fluorescence Images Using Level Sets

Xiong, G., Zhou, X., Ji, L., Bradley, P. L., Perrimon, N., & Wong, S. T. C. (2006) · Proceedings - International Conference on Image Processing · doi:10.1109/icip.2006.312365 · Cited by 30

Lateral Ventricular Size in Extremely Premature Infants: 3D MRI Confirms 2D Ultrasound Measurements

Horsch, S., Bengtsson, J., Nordell, A., Lagercrantz, H., Ådén, U., & Blennow, M. (2008) · Ultrasound in Medicine & Biology · doi:10.1016/j.ultrasmedbio.2008.09.006 · Cited by 30

Automated segmentation of routinely hematoxylin-eosin-stained microscopic images by combining support vector machine clustering and active contour models.

Glotsos, D. T., Σπυρίδωνος, Π. Π., Cavouras, D. A., Σπυρίδωνος, Π. Π., Dadioti, P., & Nikiforidis, G. (2004) · PubMed · Cited by 30

Image segmentation functional model

Zouagui, T., Benoit-Cattin, H., & Odet, C. (2004) · Pattern Recognition · doi:10.1016/j.patcog.2003.12.014 · Cited by 30

Ultrasound Guided Surgery: Image Processing and Navigation

Langø, T. (2000) · NORA - Norwegian Open Research Archives · Cited by 30

Development of an optical defect inspection algorithm based on an active contour model for large steel roller surfaces

Yang, J., Li, X., Xu, J., Cao, Y., Zhang, Y., Wang, L., & Jiang, S. (2018) · Applied Optics · doi:10.1364/ao.57.002490 · Cited by 29

Attractive deep morphology-aware active contour network for vertebral body contour extraction with extensions to heterogeneous and semi-supervised scenarios

Zhao, S., Wang, J., Wang, X., Wang, Y., Zheng, H., Chen, B., Zeng, A., Wei, F., Al-Kindi, S. G., & Li, S. (2023) · Medical Image Analysis · doi:10.1016/j.media.2023.102906 · Cited by 29

Sparse Texture Active Contour

Gao, Y., Sylvain Bouix, A., Shenton, M. E., & Tannenbaum, A. (2013) · IEEE Transactions on Image Processing · doi:10.1109/tip.2013.2263147 · Cited by 29

Rectilinear building roof contour extraction based on snakes and dynamic programming

Fazan, A. J., & Póz, A. P. D. (2013) · International Journal of Applied Earth Observation and Geoinformation · doi:10.1016/j.jag.2013.03.003 · Cited by 29

Active contour model driven by linear speed function for local segmentation with robust initialization and applications in MR brain images

Zheng, Q., Dong, E., Cao, Z., Wenyan, S., & Li, Z. (2013) · Signal Processing · doi:10.1016/j.sigpro.2013.10.008 · Cited by 29

Lumen detection for capsule endoscopy

Zabulis, X., Argyros, A., & Tsakiris, D. P. (2008) · IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) · doi:10.1109/iros.2008.4650969 · Cited by 29

An efficient method for segmentation step of automated white blood cell classifications

Theerapattanakul, J., Plodpai, J., & Pintavirooj, C. (2004) · IEEE Region 10 Conference (TENCON) · doi:10.1109/tencon.2004.1414389 · Cited by 29

Multi-layer segmentation framework for cell nuclei using improved GVF Snake model, Watershed, and ellipse fitting

Jia, D., Zhang, C., Wu, N., Guo, Z., & Ge, H. (2021) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2021.102516 · Cited by 29

Combining natural and artificial intelligence for robust automatic anatomy segmentation: Application in neck and thorax auto‐contouring

Udupa, J. K., Liu, T., Jin, C., Zhao, L., Odhner, D., Tong, Y., Agrawal, V., Pednekar, G. V., Nag, S., Kotia, T., et al. (2022) · Medical Physics · doi:10.1002/mp.15854 · Cited by 29

3D Brain Segmentation Using Dual‐Front Active Contours with Optional User Interaction

Li, H., Yezzi, A. J., & Cohen, L. D. (2006) · International Journal of Biomedical Imaging · doi:10.1155/ijbi/2006/53186 · Cited by 29

Localisation of the optic disc by means of GA-optimised Topological Active Nets

Novo, J., Penedo, M. G., & Santos, J. C. A. (2009) · Image and Vision Computing · doi:10.1016/j.imavis.2009.02.011 · Cited by 29

On the segmentation of vascular geometries from medical images

Radaelli, A., & Peiró, J. (2009) · International Journal for Numerical Methods in Biomedical Engineering · doi:10.1002/cnm.1290 · Cited by 29

Adaptive shape prior for recognition and variational segmentation of degraded historical characters

Bar-Yosef, I., Mokeichev, A., Kedem, K., Dinstein, I., & Ehrlich, U. (2008) · Pattern Recognition · doi:10.1016/j.patcog.2008.10.005 · Cited by 29

Temporal Spectral Residual for fast salient motion detection

Cui, X., Liu, Q., Zhang, S., Yang, F. H., & Metaxas, D. (2012) · Neurocomputing · doi:10.1016/j.neucom.2011.12.033 · Cited by 29

Interactive Medical Image Segmentation Using Snake and Multiscale Curve Editing

Zhou, W., & Xie, Y. (2013) · Computational and Mathematical Methods in Medicine · doi:10.1155/2013/325903 · Cited by 29

Detection of blob objects in microscopic zebrafish images based on gradient vector diffusion

Li, G., Liu, T., Nie, J., Guo, L., Malicki, J. J., Mara, A., Holley, S. A., Xia, W., & Wong, S. T. C. (2007) · Cytometry Part A · doi:10.1002/cyto.a.20436 · Cited by 29

Segmentation of elastographic images using a coarse-to-fine active contour model

Liu, W., Zagzebski, J. A., Varghese, T., Dyer, C. R., Techavipoo, U., & Hall, T. J. (2006) · Ultrasound in Medicine & Biology · doi:10.1016/j.ultrasmedbio.2005.11.011 · Cited by 29

Automatic detection of brain tumors in MR images

Dvorak, P., Kropatsch, W. G., & Bartusek, K. (2013) · International Conference on Telecommunications and Signal Processing (TSP) · doi:10.1109/tsp.2013.6614000 · Cited by 29

Stretching and relaxation of vesicles

Zhou, H., Gabilondo, B. B., Losert, W., & van de Water, W. (2011) · Physical Review E · doi:10.1103/physreve.83.011905 · Cited by 29

Locating Brain Tumors from MR Imagery Using Symmetry

Ray, N., Saha, B. N., & Brown, M. R. G. (2007) · Asilomar Conference on Signals, Systems and Computers (ACSSC) · doi:10.1109/acssc.2007.4487200 · Cited by 29

Discrete gradient methods for solving variational image regularisation models

Grimm, V., McLachlan, R. I., McLaren, D. I., Quispel, G. R. W., & Schönlieb, C. (2017) · Journal of Physics A Mathematical and Theoretical · doi:10.1088/1751-8121/aa747c · Cited by 29

Segmentation, Tracing, and Quantification of Microglial Cells from 3D Image Stacks

Abdolhoseini, M., Kluge, M. G., Walker, F. R., & Johnson, S. J. (2019) · Scientific Reports · doi:10.1038/s41598-019-44917-6 · Cited by 29

Radiomics-Based Assessment of Primary Sjögren's Syndrome From Salivary Gland Ultrasonography Images

Vukićević, A. M., Milić, V., Zabotti, A., Hočevar, A., Lucia, O. D., Filippou, G., Frangi, A. F., Tzioufas, A. G., Vita, S. D., & Filipović, N. (2019) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2019.2923773 · Cited by 29

Development of automatized new indices for radiological assessment of chest-wall deformity and its quantitative evaluation

Kim, H. C., Park, H. J., Ham, S. Y., Nam, K. W., Choi, S. Y., Oh, J., Choi, H., Jeong, G. S., Park, S., Kim, M.-G., et al. (2008) · Medical & Biological Engineering & Computing · doi:10.1007/s11517-008-0367-2 · Cited by 29

Detecting rotational symmetries

Prasad, V. S. N., & Davis, L. S. (2005) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2005.71 · Cited by 29

Semi-supervised discriminative classification with application to tumorous tissues segmentation of MR brain images

Song, Y., Zhang, C., Lee, J., Wang, F., Xiang, S., & Zhang, D. (2008) · Pattern Analysis and Applications · doi:10.1007/s10044-008-0104-3 · Cited by 29

Global optimality of gradient vector flow

Xu, C., & Prince, J. L. (2000) · Cited by 29

Segmentation of 3D holographic images using bivariate jointly distributed region snake

Daneshpanah, M., & Javidi, B. (2006) · Optics Express · doi:10.1364/oe.14.005143 · Cited by 29

Reflection Symmetry-Integrated Image Segmentation

Sun, Y., & Bhanu, B. (2011) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2011.259 · Cited by 28

Pop out many small structures from a very large microscopic image

Bernardis, E., & Yu, S. X. (2011) · Medical Image Analysis · doi:10.1016/j.media.2011.06.009 · Cited by 28

A multi-compartment segmentation framework with homeomorphic level sets

Fan, X., Bazin, P., & Prince, J. L. (2008) · 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.2008.4587475 · Cited by 28

A Novel 3D Joint Markov-Gibbs Model for Extracting Blood Vessels from PC–MRA Images

El-Baz, A. S., Gimel’farb, G., Falk, R. L., El‐Ghar, M. A., Kumar, V., & Heredia, D. R. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-04271-3_114 · Cited by 28

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

Generalized gradient vector flow external forces for active contours

Xu, C., & Prince, J. L. (1998) · Signal Processing · doi:10.1016/s0165-1684(98)00140-6 · Cited by 698

An Edge Preserving Gradient Vector Flow for Active Contours

Jia, X., & Wang, Y. (2009) · International Congress on Image and Signal Processing (CISP) · doi:10.1109/cisp.2009.5304695 · Cited by 3

Gradient Vector Flow over Manifold for Active Contours

Lu, S., & Wang, Y. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-12307-8_14 · Cited by 12

Active contours with normally generalized gradient vector flow external force

赵恒博, 刘利雄, 张麒, 姚宇华, & 刘宝 (2012) · 北京理工大学学报：英文版 · Cited by 1