Seam carving for content-aware image resizing, ACM Transactions on Graphics (SIGGRAPH), vol.26, issue.3, 2007. ,
Motion segmentation with occlusions on the superpixel graph, 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops, 2009. ,
DOI : 10.1109/ICCVW.2009.5457630
Interactive graph cuts for optimal boundary & region segmentation of objects in N-D images, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, 2001. ,
DOI : 10.1109/ICCV.2001.937505
Mean shift: a robust approach toward feature space analysis, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.24, issue.5, pp.603-619, 2002. ,
DOI : 10.1109/34.1000236
Spectral Segmentation with Multiscale Graph Decomposition, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), 2005. ,
DOI : 10.1109/CVPR.2005.332
Using the triangle inequality to accelerate k-means, International Conference on Machine Learning, 2003. ,
The Pascal Visual Object Classes (VOC) Challenge, International Journal of Computer Vision, vol.73, issue.2, pp.303-338, 2010. ,
DOI : 10.1007/s11263-009-0275-4
Efficient Graph-Based Image Segmentation, International Journal of Computer Vision, vol.59, issue.2, pp.167-181, 2004. ,
DOI : 10.1023/B:VISI.0000022288.19776.77
Class segmentation and object localization with superpixel neighborhoods, 2009 IEEE 12th International Conference on Computer Vision, 2009. ,
DOI : 10.1109/ICCV.2009.5459175
Harmony potentials for joint classification and segmentation, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010. ,
DOI : 10.1109/CVPR.2010.5540048
Multi-Class Segmentation with Relative Location Prior, International Journal of Computer Vision, vol.30, issue.6, pp.300-316, 2008. ,
DOI : 10.1007/s11263-008-0140-x
A local search approximation algorithm for k-means clustering, Eighteenth annual symposium on Computational geometry, pp.10-18, 2002. ,
A simple linear time (1+e)-approximation algorithm for k-means clustering in any dimensions, Annual IEEE Symposium on Foundations of Computer Science, pp.454-462, 2004. ,
Graphcut textures, ACM Transactions on Graphics, vol.22, issue.3, pp.277-286, 2003. ,
DOI : 10.1145/882262.882264
TurboPixels: Fast Superpixels Using Geometric Flows, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.31, issue.12, 2009. ,
DOI : 10.1109/TPAMI.2009.96
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.161.240
Lazy snapping, ACM Transactions on Graphics, vol.23, issue.3, pp.303-308, 2004. ,
DOI : 10.1145/1015706.1015719
Least squares quantization in PCM, IEEE Transactions on Information Theory, issue.2, pp.28129-137, 1982. ,
A Fully Automated Approach to Segmentation of Irregularly Shaped Cellular Structures in EM Images, International Conference on Medical Image Computing and Computer Assisted Intervention, 2010. ,
DOI : 10.1007/978-3-642-15745-5_57
Supervoxel-Based Segmentation of Mitochondria in EM Image Stacks With Learned Shape Features, IEEE Transactions on Medical Imaging, vol.31, issue.2, p.30, 2011. ,
DOI : 10.1109/TMI.2011.2171705
A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, 2001. ,
DOI : 10.1109/ICCV.2001.937655
Guiding model search using segmentation, Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1, 2005. ,
DOI : 10.1109/ICCV.2005.112
Normalized cuts and image segmentation, IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI), vol.22, issue.8, pp.888-905, 2000. ,
TextonBoost for Image Understanding: Multi-Class Object Recognition and Segmentation by Jointly Modeling Texture, Layout, and Context, International Journal of Computer Vision, vol.62, issue.1???2, 2009. ,
DOI : 10.1007/s11263-007-0109-1
Quick Shift and Kernel Methods for Mode Seeking, European Conference on Computer Vision (ECCV), 2008. ,
DOI : 10.1007/978-3-540-88693-8_52
Superpixels and Supervoxels in an Energy Optimization Framework, European Conference on Computer Vision (ECCV), 2010. ,
DOI : 10.1007/978-3-642-15555-0_16
Local k-means algorithm for color image quantization, Graphics Interface, pp.128-135, 1995. ,
Watersheds in digital spaces: an efficient algorithm based on immersion simulations, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.13, issue.6, pp.583-598, 1991. ,
DOI : 10.1109/34.87344
Layered object detection for multi-class segmentation, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2010. ,
DOI : 10.1109/CVPR.2010.5540070
Stereo for Image-Based Rendering using Image Over-Segmentation, International Journal of Computer Vision, vol.22, issue.7, pp.49-65, 2007. ,
DOI : 10.1007/s11263-006-0018-8
This article has been accepted for publication in a future issue of this journal, but has not been fully edited ,
Estimates of worldwide burden of cancer in 2008: GLOBO- CAN, International Journal of Cancer, vol.127, issue.12, pp.2893-2917, 2008. ,
Global cancer statistics, CA: A Cancer Journal for Clinicians, vol.82, issue.19 suppl, pp.69-90, 2011. ,
DOI : 10.3322/caac.20107
American cancer society guidelines for breast cancer screening: update, 2003. ,
Diagnostic Accuracy of Mammography, Clinical Examination, US, and MR Imaging in Preoperative Assessment of Breast Cancer, Radiology, vol.233, issue.3, pp.830-849, 2004. ,
DOI : 10.1148/radiol.2333031484
Solid breast nodules: use of sonography to distinguish between benign and malignant lesions., Radiology, vol.196, issue.1, pp.123-157, 1995. ,
DOI : 10.1148/radiology.196.1.7784555
Multimodality Computer-Aided Breast Cancer Diagnosis with FFDM and DCE-MRI, Academic Radiology, vol.17, issue.9, p.1158, 2010. ,
DOI : 10.1016/j.acra.2010.04.015
The contribution of ultrasonography to the differential diagnosis of breast cancer, Neoplasma, vol.41, issue.6, p.341, 1994. ,
Malignant breast masses detected only by ultrasound. A retrospective review, Cancer, vol.13, issue.4, pp.626-630, 1995. ,
DOI : 10.1002/1097-0142(19950815)76:4<626::AID-CNCR2820760413>3.0.CO;2-Z
Ultrasonics: Data, Equations, and Their Practical Uses, p.520, 2008. ,
DOI : 10.1201/b11173
Perception research in medical imaging, The British Journal of Radiology, vol.78, issue.932, pp.683-685, 2005. ,
DOI : 10.1259/bjr/72087985
Toward a standardized breast ultrasound lexicon, BI-RADS: Ultrasound, Seminars in roentgenology, pp.217-225, 2001. ,
DOI : 10.1053/sroe.2001.25125
Sonography of solid breast lesions: observer variability of lesion description and assessment., American Journal of Roentgenology, vol.172, issue.6, pp.1621-1625, 1999. ,
DOI : 10.2214/ajr.172.6.10350302
Statistics Notes: Diagnostic tests 2: predictive values, BMJ, vol.309, issue.6947, p.102, 1994. ,
DOI : 10.1136/bmj.309.6947.102
and AAPM, Medical Physics, vol.31, issue.1, p.5799, 2008. ,
DOI : 10.1056/NEJMoa066099
Estimates of the cancer incidence and mortality in Europe in 2006, Annals of Oncology, vol.18, issue.3, pp.581-592, 2006. ,
DOI : 10.1093/annonc/mdl498
Breast cancer: hormones and other risk factors, Maturitas, vol.38, issue.1, pp.103-113, 2001. ,
DOI : 10.1016/S0378-5122(00)00196-1
Disparities in breast cancer mortality trends between 30 European countries: retrospective trend analysis of WHO mortality database, BMJ, vol.341, issue.aug11 1, 2010. ,
DOI : 10.1136/bmj.c3620
Looking back on the millennium in medicine, New England Journal Medicine, vol.342, issue.1, pp.42-49, 2000. ,
Better breast cancer detection, IEEE Spectrum, vol.38, issue.5, 2001. ,
DOI : 10.1109/6.920031
Analysis of cancers missed at screening mammography., Radiology, vol.184, issue.3, pp.613-617, 1992. ,
DOI : 10.1148/radiology.184.3.1509041
Mammographic Density and the Risk and Detection of Breast Cancer, New England Journal of Medicine, vol.356, issue.3, pp.227-236, 2007. ,
DOI : 10.1056/NEJMoa062790
Diagnostic Breast Imaging, American Journal of Roentgenology, vol.177, issue.5, pp.1094-1094, 2001. ,
DOI : 10.2214/ajr.177.5.1771094
Breast cancer detection with sonography and mammography: comparison using state-of-the-art equipment, American Journal of Roentgenology, vol.140, issue.5, pp.843-845, 1983. ,
DOI : 10.2214/ajr.140.5.843
Emerging technologies in breast cancer detection, Radiology management, vol.26, issue.4, pp.16-27, 2004. ,
Frictional contact mechanics methods for soft materials: Application to tracking breast cancers, Journal of Biomechanics, vol.41, issue.1, pp.69-77, 2008. ,
DOI : 10.1016/j.jbiomech.2007.07.016
Evaluation of New Imaging Procedures for Breast Cancer, Early Detection of Breast Cancer, pp.55-61, 1984. ,
DOI : 10.1007/978-3-642-82031-1_7
Comparison of Full-Field Digital Mammography with Screen-Film Mammography for Cancer Detection: Results of 4,945 Paired Examinations, Radiology, vol.218, issue.3, pp.873-880, 2001. ,
DOI : 10.1148/radiology.218.3.r01mr29873
Fundamentals of breast tomosynthesis White Paper, Hologic Inc., WP-00007, 2008. ,
Real-time spatial compound imaging: application to breast, vascular, and musculoskeletal ultrasound, Seminars in ultrasound, CT and MRI, pp.50-64, 2001. ,
Real-time spatial compound imaging in breast ultrasound, Ultrasound in Medicine & Biology, vol.28, issue.2, pp.155-163, 2002. ,
DOI : 10.1016/S0301-5629(01)00490-2
Real time spatial compound imaging in breast ultrasound: technology and early clinical experience, pp.35-43, 1999. ,
Ultrasound for breast cancer screening and staging, Radiologic Clinics of North America, vol.40, issue.3, p.431, 2002. ,
DOI : 10.1016/S0033-8389(01)00014-8
The role of magnetic resonance imaging in the assessment of local recurrent breast carcinoma, Clinical Radiology, vol.43, issue.3, pp.197-204, 1991. ,
DOI : 10.1016/S0009-9260(05)80479-9
Experience with Mammography in a Tumor Institution, Radiology, vol.75, issue.6, pp.894-900, 1960. ,
DOI : 10.1148/75.6.894
Further pilot echographic studies on the histologic structure of tumors of the living intact human breast, The American journal of pathology, vol.28, issue.5, p.839, 1952. ,
The History of Breast Ultrasound, Journal of Ultrasound in Medicine, vol.23, issue.7, pp.887-894, 2004. ,
DOI : 10.7863/jum.2004.23.7.887
The role of ultrasound in breast cancer screening. A consensus statement by the European Group for breast cancer screening, European Journal of Cancer, vol.34, issue.4, pp.449-450, 1998. ,
DOI : 10.1016/S0959-8049(97)10066-1
Ultrasound of the Breast, World Journal of Surgery, vol.24, issue.2, pp.143-157, 2000. ,
DOI : 10.1007/s002689910027
Screening for Breast Cancer, Annals of Internal Medicine, vol.138, issue.9, pp.347-360, 2002. ,
DOI : 10.7326/0003-4819-138-9-200305060-00022
Occult cancer in women with dense breasts: detection with screening US--diagnostic yield and tumor characteristics., Radiology, vol.207, issue.1, pp.191-199, 1998. ,
DOI : 10.1148/radiology.207.1.9530316
Comparison of the Performance of Screening Mammography, Physical Examination, and Breast US and Evaluation of Factors that Influence Them: An Analysis of 27,825 Patient Evaluations, Radiology, vol.225, issue.1, pp.165-175, 2002. ,
DOI : 10.1148/radiol.2251011667
Breast tomosynthesis and digital mammography: a comparison of breast cancer visibility and BIRADS classification in a population of cancers with subtle mammographic findings, European Radiology, vol.130, issue.12, pp.2817-2825, 2008. ,
DOI : 10.1007/s00330-008-1076-9
The role of US in breast imaging., Radiology, vol.177, issue.2, 1990. ,
DOI : 10.1148/radiology.177.2.2217759
Follow-up of Palpable Circumscribed Noncalcified Solid Breast Masses at Mammography and US: Can Biopsy Be Averted?, Radiology, vol.233, issue.3, pp.850-856, 2004. ,
DOI : 10.1148/radiol.2333031845
Cystic Masses of the Breast, American Journal of Roentgenology, vol.194, issue.2, pp.122-133, 2010. ,
DOI : 10.2214/AJR.09.3688
Teaching atlas of breast ultrasound, Thieme, 1996. ,
Field: A program for simulating ultrasound systems, 10th Nordicbaltic Conference on Biomedical Imaging, Citeseer, pp.351-353, 1996. ,
BI-RADS for Sonography: Positive and Negative Predictive Values of Sonographic Features, American Journal of Roentgenology, vol.184, issue.4, pp.1260-1265, 2005. ,
DOI : 10.2214/ajr.184.4.01841260
BI-RADS Lexicon for US and Mammography: Interobserver Variability and Positive Predictive Value, Radiology, vol.239, issue.2, pp.385-391, 2006. ,
DOI : 10.1148/radiol.2392042127
Intraobserver interpretation of breast ultrasonography following the BI-RADS classification, European Journal of Radiology, vol.74, issue.3, pp.525-528, 2010. ,
DOI : 10.1016/j.ejrad.2009.04.015
Medical Electronics, New England Journal of Medicine, vol.252, issue.14, pp.580-585, 1955. ,
DOI : 10.1056/NEJM195504072521405
Improvement in Radiologists?? Detection of Clustered Microcalcifications on Mammograms, Investigative Radiology, vol.25, issue.10, p.1102, 1990. ,
DOI : 10.1097/00004424-199010000-00006
Fully automatic and segmentation-robust classification of breast tumors based on local texture analysis of ultrasound images, Pattern Recognition, vol.43, issue.1, 2010. ,
DOI : 10.1016/j.patcog.2009.06.002
Automatic segmentation of breast lesions on ultrasound, Medical Physics, vol.22, issue.8, 2001. ,
DOI : 10.1118/1.1386426
Watershed segmentation for breast tumor in 2-D sonography, Ultrasound in Medicine & Biology, vol.30, issue.5, pp.625-657, 2004. ,
DOI : 10.1016/j.ultrasmedbio.2003.12.001
Combining low-, high-level and empirical domain knowledge for automated segmentation of ultrasonic breast lesions, IEEE Transactions on Medical Imaging, vol.22, issue.2, 2003. ,
DOI : 10.1109/TMI.2002.808364
Lesion Segmentation in Breast Sonography, Digital Mammography, pp.39-45, 2010. ,
DOI : 10.1007/978-3-642-13666-5_6
Automated breast cancer detection and classification using ultrasound images: A survey, Pattern Recognition, vol.43, issue.1, pp.299-317, 2009. ,
DOI : 10.1016/j.patcog.2009.05.012
Contour segmentation in 2D ultrasound medical images with particle filtering, Machine Vision and Applications, pp.551-561, 2011. ,
DOI : 10.1007/s00138-010-0261-4
Computerized lesion segmentation of breast ultrasound based on marker-controlled watershed transformation, Medical Physics, vol.17, issue.4, p.82, 2010. ,
DOI : 10.1118/1.3265959
Segmentation of ultrasound B-mode images with intensity inhomogeneity correction, IEEE Transactions on Medical Imaging, vol.21, issue.1, pp.48-57, 2002. ,
DOI : 10.1109/42.981233
Evaluating lesion segmentation in breast ultrasound images related to lesion typology, Journal of Ultrasound in Medicine, 2013. ,
Cell-based graph cut for segmentation of 2D/3D sonographic breast images, 2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, pp.177-180, 2010. ,
DOI : 10.1109/ISBI.2010.5490384
Texture-Oriented Anisotropic Filtering and Geodesic Active Contours in Breast Tumor Ultrasound Segmentation, Journal of Mathematical Imaging and Vision, vol.11, issue.11, pp.81-97, 2007. ,
DOI : 10.1007/s10851-007-0015-8
A new automated method for the segmentation and characterization of breast masses on ultrasound images, Medical Physics, vol.33, issue.5, p.1553, 2009. ,
DOI : 10.1118/1.2207129
Phase- and GVF-Based Level Set Segmentation of Ultrasonic Breast Tumors, Journal of Applied Mathematics, vol.64, issue.2, pp.1-22, 2012. ,
DOI : 10.1016/j.compmedimag.2011.06.007
Computerized lesion detection on breast ultrasound, Medical Physics, vol.8, issue.7, pp.1438-1484, 2002. ,
DOI : 10.1118/1.1485995
Seed selection criteria for breast lesion segmentation in ultrasound images, MICCAI Workshop on Breast Image Analysis, pp.55-64, 2011. ,
Automatic Seed Placement for Breast Lesion Segmentation on US Images, Digital Mammography, pp.308-315, 2012. ,
DOI : 10.1007/978-3-642-31271-7_40
A Threshold Selection Method from Gray-Level Histograms, IEEE Transactions on Systems, Man, and Cybernetics, vol.9, issue.1, pp.285-296, 1975. ,
DOI : 10.1109/TSMC.1979.4310076
Level Set Contouring for Breast Tumor in Sonography, Journal of Digital Imaging, vol.8, issue.3, pp.238-247, 2007. ,
DOI : 10.1007/s10278-006-1041-6
Database-guided breast tumor detection and segmentation in 2D ultrasound images, Medical Imaging 2010: Computer-Aided Diagnosis, pp.762-405, 2010. ,
DOI : 10.1117/12.844558
Learning-based automatic breast tumor detection and segmentation in ultrasound images, 2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), pp.1-4, 2012. ,
DOI : 10.1109/ISBI.2012.6235878
A novel automatic seed point selection algorithm for breast ultrasound images, 2008 19th International Conference on Pattern Recognition, pp.1-4, 2008. ,
DOI : 10.1109/ICPR.2008.4761336
Completely Automated Segmentation Approach for Breast Ultrasound Images Using Multiple-Domain Features, Ultrasound in Medicine & Biology, vol.38, issue.2, pp.262-275, 2012. ,
DOI : 10.1016/j.ultrasmedbio.2011.10.022
Automatic contouring for breast tumors in 2-D sonography, Engineering in Medicine and Biology Society, pp.3225-3228, 2005. ,
A robust graph-based segmentation method for breast tumors in ultrasound images, Ultrasonics, vol.52, issue.2, pp.266-275, 2012. ,
Automated segmentation of breast lesions in ultrasound images, Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the, pp.7433-7435, 2006. ,
Object detection with discriminatively trained part-based models Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.32, issue.9, pp.1627-1645, 2010. ,
Combining CRF and Multi-hypothesis Detection for Accurate Lesion Segmentation in Breast Sonograms, Medical Image Computing and Computer-Assisted Intervention?MICCAI 2012, pp.2012-504 ,
DOI : 10.1007/978-3-642-33415-3_62
Probability density difference-based active contour for ultrasound image segmentation, Pattern Recognition, vol.43, issue.6, 2010. ,
DOI : 10.1016/j.patcog.2010.01.002
A disk expansion segmentation method for ultrasonic breast lesions, Pattern Recognition, vol.42, issue.5, 2009. ,
DOI : 10.1016/j.patcog.2008.09.004
Interactive Segmentation with Intelligent Scissors, Graphical models and image processing, pp.349-384, 1998. ,
DOI : 10.1006/gmip.1998.0480
JetStream: probabilistic contour extraction with particles, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, pp.524-531, 2001. ,
DOI : 10.1109/ICCV.2001.937670
User-Steered Image Segmentation Paradigms: Live Wire and Live Lane, Graphical Models and Image Processing, vol.60, issue.4, pp.233-260, 1998. ,
DOI : 10.1006/gmip.1998.0475
Lazy snapping, ACM Transactions on Graphics, vol.23, issue.3, pp.303-308, 2004. ,
DOI : 10.1145/1015706.1015719
"GrabCut", ACM Transactions on Graphics, vol.23, issue.3, pp.309-314, 2004. ,
DOI : 10.1145/1015706.1015720
Interactive graph cuts for optimal boundary & region segmentation of objects in ND images, Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on, pp.105-112, 2001. ,
Contour extraction from ultrasound images viewed as a tracking problem, Information Fusion, 2009. ,
Phase congruency: A low-level image invariant Simultaneous Truth and Performance Level Estimation (STAPLE): an algorithm for the validation of image segmentation, Psychological Research IEEE Transactions on Medical Imaging, vol.64, issue.23 7, pp.136-148, 2000. ,
Image features from phase congruency, Videre: Journal of computer vision research, vol.1, issue.3, pp.1-26, 1999. ,
A discrete dynamic contour model, IEEE Transactions on Medical Imaging, vol.14, issue.1, pp.12-24, 1995. ,
DOI : 10.1109/42.370398
The watershed transformation applied to image segmentation Scanning microscopy-supplement, pp.299-299, 1992. ,
Geodesic saliency of watershed contours and hierarchical segmentation Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.18, issue.12, pp.1163-1173, 1996. ,
Normalized cuts and image segmentation Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.22, issue.8, pp.888-905, 2000. ,
Class segmentation and object localization with superpixel neighborhoods, 2009 IEEE 12th International Conference on Computer Vision, pp.670-677, 2009. ,
DOI : 10.1109/ICCV.2009.5459175
Ultrasound image segmentation and tissue characterization, Proceedings of the Institution of Mechanical Engineers, pp.307-316, 2009. ,
DOI : 10.1243/09544119JEIM604
A Review of Statistical Approaches to Level Set Segmentation: Integrating Color, Texture, Motion and Shape, International Journal of Computer Vision, vol.18, issue.9, pp.195-215, 2007. ,
DOI : 10.1007/s11263-006-8711-1
Fast approximate energy minimization via graph cuts Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.23, issue.11, pp.1222-1239, 2001. ,
Fast Approximate Energy Minimization with Label Costs, International Journal of Computer Vision, vol.18, issue.9, pp.1-27, 2012. ,
DOI : 10.1007/s11263-011-0437-z
Snakes: Active contour models, International Journal of Computer Vision, vol.5, issue.6035, pp.321-331, 1988. ,
DOI : 10.1007/BF00133570
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.124.5318
Level set methods and dynamic implicit surfaces, 2003. ,
Ultrasound image segmentation: a survey, IEEE Transactions on Medical Imaging, vol.25, issue.8, 2006. ,
DOI : 10.1109/TMI.2006.877092
URL : https://hal.archives-ouvertes.fr/hal-00338658
Comparison of Balloon Snake and GVF Snake in Segmenting Masses from Breast Ultrasound Images, 2010 Second International Conference on Computer Research and Development, pp.505-509, 2010. ,
DOI : 10.1109/ICCRD.2010.109
On active contour models and balloons, CVGIP: Image Understanding, vol.53, issue.2, pp.211-218, 1991. ,
DOI : 10.1016/1049-9660(91)90028-N
Snakes, shapes, and gradient vector flow, Image Processing IEEE Transactions on, vol.7, issue.3, pp.359-369, 1998. ,
Automated seeded lesion segmentation on digital mammograms, IEEE Transactions on Medical Imaging, vol.17, issue.4, 1998. ,
DOI : 10.1109/42.730396
Computerized diagnosis of breast lesions on ultrasound, Medical Physics, vol.3034, issue.2, 2002. ,
DOI : 10.1118/1.1429239
A fast marching level set method for monotonically advancing fronts., Proceedings of the National Academy of Sciences, vol.93, issue.4, pp.1591-1595, 1996. ,
DOI : 10.1073/pnas.93.4.1591
SLIC Superpixels Compared to State-of-the-Art Superpixel Methods, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.34, issue.11, 2012. ,
DOI : 10.1109/TPAMI.2012.120
An Effective Approach of Lesion Segmentation Within the Breast Ultrasound Image Based on the Cellular Automata Principle, Journal of Digital Imaging, vol.18, issue.2, pp.1-11, 2012. ,
DOI : 10.1007/s10278-011-9450-6
Active contours without edges [118] A Madabhushi and D Metaxas Automatic boundary extraction of ultrasonic breast lesions, Proceedings. 2002 IEEE International Symposium on, pp.601-604, 2001. ,
Segmentation of ultrasonic images using Support Vector Machines, Pattern Recognition Letters, vol.24, issue.4-5, pp.715-727, 2003. ,
DOI : 10.1016/S0167-8655(02)00177-0
Optimally discriminant moments for speckle detection in real B-scan images, Ultrasonics, vol.48, issue.3, pp.169-181, 2008. ,
DOI : 10.1016/j.ultras.2007.11.010
Discriminative Training for Object Recognition Using Image Patches, 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05), pp.157-162, 2005. ,
DOI : 10.1109/CVPR.2005.134
Representing shape with a spatial pyramid kernel, Proceedings of the 6th ACM international conference on Image and video retrieval, CIVR '07, pp.401-408, 2007. ,
DOI : 10.1145/1282280.1282340
The Pascal Visual Object Classes (VOC) Challenge, International Journal of Computer Vision, vol.73, issue.2, pp.303-338, 2010. ,
DOI : 10.1007/s11263-009-0275-4
The Pascal Visual Object Classes (VOC) Challenge, International Journal of Computer Vision, vol.73, issue.2, 2006. ,
DOI : 10.1007/s11263-009-0275-4
Beyond sliding windows: Object localization by efficient subwindow search, 2008 IEEE Conference on Computer Vision and Pattern Recognition, pp.1-8, 2008. ,
DOI : 10.1109/CVPR.2008.4587586
URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.149.4517
Watersheds in digital spaces: an efficient algorithm based on immersion simulations, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.13, issue.6, pp.583-598, 1991. ,
DOI : 10.1109/34.87344
Efficient Graph-Based Image Segmentation, International Journal of Computer Vision, vol.59, issue.2, pp.167-181, 2004. ,
DOI : 10.1023/B:VISI.0000022288.19776.77
Superpixels and Supervoxels in an Energy Optimization Framework, Computer Vision?ECCV 2010, pp.211-224, 2010. ,
DOI : 10.1007/978-3-642-15555-0_16
Turbopixels: Fast superpixels using geometric flows Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.31, issue.12, pp.2290-2297, 2009. ,
Quick Shift and Kernel Methods for Mode Seeking, Computer Vision?ECCV, pp.705-718, 2008. ,
DOI : 10.1007/978-3-540-88693-8_52
Mean shift: A robust approach toward feature space analysis Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.24, issue.5, pp.603-619, 2002. ,
Contour detection and hierarchical image segmentation Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol.33, issue.5, pp.898-916, 2011. ,
The Quadratic-Chi Histogram Distance Family, Computer Vision?ECCV 2010, pp.749-762, 2010. ,
DOI : 10.1007/978-3-642-15552-9_54
Applied statistics: a handbook of techniques, 1984. ,
Computer vision: a modern approach, Computer, vol.16, p.11, 2011. ,
URL : https://hal.archives-ouvertes.fr/hal-01063327
Local Features and Kernels for Classification of Texture and Object Categories: A Comprehensive Study, International Journal of Computer Vision, vol.36, issue.1, pp.213-238, 2007. ,
DOI : 10.1007/s11263-006-9794-4
URL : https://hal.archives-ouvertes.fr/inria-00548574
Beyond Bags of Features: Spatial Pyramid Matching for Recognizing Natural Scene Categories, 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, Volume 2 (CVPR'06), pp.2169-2178, 2006. ,
DOI : 10.1109/CVPR.2006.68
URL : https://hal.archives-ouvertes.fr/inria-00548585
Distinctive Image Features from Scale-Invariant Keypoints, International Journal of Computer Vision, vol.60, issue.2, pp.91-110, 2004. ,
DOI : 10.1023/B:VISI.0000029664.99615.94
Complex cells and object recognition Machine learning: a probabilistic perspective, 1997. ,
Visual categorization with bags of keypoints, Workshop on statistical learning in computer vision, ECCV, p.22, 2004. ,
Multiresolution image processing and analysis, 1984. ,
DOI : 10.1007/978-3-642-51590-3
Detection of breast lesion regions in ultrasound images using wavelets and order statistics, Medical Physics, vol.22, issue.4, p.840, 2006. ,
DOI : 10.1109/TMI.2002.808364
Diagnosis of breast tumors with sonographic texture analysis using wavelet transform and neural networks, Ultrasound in Medicine & Biology, vol.28, issue.10, pp.1301-1310, 2002. ,
DOI : 10.1016/S0301-5629(02)00620-8
LIBSVM, ACM Transactions on Intelligent Systems and Technology, vol.2, issue.3, pp.1-27, 2011. ,
DOI : 10.1145/1961189.1961199
Markov random field modeling in image analysis, 2009. ,
DOI : 10.1007/978-4-431-67044-5
A Comparative Study of Energy Minimization Methods for Markov Random Fields with Smoothness-Based Priors, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.30, issue.6, pp.1068-1080, 2008. ,
DOI : 10.1109/TPAMI.2007.70844
Metaheuristics in Combinatorial Optimization, Annals of Operations Research, vol.1, issue.1, pp.189-213, 2005. ,
DOI : 10.1007/s10479-005-3971-7
Statistical analysis of dirty pictures*, Journal of Applied Statistics, vol.6, issue.5-6, pp.259-302, 1986. ,
DOI : 10.1016/0031-3203(83)90012-2
Optimization by Simulated Annealing, Science, vol.220, issue.4598, pp.671-680, 1983. ,
DOI : 10.1126/science.220.4598.671
Greedy Randomized Adaptive Search Procedures, Journal of Global Optimization, vol.68, issue.2, pp.109-133, 1995. ,
DOI : 10.1007/BF01096763
Simulated annealing, Search methodologies, pp.187-210, 2005. ,
Parallel simulated annealing for the vehicle routing problem with time windows, Proceedings 10th Euromicro Workshop on Parallel, Distributed and Network-based Processing, pp.376-383, 2002. ,
DOI : 10.1109/EMPDP.2002.994313
Computerized detection and classification of cancer on breast ultrasound1, Academic Radiology, vol.11, issue.5, p.526, 2004. ,
DOI : 10.1016/S1076-6332(03)00723-2
Kernel Codebooks for Scene Categorization, Computer Vision?ECCV, pp.696-709, 2008. ,
DOI : 10.1007/978-3-540-88690-7_52
Image classification based on bag of visual graphs, 2013 IEEE International Conference on Image Processing, 2013. ,
DOI : 10.1109/ICIP.2013.6738888
URL : https://hal.archives-ouvertes.fr/hal-00939183