21.12.4 Ultrasound, Ultrasonic, Image Segmentation, Contour Extraction, Contour Motion

Chen, H., Wu, L., Dou, Q., Qin, J., Li, S., Cheng, J.Z., Ni, D., Heng, P.A.,
Ultrasound Standard Plane Detection Using a Composite Neural Network Framework,
Cyber(47), No. 6, June 2017, pp. 1576-1586.
IEEE DOI 1706
Biomedical imaging, Feature extraction, Fetus, Machine learning, Standards, Training data, Videos, Convolutional neural network (CNN), deep learning, knowledge transfer, recurrent neural network (RNN), standard plane, ultrasound, (US) BibRef

Pourtaherian, A., Scholten, H.J., Kusters, L., Zinger, S., Mihajlovic, N., Kolen, A.F., Zuo, F., Ng, G.C., Korsten, H.H.M., de With, P.H.N.,
Medical Instrument Detection in 3-Dimensional Ultrasound Data Volumes,
MedImg(36), No. 8, August 2017, pp. 1664-1675.
IEEE DOI 1708
BibRef
Earlier: A1, A4, A10, A9, A5, Only:
Gabor-based needle detection and tracking in three-dimensional ultrasound data volumes,
ICIP14(3602-3606)
IEEE DOI 1502
Needles, Robustness, Transducers, Ultrasonic imaging, 3D ultrasound, Gabor transformation, Medical instrument detection, interventional guidance, line filtering. BibRef

Bi, H.[Hui], Tang, H.[Hui], Yang, G.Y.[Guan-Yu], Li, B.S.[Bao-Sheng], Shu, H.Z.[Hua-Zhong], Dillenseger, J.L.[Jean-Louis],
Fast segmentation of ultrasound images by incorporating spatial information into Rayleigh mixture model,
IET-IPR(11), No. 12, Decmeber 2017, pp. 1188-1196.
DOI Link 1712
BibRef

Bi, H.[Hui], Jiang, Y.B.[Yi-Bo], Li, H.[Hui], Sha, X.[Xuan], Wang, Y.[Yi],
Active Contours Driven by Local Rayleigh Distribution Fitting Energy for Ultrasound Image Segmentation,
IEICE(E101-D), No. 7, July 2018, pp. 1933-1937.
WWW Link. 1807
BibRef

Santos, C.A.N., Mascarenhas, N.D.A.,
Geodesic Distances in Probabilistic Spaces for Patch-Based Ultrasound Image Processing,
IP(28), No. 1, January 2019, pp. 216-226.
IEEE DOI 1810
biomedical ultrasonics, Gaussian noise, image denoising, image filtering, image reconstruction, image segmentation, Fisher-Tippett noise BibRef

Diamantis, K., Anderson, T., Butler, M.B., Villagómez-Hoyos, C.A., Jensen, J.A., Sboros, V.,
Resolving Ultrasound Contrast Microbubbles Using Minimum Variance Beamforming,
MedImg(38), No. 1, January 2019, pp. 194-204.
IEEE DOI 1901
Image resolution, Imaging, Electron tubes, Ultrasonic imaging, Transducers, Array signal processing, Signal resolution, super-resolution ultrasound BibRef

Yang, X., Yu, L., Li, S., Wen, H., Luo, D., Bian, C., Qin, J., Ni, D., Heng, P.,
Towards Automated Semantic Segmentation in Prenatal Volumetric Ultrasound,
MedImg(38), No. 1, January 2019, pp. 180-193.
IEEE DOI 1901
Ultrasonic imaging, Fetus, Semantics, Image segmentation, Shape, Labeling, Prenatal examination, recurrent neural networks BibRef

Karami, E., Shehata, M.S., Smith, A.,
Adaptive Polar Active Contour for Segmentation and Tracking in Ultrasound Videos,
CirSysVideo(29), No. 4, April 2019, pp. 1209-1222.
IEEE DOI 1904
Image segmentation, Ultrasonic imaging, Shape, Active contours, Blood, Videos, Image quality, Circulating blood volume, active contours BibRef

Shao, D.G.[Dang-Guo], Xu, C.R.[Chun-Rong], Xiang, Y.[Yan], Gui, P.[Peng], Zhu, X.F.[Xiao-Fang], Zhang, C.[Chao], Yu, Z.T.[Zheng-Tao],
Ultrasound image segmentation with multilevel threshold based on differential search algorithm,
IET-IPR(13), No. 6, 10 May 2019, pp. 998-1005.
DOI Link 1906
BibRef

Liu, Z.[Zhong], Chan, S.C.[Shing-Chow], Zhang, S.[Shuai], Zhang, Z.G.[Zhi-Guo], Chen, X.[Xin],
Automatic Muscle Fiber Orientation Tracking in Ultrasound Images Using a New Adaptive Fading Bayesian Kalman Smoother,
IP(28), No. 8, August 2019, pp. 3714-3727.
IEEE DOI 1907
Bayes methods, biomedical ultrasonics, Gabor filters, Gaussian processes, Hough transforms, image enhancement, adaptive fading BibRef

Zhang, S.[Shuai], Zhang, Z.G.[Zhi-Guo], Chan, S.C., Wen, H.Y.[Hui-Ying], Chen, X.[Xin],
An automatic muscle fiber orientation tracking algorithm using Bayesian Kalman Filter for ultrasound images,
ICIP15(3510-3514)
IEEE DOI 1512
Bayesian Kalman filter BibRef

Heiles, B., Correia, M., Hingot, V., Pernot, M., Provost, J., Tanter, M., Couture, O.,
Ultrafast 3D Ultrasound Localization Microscopy Using a 32X32 Matrix Array,
MedImg(38), No. 9, September 2019, pp. 2005-2015.
IEEE DOI 1909
Ultrasonic imaging, Image resolution, Microscopy, Probes, Irrigation, Ultrasound, microbubbles ULM, 4D BibRef

Nguyen, K.L.[Khac L.], Tekitek, M.M.[Mohamed M.], Delachartre, P.[Philippe], Berthier, M.[Michel],
Multiple Relaxation Time Lattice Boltzmann Models for Multigrid Phase-Field Segmentation of Tumors in 3D Ultrasound Images,
SIIMS(12), No. 3, 2019, pp. 1324-1346.
DOI Link 1911
BibRef

Zhang, Z.M.[Zhuo-Min], Davaasuren, D.[Dolzodmaa], Wu, C.Y.[Chen-Yan], Goldstein, J.A.[Jeffery A.], Gernand, A.D.[Alison D.], Wang, J.Z.[James Z.],
Multi-region saliency-aware learning for cross-domain placenta image segmentation,
PRL(140), 2020, pp. 165-171.
Elsevier DOI 2012
Transfer learning, Placenta, Photo image analysis, Pathology BibRef

Ouahabi, A.[Abdeldjalil], Taleb-Ahmed, A.[Abdelmalik],
Retraction: Deep learning for real-time semantic segmentation: Application in ultrasound imaging,
PRL(159), 2022, pp. 222.
Elsevier DOI 2206
BibRef
And: PRL(144), 2021, pp. 27-34.
Elsevier DOI 2103
BibRef

Yang, X.[Xin], Dou, H.R.[Hao-Ran], Huang, R.B.[Ruo-Bing], Xue, W.F.[Wu-Feng], Huang, Y.H.[Yu-Hao], Qian, J.[Jikuan], Zhang, Y.J.[Yuan-Ji], Luo, H.[Huanjia], Guo, H.Z.[Hui-Zhi], Wang, T.F.[Tian-Fu], Xiong, Y.[Yi], Ni, D.[Dong],
Agent With Warm Start and Adaptive Dynamic Termination for Plane Localization in 3D Ultrasound,
MedImg(40), No. 7, July 2021, pp. 1950-1961.
IEEE DOI 2107
Location awareness, Ultrasonic imaging, Standards, dynamic termination BibRef

Chanti, D.A.[Dawood Al], Duque, V.G.[Vanessa Gonzalez], Crouzier, M.[Marion], Nordez, A.[Antoine], Lacourpaille, L.[Lilian], Mateus, D.[Diana],
IFSS-Net: Interactive Few-Shot Siamese Network for Faster Muscle Segmentation and Propagation in Volumetric Ultrasound,
MedImg(40), No. 10, October 2021, pp. 2615-2628.
IEEE DOI 2110
Muscles, Image segmentation, Ultrasonic imaging, Annotations, Task analysis, segmentation BibRef

Kim, K.B.[Kwang Baek], Song, D.H.[Doo Heon], Park, H.J.[Hyun Jun],
Cooperative pixel clustering for accurate automatic inflamed appendix extraction from ultrasound images,
IJCVR(11), No. 6, 2021, pp. 640-652.
DOI Link 2111
BibRef

Xu, J.Y.[Jing-Yuan], Xie, H.T.[Hong-Tao], Liu, C.B.[Chuan-Bin], Yang, F.[Fang], Zhang, S.C.[Si-Cheng], Chen, X.[Xun], Zhang, Y.D.[Yong-Dong],
Hip Landmark Detection With Dependency Mining in Ultrasound Image,
MedImg(40), No. 12, December 2021, pp. 3762-3774.
IEEE DOI 2112
Hip, Ultrasonic imaging, Feature extraction, Heating systems, Pediatrics, Measurement, Attenuation, dependency mining BibRef

Khan, S.[Shujaat], Huh, J.[Jaeyoung], Ye, J.C.[Jong Chul],
Switchable and Tunable Deep Beamformer Using Adaptive Instance Normalization for Medical Ultrasound,
MedImg(41), No. 2, February 2022, pp. 266-278.
IEEE DOI 2202
Codes, Switches, Ultrasonic imaging, Noise reduction, Training, Speckle, Generators, Deep beamformer, adaptive beamformer BibRef

Srivastava, S.[Somya], Vidyarthi, A.[Ankit], Jain, S.[Shikha],
A regressive encoder-decoder-based deep attention model for segmentation of fetal head in 2D-ultrasound images,
IVC(136), 2023, pp. 104725.
Elsevier DOI 2308
Ultrasound imaging, Deep learning, Fetus head segmentation, Head circumference assessment, Regression-attention model BibRef

Huang, X.P.[Xu-Ping], Wang, Q.[Qian], Chen, J.X.[Jun-Xi], Chen, L.[Lingna], Chen, Z.Y.[Zhi-Yi],
Effective hybrid attention network based on pseudo-color enhancement in ultrasound image segmentation,
IVC(137), 2023, pp. 104742.
Elsevier DOI 2309
Ultrasound image, UNet, Attention, Pseudo-color enhancement, CNNs BibRef

Chen, F.[Fang], Chen, L.[Lingyu], Kong, W.T.[Wen-Tao], Zhang, W.J.[Wei-Jing], Zheng, P.F.[Peng-Fei], Sun, L.[Liang], Zhang, D.Q.[Dao-Qiang], Liao, H.[Hongen],
Deep Semi-Supervised Ultrasound Image Segmentation by Using a Shadow Aware Network With Boundary Refinement,
MedImg(42), No. 12, December 2023, pp. 3779-3793.
IEEE DOI 2312
BibRef

Zhai, J.T.[Jin-Tao], Tian, F.[Feng], Li, A.[Ang], Qian, S.[Shengyou], Wang, R.[Runmin], Zou, X.[Xiao],
A target region extraction method for ultrasound medical images based on improved PRIDNet and UCTransNet,
IJIST(34), No. 2, 2024, pp. e23035.
DOI Link Code:
WWW Link. 2402
enhancement network, segmentation network, target region extraction, ultrasound medical images BibRef

Ling, Y.T.[Ya-Ting], Wang, Y.L.[Yu-Ling], Dai, W.L.[Wen-Li], Yu, J.[Jie], Liang, P.[Ping], Kong, D.[Dexing],
MTANet: Multi-Task Attention Network for Automatic Medical Image Segmentation and Classification,
MedImg(43), No. 2, February 2024, pp. 674-685.
IEEE DOI 2402
Medical diagnostic imaging, Image segmentation, Ultrasonic imaging, Task analysis, Transformers, one-stage BibRef

Wijata, A.M.[Agata M.], Nalepa, J.[Jakub],
Machine Learning Detects a Biopsy Needle in Ultrasound Images,
ICIP23(3548-3552)
IEEE DOI 2312
BibRef

Qi, H., Collins, S., Noble, J.A.,
UPI-Net: Semantic Contour Detection in Placental Ultrasound,
VRMI19(416-424)
IEEE DOI 2004
Semantics, Image edge detection, Ultrasonic imaging, Context modeling, Convolution, Geometry, Detectors, placenta BibRef

Nahas, H.[Hassan], Ishii, T.[Takuro], Chee, A.[Adrian], Yiu, B.[Billy], Yu, A.[Alfred],
Segmentation of Aliasing Artefacts in Ultrasound Color Flow Imaging Using Convolutional Neural Networks,
ICIAR19(II:452-461).
Springer DOI 1909
BibRef

Sciortino, G.[Giuseppa], Tegolo, D.[Domenico], Valenti, C.[Cesare],
Morphological Analysis Combined with a Machine Learning Approach to Detect Utrasound Median Sagittal Sections for the Nuchal Translucency Measurement,
MCPR17(257-267).
Springer DOI 1706
BibRef

Wang, S.Y.[Shuang-Yi], Singh, D.[Davinder], Lau, D.[David], Reddy, K.[Kiran], Althoefer, K.[Kaspar], Rhode, K.[Kawal], Housden, R.J.[Richard J.],
Probe Tracking and Its Application in Automatic Acquisition Using a Trans-Esophageal Ultrasound Robot,
CARE16(14-23).
Springer DOI 1703
BibRef

Vasconcelos, F.[Francisco], Peebles, D.[Donald], Ourselin, S.[Sebastien], Stoyanov, D.[Danail],
Similarity Registration Problems for 2D/3D Ultrasound Calibration,
ECCV16(VI: 171-187).
Springer DOI 1611
BibRef

Milletari, F.[Fausto], Navab, N.[Nassir], Ahmadi, S.A.[Seyed-Ahmad],
V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation,
3DV16(565-571)
IEEE DOI 1701
biomedical MRI BibRef

Kroll, C.[Christine], Milletari, F.[Fausto], Navab, N.[Nassir], Ahmadi, S.A.[Seyed-Ahmad],
Coupling Convolutional Neural Networks and Hough Voting for Robust Segmentation of Ultrasound Volumes,
GCPR16(439-450).
Springer DOI 1611
BibRef

Wang, W.N.[Wei-Ning], Li, J.C.[Jia-Chang], Jiang, Y.Z.[Yi-Zi], Xing, Y.[Yi], Xu, X.M.[Xiang-Min],
An automatic energy-based region growing method for ultrasound image segmentation,
ICIP15(1553-1557)
IEEE DOI 1512
energy function BibRef

González, J.G.[Julián Gil], Álvarez, M.A.[Mauricio A.], Orozco, Á.A.[Álvaro A.],
Peripheral Nerves Segmentation in Ultrasound Images Using Non-linear Wavelets and Gaussian Processes,
IbPRIA15(603-611).
Springer DOI 1506
BibRef

Wang, L.[Liang], Girard, P.R., Bernard, A., Liu, Z.J.[Zheng-Jun], Clarysse, P., Delachartre, P.,
3-D biquaternionic analytic signal and application to envelope detection in 3-D ultrasound imaging,
IC3D12(1-8)
IEEE DOI 1503
Fourier transforms BibRef

Maraci, M.A.[Mohammad Ali], Napolitano, R.[Raffaele], Papageorghiou, A.[Aris], Noble, J.A.[J. Allison],
Object Classification in an Ultrasound Video Using LP-SIFT Features,
MCV14(71-81).
Springer DOI 1501
BibRef
And:
Searching for Structures of Interest in an Ultrasound Video Sequence,
MLMI14(133-140).
Springer DOI 1410
BibRef

Kulbacki, M.[Marek], Segen, J.[Jakub], Habela, P.[Piotr], Janiak, M.[Mateusz], Kniec, W.[Wojciech], Fojcik, M.[Marcin], Mielnik, P.[Pawel], Wojciechowski, K.[Konrad],
Collaborative Tool for Annotation of Synovitis and Assessment in Ultrasound Images,
ICCVG14(364-373).
Springer DOI 1410
BibRef

Sagar, J.V.R., Bhagvati, C.,
Stochastic resonance aided robust techniques for segmentation of medical ultrasound images,
NCVPRIPG13(1-5)
IEEE DOI 1408
biomedical ultrasonics BibRef

Xu, R.[Rong], Ohya, J.[Jun], Zhang, B.[Bo], Fujie, M.G., Sato, Y.,
Automatic fetal face detection by locating fetal facial features from 3D ultrasound images for navigating fetoscopic tracheal occlusion surgeries,
FG13(1-6)
IEEE DOI 1309
Gaussian processes BibRef

Faucheux, C.[Cyrille], Olivier, J.[Julien], Bone, R.[Romuald], Makris, P.[Pascal],
Texture-based graph regularization process for 2D and 3D ultrasound image segmentation,
ICIP12(2333-2336).
IEEE DOI 1302

See also Graph-Based Regularization of Binary Classifiers for Texture Segmentation. BibRef

Boukerroui, D.[Djamal],
Optimal spatial scale for local region-based active contours,
ICIP14(4393-4397)
IEEE DOI 1502
BibRef
Earlier:
A local Rayleigh model with spatial scale selection for ultrasound image segmentation,
BMVC12(84).
DOI Link 1301
Active contours BibRef

Ciecholewski, M.[Marcin],
Gallbladder Segmentation from 2-D Ultrasound Images Using Active Contour Models and Gradient Vector Flow,
MIRAGE11(86-97).
Springer DOI 1110
BibRef

Talebi, M.[Mohammad], Ayatollahi, A.[Ahmad],
Genetic Snake for Medical Ultrasound Image Segmentation,
ICIAR11(II: 48-58).
Springer DOI 1106
BibRef

Banerjee, J.[Jyotirmoy], Krishnan, K.B.[Kajoli B.],
Model-Based Detection of Acoustically Dense Objects in Ultrasound,
ICPR10(4166-4169).
IEEE DOI 1008
BibRef

Jourdain, M.[Melissa], Meunier, J.[Jean], Sequeira, J.[Jean], Cloutier, G.[Guy], Tardif, J.C.[Jean-Claude],
Intravascular Ultrasound image segmentation: A helical active contour method,
IPTA10(92-97).
IEEE DOI 1007
BibRef

Dong, B.[Bin], Savitsky, E.[Eric], Osher, S.J.[Stanley J.],
A Novel Method for Enhanced Needle Localization Using Ultrasound-Guidance,
ISVC09(I: 914-923).
Springer DOI 0911
BibRef

Zouqi, M., Samarabandu, J.,
2D ultrasound image segmentation using graph cuts and local image features,
CIIP09(33-40).
IEEE DOI 0903
BibRef

Mendizabal-Ruiz, G.[Gerardo], Rivera, M.[Mariano], Kakadiaris, I.A.[Ioannis A.],
A probabilistic segmentation method for the identification of luminal borders in intravascular ultrasound images,
CVPR08(1-8).
IEEE DOI 0806
BibRef

Alexandrescu, I.[Ionut], Cheriet, F.[Farida], Delorme, S.[Sébastien],
A Novel 3D Segmentation Method of the Lumen from Intravascular Ultrasound Images,
ICIAR07(949-960).
Springer DOI 0708
BibRef

Hamou, A.K.[Ali K.], Osman, S.[Said], El-Sakka, M.R.[Mahmoud R.],
Carotid Ultrasound Segmentation Using DP Active Contours,
ICIAR07(961-971).
Springer DOI 0708
BibRef

Nam, T.J.[Tae-Jin], Park, R.H.[Rae-Hong], Yun, J.H.[Jae-Ho],
Optical Flow Based Frame Interpolation of Ultrasound Images,
ICIAR06(I: 792-803).
Springer DOI 0610
BibRef

Saad, A.A.[Ashraf A.], Shapiro, L.G.[Linda G.],
Shape Decomposition Approach for Ultrasound Color Doppler Image Segmentation,
ICPR06(IV: 691-694).
IEEE DOI 0609
BibRef

Arbelaez, P.[Pablo],
Boundary Extraction in Natural Images Using Ultrametric Contour Maps,
PercOrg06(182).
IEEE DOI 0609
BibRef

Yap, M.H.[Moi Hoon], Edirisinghe, E.A., Bez, H.E.[Helmut E.],
Object Boundary Detection in Ultrasound Images,
CRV06(53-53).
IEEE DOI 0607
BibRef

Slabaugh, G.G.[Gregory G.], Unal, G.[Gozde], Fang, T.[Tong], Wels, M.[Michael],
Ultrasound-Specific Segmentation via Decorrelation and Statistical Region-Based Active Contours,
CVPR06(I: 45-53).
IEEE DOI 0606
BibRef

Kissi, A., Cormier, S., Pourcelot, L., Tranquart, F.,
Automatic Lesions Segmentation in Ultrasound Nonlinear Imaging,
ICIP05(I: 1153-1156).
IEEE DOI 0512
BibRef

Kies, P.[Pawel],
Application of Wavelet Transforms and Bayes Classifier to Segmentation of Ultrasound Images,
IbPRIA05(II:336).
Springer DOI 0509
BibRef

Jiang, Y.F.[Yi-Feng], Zhang, Z.J.[Zhi-Jun], Cen, F.[Feng], Tsui, H.T.[Hung Tat], Lau, T.K.[Tze Kin],
An enhanced appearance model for ultrasound image segmentation,
ICPR04(III: 802-805).
IEEE DOI 0409
BibRef

Cancela, P., Reyes, F., Rodriguez, P., Randall, G., Fernandez, A.,
Automatic object detection using shape information in ultrasound images,
ICIP03(III: 417-420).
IEEE DOI 0312
BibRef

Jardim, S.V.B.,
Automatic contour estimation in fetal ultrasound images,
ICIP03(II: 1065-1068).
IEEE DOI 0312
BibRef

Ruisz, J., Honigmann, D., Pottmann, H.,
Segmentation and modeling of approximately rotationally symmetric objects in 3D ultrasound,
3DIM03(124-131).
IEEE DOI 0311
BibRef

Hiransakolwong, N., Windyga, P.S., Hua, K.A., Vu, K.[Khanh],
FASU: A full automatic segmenting system for ultrasound images,
WACV02(90-94).
IEEE DOI 0303
BibRef

Srinark, T.[Thitiwan], Kambhamettu, C.[Chandra], Stone, M.[Maureen],
A Hierarchical Method for 3D Rigid Motion Estimation,
ACCV06(II:791-800).
Springer DOI 0601
Given 3-D mesh representations. BibRef

Karoubi, B., Zhu, Y.M., Gimenez, G., Bigiln, J.,
Detection of objects in RF ultrasonic images using 2-D spatial phase techniques,
ICIP96(II: 641-644).
IEEE DOI 9610
BibRef

Cohen, F.S., Georgiou, G.,
Detecting and estimating structure regularity of soft tissue organs from ultrasound images,
ICIP95(II: 488-491).
IEEE DOI 9510
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Elastography Analysis .

Last update:Sep 28, 2024 at 17:47:54