20.7.3.6 Medical Applications, Knee Joints

Chapter Contents (Back)
Knee Joints. Skeletal.

Ausherman, D.A., Dwyer, III, S.J., Lodwick, G.S.,
Extraction of Connected Edges from Knee Radiographs,
TC(21), No. 7, July 1972, pp. 753-758. BibRef 7207

Stindel, E., Udupa, J.K., Hirsch, B.E., Odhner, D.,
A characterization of the geometric architecture of the peritalar joint complex via MRI, an aid to classification of foot type,
MedImg(18), No. 9, September 1999, pp. 753-763.
IEEE Top Reference. 0110
BibRef

Mahfouz, M.R., Hoff, W.A., Komistek, R.D., Dennis, D.A.,
A robust method for registration of three-dimensional knee implant models to two-dimensional fluoroscopy images,
MedImg(22), No. 12, December 2003, pp. 1561-1574.
IEEE Abstract. 0401
BibRef

Yamazaki, T., Watanabe, T., Nakajima, Y., Sugamoto, K., Tomita, T., Yoshikawa, H., Tamura, S.,
Improvement of depth position in 2-D/3-D registration of knee implants using single-plane fluoroscopy,
MedImg(23), No. 5, May 2004, pp. 602-612.
IEEE Abstract. 0406
BibRef

Folkesson, J.[Jenny], Dam, E.B.[Erik B.], Olsen, O.F.[Ole Fogh], Pettersen, P.[Paola], Christiansen, C.[Claus],
Segmenting Articular Cartilage Automatically Using a Voxel Classification Approach,
MedImg(26), No. 1, January 2007, pp. 106-115.
IEEE DOI 0701
BibRef
Earlier: A1, A3, A4, A2, A5:
Combining Binary Classifiers for Automatic Cartilage Segmentation in Knee MRI,
CVBIA05(230-239).
Springer DOI 0601
BibRef

Ramakrishna, B., Liu, W.M.[Wei-Min], Saiprasad, G., Safdar, N., Chang, C.I.[Chein-I], Siddiqui, K., Kim, W., Siegel, E., Chai, J.W.[Jyh-Wen], Chen, C.C.C., Lee, S.K.[San-Kan],
An Automatic Computer-Aided Detection System for Meniscal Tears on Magnetic Resonance Images,
MedImg(28), No. 8, August 2009, pp. 1308-1316.
IEEE DOI 0909
BibRef

Atmani, H.[Hakim], Mérienne, F.[Frédéric], Fofi, D.[David],
From medical data to simple virtual mock-up of scapulo-humeral joint,
ELCVIA(7), No. 3, 2008, pp. xx-yy.
WWW Link. 0909
BibRef

Fripp, J.[Jurgen], Crozier, S.[Stuart], Warfield, S.K.[Simon K.], Ourselin, S.[Sebastien],
Automatic Segmentation and Quantitative Analysis of the Articular Cartilages From Magnetic Resonance Images of the Knee,
MedImg(29), No. 1, January 2010, pp. 55-64.
IEEE DOI 1001
BibRef
Earlier: A1, A3, A2, A4:
Automatic Segmentation of the Knee Bones using 3D Active Shape Models,
ICPR06(I: 167-170).
IEEE DOI 0609
BibRef

Fripp, J.[Jurgen], Bourgeat, P.[Pierrick], Mewes, A.J.U.[Andrea J.U.], Warfield, S.K.[Simon K.], Crozier, S.[Stuart], Ourselin, S.[Sébastien],
3D Statistical Shape Models to Embed Spatial Relationship Information,
CVBIA05(51-60).
Springer DOI 0601
Shape model of knee to embed info in MRI data. BibRef

Williams, T.G., Holmes, A.P., Waterton, J.C., Maciewicz, R.A., Hutchinson, C.E., Moots, R.J., Nash, A.F.P., Taylor, C.J.,
Anatomically Corresponded Regional Analysis of Cartilage in Asymptomatic and Osteoarthritic Knees by Statistical Shape Modelling of the Bone,
MedImg(29), No. 8, August 2010, pp. 1541-1559.
IEEE DOI 1008
BibRef

Yin, Y.[Yin], Zhang, X.M.[Xiang-Min], Williams, R., Wu, X.D.[Xiao-Dong], Anderson, D.D., Sonka, M.,
LOGISMOS: Layered Optimal Graph Image Segmentation of Multiple Objects and Surfaces: Cartilage Segmentation in the Knee Joint,
MedImg(29), No. 12, December 2010, pp. 2023-2037.
IEEE DOI 1101
BibRef

Chen, B.L.[Bai-Liang], Lambrou, T.[Tryphon], Offiah, A.[Amaka], Fry, M.[Martin], Todd-Pokropek, A.[Andrew],
Combined MR imaging towards subject-specific knee contact analysis,
VC(27), No. 2, February 2011, pp. 121-128.
WWW Link. 1103
BibRef

Hockett, F.D., Wallace, K.D., Schmieder, A.H., Caruthers, S.D., Pham, C.T.N., Wickline, S.A., Lanza, G.M.,
Simultaneous Dual Frequency ^1-H and ^19-F Open Coil Imaging of Arthritic Rabbit Knee at 3T,
MedImg(30), No. 1, January 2011, pp. 22-27.
IEEE DOI 1101
MRI Imaging. BibRef

Lee, S.[Soochahn], Park, S.H.[Sang Hyun], Shim, H.J.[Hack-Joon], Yun, I.D.[Il Dong], Lee, S.U.[Sang Uk],
Optimization of local shape and appearance probabilities for segmentation of knee cartilage in 3-D MR images,
CVIU(115), No. 12, December 2011, pp. 1710-1720.
Elsevier DOI 1111
Segmentation; Medical image analysis; MRF optimization; Local shape and appearance; Knee cartilage; Localized probabilities; Shape and appearance priors BibRef

Park, S.H.[Sang Hyun], Lee, S.[Soochahn], Yun, I.D.[Il Dong], Lee, S.U.[Sang Uk],
Hierarchical MRF of globally consistent localized classifiers for 3D medical image segmentation,
PR(46), No. 9, September 2013, pp. 2408-2419.
Elsevier DOI 1305
Segmentation; Hierarchical Markov random field; Medical image analysis; Discrete optimization; Local and global prior BibRef

Zhan, Y., Dewan, M., Harder, M., Krishnan, A., Zhou, X.S.,
Robust Automatic Knee MR Slice Positioning Through Redundant and Hierarchical Anatomy Detection,
MedImg(30), No. 12, December 2011, pp. 2087-2100.
IEEE DOI 1112
BibRef

Harvey, A.K., Thompson, M.S., Cochlin, L.E., Raju, P.A., Cui, Z., Cornell, H.R., Hulley, P.A., Brady, M.,
Functional Imaging of Tendon,
BMVA(2009), No. 8, 2009, pp. 1-10.
PDF File. 1209
BibRef

Zhang, K.L.[Kun-Lei], Lu, W.M.[Wen-Miao], Marziliano, P.[Pina],
The unified extreme learning machines and discriminative random fields for automatic knee cartilage and meniscus segmentation from multi-contrast MR images,
MVA(24), No. 7, October 2013, pp. 1459-1472.
WWW Link. 1309
BibRef

Zhang, K.L.[Kun-Lei], Deng, J.[Jun], Lu, W.M.[Wen-Miao],
Segmenting human knee cartilage automatically from multi-contrast MR images using support vector machines and discriminative random fields,
ICIP11(721-724).
IEEE DOI 1201
BibRef
Earlier: A1, A3, Only:
Automatic Human Knee Cartilage Segmentation from Multi-contrast MR Images Using Extreme Learning Machines and Discriminative Random Fields,
MLMI11(335-343).
Springer DOI 1109
BibRef

Choi, H.F.[Hon Fai], Chincisan, A.[Andra], Becker, M.[Matthias], Magnenat-Thalmann, N.[Nadia],
Multimodal composition of the digital patient: a strategy for the knee articulation,
VC(30), No. 6-8, June 2014, pp. 739-749.
Springer DOI 1407
BibRef

Huang, C., Shan, L., Charles, H.C., Wirth, W., Niethammer, M., Zhu, H.,
Diseased Region Detection of Longitudinal Knee Magnetic Resonance Imaging Data,
MedImg(34), No. 9, September 2015, pp. 1914-1927.
IEEE DOI 1509
Bones BibRef

Turunen, M.J., Toyras, J., Kokkonen, H.T., Jurvelin, J.S.,
Quantitative Evaluation of Knee Subchondral Bone Mineral Density Using Cone Beam Computed Tomography,
MedImg(34), No. 10, October 2015, pp. 2186-2190.
IEEE DOI 1511
bone BibRef

Zheng, J.J.[Jing-Jie], Ji, Z.Y.[Zhen-Yan], Yu, K.D.[Kuang-Di], An, Q.[Qin], Guo, Z.M.[Zhi-Ming], Wu, Z.[Zuyi],
A feature-based solution for 3D registration of CT and MRI images of human knee,
SIViP(9), No. 8, November 2015, pp. 1815-1824.
Springer DOI 1511
BibRef

Faisal, A., Ng, S.C.[Siew-Cheok], Goh, S.L.[Siew-Li], George, J., Supriyanto, E., Lai, K.W.,
Multiple LREK Active Contours for Knee Meniscus Ultrasound Image Segmentation,
MedImg(34), No. 10, October 2015, pp. 2162-2171.
IEEE DOI 1511
biomedical ultrasonics BibRef

Constantinescu, M.A.M., Lee, S.L., Navkar, N.V., Yu, W., Al-Rawas, S., Abinahed, J., Zheng, G., Keegan, J., Al-Ansari, A., Jomaah, N., Landreau, P., Yang, G.Z.,
Constrained Statistical Modelling of Knee Flexion From Multi-Pose Magnetic Resonance Imaging,
MedImg(35), No. 7, July 2016, pp. 1686-1695.
IEEE DOI 1608
biomechanics BibRef


Tiulpin, A.[Aleksei], Thevenot, J.[Jerome], Rahtu, E.[Esa], Saarakkala, S.[Simo],
A Novel Method for Automatic Localization of Joint Area on Knee Plain Radiographs,
SCIA17(II: 290-301).
Springer DOI 1706
BibRef

Antony, J., McGuinness, K., O'Connor, N.E., Moran, K.,
Quantifying radiographic knee osteoarthritis severity using deep convolutional neural networks,
ICPR16(1195-1200)
IEEE DOI 1705
Feature extraction, Indexes, Neural networks, Osteoarthritis, Radiography, Support vector machines, Training, Convolutional neural network, KL grades, Knee osteoarthritis, classification, regression, wndchrm BibRef

Minciullo, L., Cootes, T.,
Fully automated shape analysis for detection of Osteoarthritis from lateral knee radiographs,
ICPR16(3787-3791)
IEEE DOI 1705
Bones, Diagnostic radiography, Feature extraction, Manuals, Shape, Vegetation BibRef

Mezghani, N., Dunbar, M., Ouakrim, Y., Fuentes, A., Mitiche, A., Whynot, S., Richardson, G.,
Biomechanical signal classification of surgical and non-surgical candidates for knee arthroplasty,
ISIVC16(287-290)
IEEE DOI 1704
Biomechanics BibRef

Amami, A., Azouz, Z.B., Alouane, M. .T.H.[M. Turki-Hadj],
Weakly supervised 3D reconstruction of the knee joint from MR images using a volumetric Active Appearance Model,
ICVNZ15(1-6)
IEEE DOI 1701
biomedical MRI BibRef

Thomson, J.[Jessie], O'Neill, T.[Terence], Felson, D.[David], Cootes, T.[Tim],
Detecting Osteophytes in Radiographs of the Knee to Diagnose Osteoarthritis,
MLMI16(45-52).
Springer DOI 1611
BibRef

Galván-Tejada, J.I.[Jorge I.], Galván-Tejada, C.E.[Carlos E.], Celaya-Padilla, J.M.[José M.], Delgado-Contreras, J.R.[Juan R.], Cervantes, D.[Daniel], Ortiz, M.[Manuel],
Automated Image Registration for Knee Pain Prediction in Osteoarthritis: Data from the OAI,
MCPR16(335-345).
Springer DOI 1608
BibRef

Mezlini, H., Youssef, R., Bouhadoun, H., Budyn, E., Laredo, J.D.[J. Denis], Ghalila, S.S., Chappard, C.,
High resolution volume quantification of the knee joint space based on a semi-automatic segmentation of computed tomography images,
WSSIP15(157-161)
IEEE DOI 1603
bone BibRef

Singh, V.[Vedpal], Elamvazuthi, I.[Irraivan], Jeoti, V.[Varun], George, J.[John], Swain, A.K.[Akshya Kumar], Kumar, D.[Dileep],
3D Reconstruction of CFL Ligament Based on Ultrasonographic Images,
IVIC15(503-513).
Springer DOI 1511
BibRef

Liu, Q.[Qin], Wang, Q.[Qian], Zhang, L.[Lichi], Gao, Y.Z.[Yao-Zong], Shen, D.G.[Ding-Gang],
Multi-atlas Context Forests for Knee MR Image Segmentation,
MLMI15(186-193).
Springer DOI 1511
BibRef

Kusakunniran, W.[Worapan], Dirakbussarakom, N.[Nattaporn], Prachasri, N.[Nantawat], Yangchaem, D.[Duangkamol], Vanrenterghem, J.[Jos], Robinson, M.[Mark],
Discriminating motion patterns of ACL reconstructed patients from healthy individuals,
MVA15(447-450)
IEEE DOI 1507
Force; Hip; Joints; Knee; Niobium; Principal component analysis; Training BibRef

Menon, P.G.[Prahlad G.], Muller, J.H.[Jacobus H.],
Characterization of a Novel Imaging-Based Metric of Patellofemoral Separation Using Computational Modeling,
CompIMAGE14(188-203).
Springer DOI 1407
BibRef

Galván-Tejada, J.I.[Jorge I.], Celaya-Padilla, J.M.[José M.], Galván-Tejada, C.E.[Carlos E.], Trevińo, V.[Victor], Tamez-Peńa, J.G.[José G.],
Radiological Pain Predictors in Knee Osteoarthritis, a Four Feature Selection Comparison: Data from the OAI,
MCPR14(351-360).
Springer DOI 1407
BibRef

Wang, Q.[Quan], Wu, D.[Dijia], Lu, L.[Le], Liu, M.[Meizhu], Boyer, K.L.[Kim L.], Zhou, S.H.K.[Shao-Hua Kevin],
Semantic Context Forests for Learning-Based Knee Cartilage Segmentation in 3D MR Images,
MCV13(105-115).
Springer DOI 1405
BibRef

Hossain, M.M., Muhit, A.A., Pickering, M.R., Scarvell, J., Smith, P.,
A 3D-2D Image Registration Algorithm for Kinematic Analysis of the Knee after Total Knee Arthroplasty (TKA),
DICTA13(1-6)
IEEE DOI 1402
computerised tomography BibRef

Kong, Q.[Qi], Wang, S.[Shaoshan], Yang, J.[Jiushan], Zou, R.[Ruiqi], Huang, Y.[Yan], Yin, Y.L.[Yi-Long], Peng, J.L.[Jing-Liang],
Automatic measurement on CT images for patella dislocation diagnosis,
ICIP13(1130-1134)
IEEE DOI 1402
Active contours BibRef

Lee, H.S.[Han-Sang], Hong, H.[Helen], Kim, J.[Junmo],
Anterior Cruciate Ligament Segmentation from Knee MR Images Using Graph Cuts with Geometric and Probabilistic Shape Constraints,
ACCV12(II:305-315).
Springer DOI 1304
BibRef

Jopek, L.[Lukasz], Babout, L.[Laurent], Janaszewski, M.[Marcin],
A New Method to Segment X-Ray Microtomography Images of Lamellar Titanium Alloy Based on Directional Filter Banks and Gray Level Gradient,
ICCVG12(105-112).
Springer DOI 1210
BibRef

Donoghue, C.R.[Claire R.], Rao, A.[Anil], Bull, A.M.J.[Anthony M. J.], Rueckert, D.[Daniel],
Robust Global Registration through Geodesic Paths on an Empirical Manifold with Knee MRI from the Osteoarthritis Initiative (OAI),
WBIR12(1-10).
Springer DOI 1208
BibRef

Guerrero, R.[Ricardo], Donoghue, C.R.[Claire R.], Pizarro, L.[Luis], Rueckert, D.[Daniel],
Learning Correspondences in Knee MR Images from the Osteoarthritis Initiative,
MLMI12(218-225).
Springer DOI 1211
BibRef

Donoghue, C.R.[Claire R.], Rao, A.[Anil], Pizarro, L.[Luis], Bull, A.M.J.[Anthony M. J.], Rueckert, D.[Daniel],
Fast and accurate global geodesic registrations using knee MRI from the Osteoarthritis Initiative,
MCV12(50-57).
IEEE DOI 1207
BibRef

Akter, M., Lambert, A.J., Pickering, M.R., Scarvell, J.M., Smith, P.N.,
A 2D-3D Image Registration Algorithm Using Log-Polar Transforms for Knee Kinematic Analysis,
DICTA12(1-8).
IEEE DOI 1303
BibRef

Masum, M.A., Lambert, A.J., Pickering, M.R., Scarvell, J.M., Smith, P.N.,
Precision Assessment of B-Mode Ultrasound for Non-Invasive Motion Analysis of Knee Joints,
DICTA11(279-284).
IEEE DOI 1205
BibRef

Shan, L.[Liang], Charles, C.[Cecil], Niethammer, M.[Marc],
Automatic atlas-based three-label cartilage segmentation from MR knee images,
MMBIA12(241-246).
IEEE DOI 1203
BibRef

Ramli, I.S.[Intan Syaherra], Arshad, H.[Haslina], Sulong, A.B.[Abu Bakar], Yahaya, N.H.M.[Nor Hamdan Mohammed], Haron, C.H.C.[Che Hassan Che],
Visualization of the Newly Designed Jig and Fixture for Computer-Assisted Knee Replacement Surgery,
IVIC09(223-231).
Springer DOI 0911
BibRef

Yusof, S.F.[Siti Fairuz], Sulaiman, R.[Riza], Seng, L.T.[Lee Thian], Kassim, A.Y.M.[Abdul Yazid Mohammed], Abdullah, S.[Suhail], Yusof, S.[Shahril], Omar, M.[Masbah], Hamid, H.A.[Hamzaini Abdul],
Development of Total Knee Replacement Digital Templating Software,
IVIC09(180-190).
Springer DOI 0911
BibRef

Park, S.H.[Sang Hyun], Lee, S.[Soochahn], Shim, H.[Hackjoon], Yun, I.D.[Il Dong], Lee, S.U.[Sang Uk], Lee, K.H.[Kyoung Ho], Kang, H.S.[Heung Sik], Han, J.K.[Joon Koo],
Fully automatic 3-D segmentation of knee bone compartments by iterative local branch-and-mincut on MR images from osteoarthritis initiative (OAI),
ICIP09(3381-3384).
IEEE DOI 0911
BibRef

Seisler, A.R., Sheehan, F.T.,
A Visualization Tool to convey Quantitative in vivo, 3D Knee Joint Kinematics,
AIPR06(18-18).
IEEE DOI 0610
BibRef

Impoco, G.[Gaetano],
Level Set Segmentation of Knee Bones Using Normal Profile Models,
MIRAGE09(195-206).
Springer DOI 0905
BibRef

Hermans, J., Bellemans, J., Maes, F., Vandermeulen, D., Suetens, P.,
A statistical framework for the registration of 3D knee implant components to single-plane X-ray images,
MMBIA08(1-8).
IEEE DOI 0806
BibRef

Hermans, J., Bellemans, J., Vandermeulen, D., Suetens, P.,
A Statistical Approach to Determine Symmetrical Solutions for the Registration of 3D Knee Implant Models to Sagittal Fluoroscopy Images,
MMBIA07(1-8).
IEEE DOI 0710
BibRef

Tsechpenakis, G.[Gabriel], Wang, J.H.[Jian-Hua],
CRF-Based Segmentation of Human Tear Meniscus Obtained with Optical Coherence Tomography,
ICIP07(V: 509-512).
IEEE DOI 0709
BibRef

Ardizzone, E.[Edoardo], Pirrone, R.[Roberto], Gambino, O.[Orazio],
Frequency Determined Homomorphic Unsharp Masking Algorithm on Knee MR Images,
CIAP05(922-929).
Springer DOI 0509
BibRef

Hoff, W.A., Komistek, R.D., Dennis, D.A., Walker, S., Northcut, E., and Spargo, K.,
Pose Estimation of Artificial Knee Implants in Fluoroscopy Images Using a Template Matching Technique,
WACV96(181-186).
IEEE DOI 9609
BibRef

Dessenne, V., Lavallee, S., Julliard, R., Cinquin, P., Orti, R.,
Computer Assisted Knee Anterior Cruciate Ligament Reconstruction: First Clinical Tests,
CVRMed95(XX-YY) BibRef 9500

Zhi, H.,
Recognition system for automatic diagnosis of knee ligaments,
ICPR90(I: 597-602).
IEEE DOI 9006
BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Tomographic Images, CAT Scans (Computed Axial Tomography) .


Last update:Sep 18, 2017 at 11:34:11