21.7.5.2 Medical Applications, Pelvic Bones, Fracture, Surgery

Chapter Contents (Back)
Pelvis. Pelvic Fracture. Pelvic Surgery. Skeletal. 2606

Sarry, L., Tilmant, C., Boisgard, S., Boire, J.Y., Levai, J.P.,
Monitoring of polyethylene wear in nonmetal-backed acetubular cups by digitized anteroposterior pelvic radiography,
MedImg(22), No. 9, September 2003, pp. 1172-1182.
IEEE Abstract. 0309
BibRef

Wu, J.[Jie], Belle, A.[Ashwin], Hargraves, R.H.[Rosalyn H.], Cockrell, C.[Charles], Tang, Y.[Yang], Najarian, K.[Kayvan],
Bone segmentation and 3D visualization of CT images for traumatic pelvic injuries,
IJIST(24), No. 1, 2014, pp. 29-38.
DOI Link 1403
traumatic pelvic injury BibRef

Chen, C.[Cheng], Zheng, G.Y.[Guo-Yan],
Fully automatic segmentation of AP pelvis X-rays via random forest regression with efficient feature selection and hierarchical sparse shape composition,
CVIU(126), No. 1, 2014, pp. 1-10.
Elsevier DOI 1407
BibRef
Earlier:
Fully Automatic Segmentation of AP Pelvis X-rays via Random Forest Regression and Hierarchical Sparse Shape Composition,
CAIP13(335-343).
Springer DOI 1308
BibRef
Earlier:
Robust Proximal Femur Segmentation in Conventional X-Ray Images via Random Forest Regression on Multi-resolution Gradient Features,
ICIAR13(442-450).
Springer DOI 1307
X-ray radiograph BibRef

Zheng, G.Y.[Guo-Yan], Dong, X.[Xiao],
Particle Filter Based Automatic Reconstruction of a Patient-Specific Surface Model of a Proximal Femur from Calibrated X-Ray Images for Surgical Navigation,
ACIVS07(616-627).
Springer DOI 0708
BibRef
Earlier: A2, A1:
A Computational Framework for Automatic Determination of Morphological Parameters of Proximal Femur from Intraoperative Fluoroscopic Images,
ICPR06(I: 1008-1013).
IEEE DOI 0609
BibRef
And: A2, A1:
Fully Automatic Determination of Morphological Parameters of Proximal Femur from Calibrated Fluoroscopic Images Through Particle Filtering,
ICIAR06(II: 535-546).
Springer DOI 0610
BibRef

Dong, X.[Xiao], Gonzalez Ballester, M.A.[Miguel A.], Zheng, G.Y.[Guo-Yan],
Automatic Extraction of Femur Contours from Calibrated Fluoroscopic Images,
WACV07(55-55).
IEEE DOI 0702
BibRef

Cao, X., Yang, J., Gao, Y., Wang, Q., Shen, D.,
Region-Adaptive Deformable Registration of CT/MRI Pelvic Images via Learning-Based Image Synthesis,
IP(27), No. 7, July 2018, pp. 3500-3512.
IEEE DOI 1805
Bidirectional control, Biological tissues, Computed tomography, Image generation, Image registration, Magnetic resonance imaging, radiation therapy BibRef

Morooka, K.[Ken'ichi], Matsubara, R.[Ryota], Miyauchi, S.[Shoko], Fukuda, T.[Takaichi], Sugii, T.[Takeshi], Kurazume, R.[Ryo],
Ancient pelvis reconstruction from collapsed component bones using statistical shape models,
MVA(30), No. 1, February 2019, pp. 59-69.
Springer DOI 1904
BibRef

Zhang, Y., Li, F., Qiu, L., Xu, L., Niu, X., Sui, Y., Zhang, S., Zhang, Q., Zhang, L.,
Toward Precise Osteotomies: A Coarse-to-Fine 3D Cut Plane Planning Method for Image-Guided Pelvis Tumor Resection Surgery,
MedImg(39), No. 5, May 2020, pp. 1511-1523.
IEEE DOI 2005
Tumors, Planning, Bones, Surgery, Pelvis, Cut plane planning, 3D cut plane refinement BibRef

Liu, C., Xie, H., Zhang, S., Mao, Z., Sun, J., Zhang, Y.,
Misshapen Pelvis Landmark Detection With Local-Global Feature Learning for Diagnosing Developmental Dysplasia of the Hip,
MedImg(39), No. 12, December 2020, pp. 3944-3954.
IEEE DOI 2012
Pelvis, Feature extraction, Deep learning, Hip, X-ray imaging, Medical diagnostic imaging, Developmental dysplasia of the hip, medical imaging BibRef

Zeng, B.[Bolun], Wang, H.X.[Hui-Xiang], Xu, J.C.[Jiang-Chang], Tu, P.[Puxun], Joskowicz, L.[Leo], Chen, X.J.[Xiao-Jun],
Two-Stage Structure-Focused Contrastive Learning for Automatic Identification and Localization of Complex Pelvic Fractures,
MedImg(42), No. 9, September 2023, pp. 2751-2762.
IEEE DOI 2310
BibRef

Ali, M.[Mudassar], Hu, H.J.[Hao-Ji], Wu, T.[Tong], Mansoor, M.[Maryam], Luo, Q.[Qiong], Zheng, W.Z.[Wei-Zeng], Jin, N.[Neng],
Segmentation of MRI tumors and pelvic anatomy via cGAN-synthesized data and attention-enhanced U-Net,
PRL(187), 2025, pp. 100-106.
Elsevier DOI 2501
Medical image segmentation, Synthetic data, Conditional GAN, U-Net, Attention gates, MRI, Brain tumor, Liver tumor, Pelvic organ BibRef

Chen, H.M.[Hao-Min], Dreizin, D.[David], Gomez, C.[Catalina], Zapaishchykova, A.[Anna], Unberath, M.[Mathias],
Interpretable Severity Scoring of Pelvic Trauma Through Automated Fracture Detection and Bayesian Inference,
MedImg(44), No. 1, January 2025, pp. 130-141.
IEEE DOI 2501
Computed tomography, Injuries, Bayes methods, Feature extraction, Artificial intelligence, Deep learning, Bayesian inference, human-computer interaction BibRef

Zhao, X.[Xirui], Xiao, D.Q.[De-Qiang], Zhang, T.[Teng], Shao, L.[Long], Ai, D.[Danni], Fan, J.F.[Jing-Fan], Fu, T.Y.[Tian-Yu], Lin, Y.C.[Yu-Cong], Song, H.[Hong], Wang, J.Q.[Jun-Qiang], Yang, J.[Jian],
Pelvic Fracture Reduction Planning via Joint Shape-Intensity Reference,
MedImg(45), No. 4, April 2026, pp. 1352-1368.
IEEE DOI 2604
Planning, Computed tomography, Bones, Shape, Pelvis, Surgery, Image synthesis, Image segmentation, Image reconstruction, landmark graph BibRef

Liu, J.X.[Jia-Xuan], Li, H.T.[Hai-Tao], Zeng, B.[Bolun], Wang, H.X.[Hui-Xiang], Kikinis, R.[Ron], Joskowicz, L.[Leo], Chen, X.J.[Xiao-Jun],
An End-to-End Geometry-Based Pipeline for Automatic Preoperative Surgical Planning of Pelvic Fracture Reduction and Fixation,
MedImg(44), No. 1, January 2025, pp. 79-91.
IEEE DOI 2501
Planning, Bones, Labeling, Surgery, Surface cracks, Fasteners, Pipelines, Computer-assisted surgery, preoperative planning, pelvic fracture reduction BibRef

Sang, Y.[Yudi], Liu, Y.Z.[Yan-Zhen], Yibulayimu, S.[Sutuke], Wang, Y.N.[Yun-Ning], Killeen, B.D.[Benjamin D.], Liu, M.X.[Ming-Xu], Ku, P.C.[Ping-Cheng], Johannsen, O.[Ole], Gotkowski, K.[Karol], Zenk, M.[Maximilian], Maier-Hein, K.[Klaus], Isensee, F.[Fabian], Yue, P.[Peiyan], Wang, Y.[Yi], Yu, H.D.[Hai-Dong], Pan, Z.H.[Zhao-Hong], He, Y.T.[Yu-Tong], Liang, X.K.[Xiao-Kun], Liu, D.[Daiqi], Fan, F.[Fuxin], Jurgas, A.[Artur], Skalski, A.[Andrzej], Ma, Y.X.[Yu-Xi], Yang, J.[Jing], Plotka, S.[Szymon], Litka, R.[Rafal], Zhu, G.[Gang], Song, Y.C.[Ying-Chun], Unberath, M.[Mathias], Armand, M.[Mehran], Ruan, D.[Dan], Zhou, S.K.[S. Kevin], Cao, Q.[Qiyong], Zhao, C.P.[Chun-Peng], Wu, X.[Xinbao], Wang, Y.[Yu],
Benchmark of Segmentation Techniques for Pelvic Fracture in CT and X-Ray: Summary of the PENGWIN 2024 Challenge,
MedImg(45), No. 5, May 2026, pp. 2212-2228.
IEEE DOI 2605
Image segmentation, Computed tomography, X-ray imaging, Biomedical imaging, Planning, Surgery, Accuracy, Robots, Deep learning, pelvic fracture BibRef


Kim, D.[Daniel], Al-masni, M.A.[Mohammed A.], Lee, J.H.[Jae-Hun], Kim, D.H.[Dong-Hyun], Ryu, K.[Kanghyun],
Improving Pelvic MR-CT Image Alignment with Self-Supervised Reference-Augmented Pseudo-CT Generation Framework,
WACV25(347-356)
IEEE DOI Code:
WWW Link. 2505
Training, Measurement, Translation, Deformation, Image synthesis, Computed tomography, Source coding, Training data, self-supervised learning BibRef

Chen, H.M.[Hao-Min], Wang, Y.R.[Yi-Rui], Zheng, K.[Kang], Li, W.J.[Wei-Jian], Chang, C.T.[Chi-Tung], Harrison, A.P.[Adam P.], Xiao, J.[Jing], Hager, G.D.[Gregory D.], Lu, L.[Le], Liao, C.H.[Chien-Hung], Miao, S.[Shun],
Anatomy-aware Siamese Network: Exploiting Semantic Asymmetry for Accurate Pelvic Fracture Detection in X-ray Images,
ECCV20(XXIII:239-255).
Springer DOI 2011
BibRef

Malladi, S.P.K.[Sai Phani Kumar], Veduruparthi, B.K.[Bijju Kranthi], Mukherjee, J.[Jayanta], Das, P.P.[Partha Pratim], Chakrabarti, S.[Saswat], Mallick, I.[Indranil],
Automated Measurement of Translational Margins and Rotational Shifts in Pelvic Structures Using CBCT Images of Rectal Cancer Patients,
PReMI17(103-109).
Springer DOI 1711
BibRef

Bay, T.[Thierry], Raffin, R.[Romain], Daniel, M.[Marc],
Discrete Geometric Modeling of Thick Pelvic Organs with a Medial Axis,
ICCVG12(14-21).
Springer DOI 1210
BibRef

Zhang, C.[Cheng], Christensen, G.E.[Gary E.], Kurtek, S.[Sebastian], Srivastava, A.[Anuj], Murphy, M.J.[Martin J.], Weiss, E.[Elisabeth], Bai, E.[Erwei], Williamson, J.F.[Jeffrey F.],
SUPIR: Surface Uncertainty-Penalized, Non-rigid Image Registration for Pelvic CT Imaging,
WBIR12(236-245).
Springer DOI 1208
BibRef

Chowdhury, A.S.[Ananda S.], Burns, J.[Joseph], Sen, B.[Bhaskar], Mukherjee, A.[Arka], Yao, J.H.[Jian-Hua], Summers, R.M.[Ronald M.],
Detection of pelvic fractures using graph cuts and curvatures,
ICIP11(1573-1576).
IEEE DOI 1201
BibRef

Constantinou, C.E.[Christos E.], McLean, L.[Linda], Kuhl, E.[Ellen], Chen, B.[Bertha],
Imaging-Based Computation of the Dynamics of Pelvic Floor Deformation and Strain Visualization Analysis,
ISVC10(III: 604-612).
Springer DOI 1011
BibRef

Ding, F.[Feng], Leow, W.K.[Wee Kheng], Howe, T.S.[Tet Sen],
Automatic Segmentation of Femur Bones in Anterior-Posterior Pelvis X-Ray Images,
CAIP07(205-212).
Springer DOI 0708
BibRef

Chen, Y.[Ying], Ee, X.[Xianhe], Leow, W.K.[Wee Kheng], Howe, T.S.[Tet Sen],
Automatic Extraction of Femur Contours from Hip X-Ray Images,
CVBIA05(200-209).
Springer DOI 0601
BibRef

Tanács, A.[Attila], Máté, E.[Eörs], Kuba, A.[Attila],
Application of Automatic Image Registration in a Segmentation Framework of Pelvic CT Images,
CAIP05(628).
Springer DOI 0509
BibRef

Jedrzejek, C.[Czeslaw], Lempicki, A.[Andrzej], Renk, R.[Rafa], Radziulis, J.[Jakub],
3-D Modeling and Parametrisation of Pelvis and Hip Joint,
CAIP01(282 ff.).
Springer DOI 0210
BibRef

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


Last update:Jun 4, 2026 at 16:38:45