21.7.4.3 Medical Applications, Vertebra, Spine, Skeletons, Bone

Baka, N., Leenstra, S., van Walsum, T.,
Ultrasound Aided Vertebral Level Localization for Lumbar Surgery,
MedImg(36), No. 10, October 2017, pp. 2138-2147.
IEEE DOI 1710
biomedical ultrasonics, bone, image matching, image registration, medical neural nets, surgery, ultrasonic imaging, 2D sagittal US, US images, BibRef

Al Arif, S.M.M.R.[S.M. Masudur Rahman], Asad, M.[Muhammad], Gundry, M.[Michael], Knapp, K.[Karen], Slabaugh, G.G.[Gregory G.],
Patch-based corner detection for cervical vertebrae in X-ray images,
SP:IC(59), No. 1, 2017, pp. 27-36.
Elsevier DOI 1711
Cervical BibRef

Abufadel, A.[Amer], Slabaugh, G.G.[Gregory G.], Unal, G.[Gozde], Zhang, L.[Li], Odry, B.[Benjamin],
Interacting Active Rectangles for Estimation of Intervertebral Disk Orientation,
ICPR06(I: 1013-1016).
IEEE DOI 0609
BibRef

Liao, H., Mesfin, A., Luo, J.,
Joint Vertebrae Identification and Localization in Spinal CT Images by Combining Short- and Long-Range Contextual Information,
MedImg(37), No. 5, May 2018, pp. 1266-1275.
IEEE DOI 1805
Biomedical imaging, Computed tomography, Feature extraction, Pathology, Task analysis, recurrent neural network BibRef

Palkar, B.[Bhakti], Mishra, D.[Dhirendra],
Fusion of multi-modal lumbar spine images using Kekre's hybrid wavelet transform,
IET-IPR(13), No. 12, October 2019, pp. 2271-2280.
DOI Link 1911
BibRef

Aubert, B., Vazquez, C., Cresson, T., Parent, S., de Guise, J.A.,
Toward Automated 3D Spine Reconstruction from Biplanar Radiographs Using CNN for Statistical Spine Model Fitting,
MedImg(38), No. 12, December 2019, pp. 2796-2806.
IEEE DOI 1912
Image reconstruction, Shape, Solid modeling, Deformable models, Hidden Markov models, patch-based methods BibRef

Chen, Y., Gao, Y., Li, K., Zhao, L., Zhao, J.,
Vertebrae Identification and Localization Utilizing Fully Convolutional Networks and a Hidden Markov Model,
MedImg(39), No. 2, February 2020, pp. 387-399.
IEEE DOI 2002
Automatic vertebrae identification and localization, CT image, deep learning, convolutional neural network, fully convolutional network BibRef

Sundarsingh, S.[Shirly], Kesavan, R.[Ramesh],
Diagnosis of disc bulge and disc desiccation in lumbar MRI using concatenated shape and texture features with random forest classifier,
IJIST(30), No. 2, 2020, pp. 340-347.
DOI Link 2005
disc bulge, disc desiccation, feature extraction, HOG, LS-RBRP, MRI, RF classifier BibRef

Ghoshal, S.[Somoballi], Banu, S.[Sourav], Chakrabarti, A.[Amlan], Sur-Kolay, S.[Susmita], Pandit, A.[Alok],
3D reconstruction of spine image from 2D MRI slices along one axis,
IET-IPR(14), No. 12, October 2020, pp. 2746-2755.
DOI Link 2010
BibRef

Silvoster, M.L.[M. Leena], Kumar, R.M.S.[Retnaswami Mathusoothana S.],
Efficient segmentation of lumbar intervertebral disc from MR images,
IET-IPR(14), No. 13, November 2020, pp. 3076-3083.
DOI Link 2012
BibRef

Pang, S., Pang, C., Zhao, L., Chen, Y., Su, Z., Zhou, Y., Huang, M., Yang, W., Lu, H., Feng, Q.,
SpineParseNet: Spine Parsing for Volumetric MR Image by a Two-Stage Segmentation Framework With Semantic Image Representation,
MedImg(40), No. 1, January 2021, pp. 262-273.
IEEE DOI 2012
Image segmentation, Image representation, Semantics, Computed tomography, graph convolution BibRef

Mandel, W., Oulbacha, R., Roy-Beaudry, M., Parent, S., Kadoury, S.,
Image-Guided Tethering Spine Surgery With Outcome Prediction Using Spatio-Temporal Dynamic Networks,
MedImg(40), No. 2, February 2021, pp. 491-502.
IEEE DOI 2102
Surgery, Solid modeling, outcome prediction, Predictive models, Forecasting, Magnetic resonance imaging BibRef

Feng, S.X.[Shi-Xiang], Liu, B.B.[Bei-Bei], Zhang, Y.[Ya], Zhang, X.Y.[Xiao-Yun], Li, Y.H.[Yue-Hua],
Two-Stream Compare and Contrast Network for Vertebral Compression Fracture Diagnosis,
MedImg(40), No. 9, September 2021, pp. 2496-2506.
IEEE DOI 2109
Task analysis, Feature extraction, Cancer, Streaming media, Weight control, Shape, Medical diagnostic imaging, two-stream BibRef

Saminathan, P.[Priya], Samuel, L.[Letitia],
Ant Cuckoo Search Optimization-based deep learning classifier for image enhancement in spinal cord images,
IJIST(31), No. 4, 2021, pp. 2267-2282.
DOI Link 2112
Ant Lion Optimization, circular-based searching method, Cuckoo Search Optimization, image enhancement, Image Enhancement Conditional Generative Adversarial Network BibRef

Nazir, A.[Anam], Cheema, M.N.[Muhammad Nadeem], Sheng, B.[Bin], Li, P.[Ping], Li, H.[Huating], Xue, G.T.[Guang-Tao], Qin, J.[Jing], Kim, J.M.[Jin-Man], Feng, D.D.[David Dagan],
ECSU-Net: An Embedded Clustering Sliced U-Net Coupled With Fusing Strategy for Efficient Intervertebral Disc Segmentation and Classification,
IP(31), 2022, pp. 880-893.
IEEE DOI 2201
Image segmentation, Computed tomography, Image resolution, Solid modeling, Loss measurement, Bones, Vertebra segmentation, 2-dimensional U-Net BibRef

Wu, M.K.[Meng-Kun], Sun, H.[Hao], Sun, Z.H.[Zhen-Hui], Guo, X.[Xin], Duan, L.H.[Lun-Hui], Tan, Y.L.[Ying-Lun], Cui, R.[Rui],
A machine learning-based method for automatic diagnosis of ankle fracture using X-ray images,
IJIST(32), No. 3, 2022, pp. 831-842.
DOI Link 2205
ankle fracture diagnosis, extreme gradient boosting, random forest, support vector machine, SURF-BoVW BibRef

Altun, S.[Sinan], Alkan, A.[Ahmet],
LSS-net: 3-dimensional segmentation of the spinal canal for the diagnosis of lumbar spinal stenosis,
IJIST(33), No. 1, 2023, pp. 378-388.
DOI Link 2301
3D-UNet, chronic low back pain, lumbar spinal stenosis, semantic segmentation BibRef

Yoon, H.[Heewon], Cho, Y.[Yongwon], Ahn, K.S.[Kyung-Sik], Lee, H.G.[Hee-Gone], Kang, C.H.[Chang Ho], Park, B.J.[Beom Jin],
Using a convolutional neural network model to derive imaging landmarks for lumbar spine numbering on axial magnetic resonance images,
IJIST(33), No. 2, 2023, pp. 547-555.
DOI Link 2303
back muscles, computer, lumbar vertebrae, MRI, neural networks BibRef

Kumari, K.H.V.[K. H. Vijaya], Barpanda, S.S.[Soubhagya Sankar],
Residual UNet with Dual Attention: An ensemble residual UNet with dual attention for multi-modal and multi-class brain MRI segmentation,
IJIST(33), No. 2, 2023, pp. 644-658.
DOI Link 2303
CerebroSpinalFluid, channel attention, GrayMatter, ResidalUNet, spatial attention, WhiteMatter BibRef

Blanc, C.[Colline], Shahrampour, S.[Shiva], Mohamed, F.B.[Feroze B.], de Leener, B.[Benjamin],
Combining PropSeg and a convolutional neural network for automatic spinal cord segmentation in pediatric populations and patients with spinal cord injury,
IJIST(33), No. 4, 2023, pp. 1396-1405.
DOI Link 2307
automatic segmentation, convolutional neural network, pediatric, PropSeg, spinal cord, spinal cord injury BibRef

Cheng, M.[Mengdan], Qin, J.[Juan], Lv, L.[Lianrong], Wang, B.[Biao], Li, L.[Lei], Xia, D.[Dan], Wang, S.[Shike],
A dual channel and spatial attention network for automatic spine segmentation of MRI images,
IJIST(33), No. 5, 2023, pp. 1634-1646.
DOI Link 2310
deep learning, dual channel and spatial attention module, MRI image, spine segmentation BibRef

Lu, S.Y.[Shu-Yi], Liu, J.H.[Jin-Hua], Wang, X.J.[Xiao-Jie], Zhou, Y.F.[Yuan-Feng],
Collaborative Multi-Metadata Fusion to Improve the Classification of Lumbar Disc Herniation,
MedImg(42), No. 12, December 2023, pp. 3590-3601.
IEEE DOI 2312
BibRef

Huang, J.Z.[Jun-Zhang], Zhu, X.F.[Xiong-Feng], Chen, Z.Y.[Zi-Yang], Lin, G.[Guoye], Huang, M.Y.[Mei-Yan], Feng, Q.J.[Qian-Jin],
Pathological Priors Inspired Network for Vertebral Osteophytes Recognition,
MedImg(43), No. 7, July 2024, pp. 2522-2536.
IEEE DOI Code:
WWW Link. 2407
Lesions, Feature extraction, Task analysis, Pathology, Medical diagnostic imaging, Wavelet transforms, Training, wavelet transform BibRef

Deng, S.C.[Shuang-Cheng], Yang, Y.[Yang], Wang, J.Y.[Jun-Yang], Li, A.[Aijing], Li, Z.W.[Zhi-Wu],
Efficient SpineUNetX for X-ray: A spine segmentation network based on ConvNeXt and UNet,
JVCIR(103), 2024, pp. 104245.
Elsevier DOI 2409
Spinal X-ray segmentation, Multi-scale feature fusion, U-Net BibRef

Hein, J.[Jonas], Giraud, F.[Frédéric], Calvet, L.[Lilian], Schwarz, A.[Alexander], Cavalcanti, N.A.[Nicola Alessandro], Prokudin, S.[Sergey], Farshad, M.[Mazda], Tang, S.[Siyu], Pollefeys, M.[Marc], Carrillo, F.[Fabio], Fürnstahl, P.[Philipp],
Creating a Digital Twin of Spinal Surgery: A Proof of Concept,
EnhanceMedIm24(2355-2364)
IEEE DOI 2410
Training, Solid modeling, Automation, Surgery, Training data, Virtual environments, Surgery Digitization, OR-X BibRef

Zhang, F.[Fan], Zheng, L.[Linya], Chen, Y.R.[Yin-Ran], Lin, C.[Chen], Huang, L.P.[Li-Ping], Bai, Y.M.[Yu-Ming], Luo, X.B.[Xiong-Biao],
Fully Automatic Cervical Vertebrae Segmentation Via Enhanced U2-Net,
ICIP23(2900-2904)
IEEE DOI 2312
BibRef