21.7.3.10 Ribs, Chest X-Rays

Chapter Contents (Back)
Chest X-Ray. Ribs. Medical, Applications.

Wechsler, H., Sklansky, J.,
Finding the Rib Cage in Chest Radiographs,
PR(9), No. 1, January 1977, pp. 21-30.
Elsevier DOI BibRef 7701
Earlier:
Automatic Detection of Rib Contours in Chest Radiographs,
IJCAI75(688-694). BibRef

Wechsler, H., and Fu, K.S.,
Image Processing Algorithms Applied to Rib Boundary Detection in Chest Radiographs,
CGIP(7), No. 3, June 1978, pp. 375-390.
Elsevier DOI BibRef 7806

de Souza, P.,
Automatic Rib Detection in Chest Radiographs,
CVGIP(23), No. 2, August 1983, pp. 129-161.
Elsevier DOI BibRef 8308

Suzuki, K., Abe, H., MacMahon, H., Doi, K.,
Image-Processing Technique for Suppressing Ribs in Chest Radiographs by Means of Massive Training Artificial Neural Network (MTANN),
MedImg(25), No. 4, April 2006, pp. 406-416.
IEEE DOI 0604
BibRef

Loog, M., van Ginneken, B.,
Segmentation of the Posterior Ribs in Chest Radiographs Using Iterated Contextual Pixel Classification,
MedImg(25), No. 5, May 2006, pp. 602-611.
IEEE DOI 0605
BibRef
Earlier:
Supervised segmentation by iterated contextual pixel classification,
ICPR02(II: 925-928).
IEEE DOI 0211
BibRef

Gomez-Laberge, C., Arnold, J.H., Wolf, G.K.,
A Unified Approach for EIT Imaging of Regional Overdistension and Atelectasis in Acute Lung Injury,
MedImg(31), No. 3, March 2012, pp. 834-842.
IEEE DOI 1203
BibRef

Chen, S.[Sheng], Suzuki, K.,
Separation of Bones From Chest Radiographs by Means of Anatomically Specific Multiple Massive-Training ANNs Combined With Total Variation Minimization Smoothing,
MedImg(33), No. 2, February 2014, pp. 246-257.
IEEE DOI 1403
bone BibRef

Herrera, C.N.L., Vallejo, M.F.M., Mueller, J.L., Lima, R.G.,
Direct 2-D Reconstructions of Conductivity and Permittivity From EIT Data on a Human Chest,
MedImg(34), No. 1, January 2015, pp. 267-274.
IEEE DOI 1502
bioelectric potentials BibRef

Chen, T., Liu, J., Chao, P., Li, P.,
Ultrawideband Synthetic Aperture Radar for Respiratory Motion Detection,
GeoRS(53), No. 7, July 2015, pp. 3749-3763.
IEEE DOI 1503
Apertures BibRef

Oliveira, H.[Hugo], Mota, V.[Virginia], Machado, A.M.C.[Alexei M.C.], dos Santos, J.A.[Jefersson A.],
From 3D to 2D: Transferring knowledge for rib segmentation in chest X-rays,
PRL(140), 2020, pp. 10-17.
Elsevier DOI 2012
Chest X-rays, Deep domain adaptation, Rib segmentation, Generative adversarial networks BibRef

Huang, Y.J., Liu, W., Wang, X., Fang, Q., Wang, R., Wang, Y., Chen, H., Chen, H., Meng, D., Wang, L.,
Rectifying Supporting Regions With Mixed and Active Supervision for Rib Fracture Recognition,
MedImg(39), No. 12, December 2020, pp. 3843-3854.
IEEE DOI 2012
Cams, Ribs, X-ray imaging, Annotations, Image recognition, Training, Supervised learning, Convolutional neural network~(CNN), active learning~(AL) BibRef

Cao, Z.[Zheng], Xu, L.M.[Li-Ming], Chen, D.Z.[Danny Z.], Gao, H.H.[Hong-Hao], Wu, J.[Jian],
A Robust Shape-Aware Rib Fracture Detection and Segmentation Framework With Contrastive Learning,
MultMed(25), 2023, pp. 1584-1591.
IEEE DOI 2305
Ribs, Computed tomography, Image segmentation, Task analysis, Training, Deep learning, Computer-aided diagnosis, shape-aware model BibRef

Tsai, H.C.[Hsin-Chun], Lu, N.H.[Nan-Han], Liu, K.Y.[Kuo-Ying], Lin, C.H.[Chuan-Han], Wang, J.F.[Jhing-Fa],
Cascading AB-YOLOv5 and PB-YOLOv5 for rib fracture detection in frontal and oblique chest X-ray images,
IET-CV(17), No. 7, 2023, pp. 750-762.
DOI Link 2310
bone, computer vision, diseases BibRef

Jin, L.[Liang], Gu, S.[Shixuan], Wei, D.L.[Dong-Lai], Adhinarta, J.K.[Jason Ken], Kuang, K.[Kaiming], Zhang, Y.J.J.[Yong-Jie Jessica], Pfister, H.[Hanspeter], Ni, B.B.[Bing-Bing], Yang, J.C.[Jian-Cheng], Li, M.[Ming],
: A Large-Scale Benchmark for Rib Labeling and Anatomical Centerline Extraction,
MedImg(43), No. 1, January 2024, pp. 570-581.
IEEE DOI Code:
WWW Link. 2401
BibRef

Chai, Z.Z.[Zhi-Zhong], Luo, L.Y.[Lu-Yang], Lin, H.J.[Huang-Jing], Heng, P.A.[Pheng-Ann], Chen, H.[Hao],
Deep Omni-Supervised Learning for Rib Fracture Detection From Chest Radiology Images,
MedImg(43), No. 5, May 2024, pp. 1972-1982.
IEEE DOI Code:
WWW Link. 2405
Annotations, Ribs, Object detection, Biomedical imaging, Computed tomography, Data models, Lesions, Rib fracture, dynamic label assignment BibRef


Nguyen-Mau, T.H.[Trong-Hieu], Huynh, T.L.[Tuan-Luc], Le, T.D.[Thanh-Danh], Nguyen, H.D.[Hai-Dang], Tran, M.T.[Minh-Triet],
Advanced Augmentation and Ensemble Approaches for Classifying Long-Tailed Multi-Label Chest X-Rays,
CVAMD23(2721-2730)
IEEE DOI 2401
BibRef

Jeong, J.[Jaehyup], Jeoun, B.[Bosoung], Park, Y.[Yeonju], Han, B.H.[Bo-Hyung],
An Optimized Ensemble Framework for Multi-Label Classification on Long-Tailed Chest X-ray Data,
CVAMD23(2731-2738)
IEEE DOI 2401
BibRef

Seo, H.[HyeRyeong], Lee, M.[MinHyuk], Cheong, W.[WooJin], Yoon, H.[HyeKyung], Kim, S.[SoHyung], Kang, M.J.[Myung-Joo],
Enhancing Multi-Label Long-Tailed Classification on Chest X-Rays through ML-GCN Augmentation,
CVAMD23(2739-2748)
IEEE DOI 2401
BibRef

Kim, C.H.[Chang-Hyun], Kim, G.[Giyeol], Yang, S.[Sooyoung], Kim, H.[Hyunsu], Lee, S.[Sangyool], Cho, H.[Hansu],
Chest X-Ray Feature Pyramid Sum Model with Diseased Area Data Augmentation Method,
CVAMD23(2749-2758)
IEEE DOI 2401
BibRef

Chen, Y.H.[Yuan-Hong], Liu, F.[Fengbei], Wang, H.[Hu], Wang, C.[Chong], Liu, Y.[Yuyuan], Tian, Y.[Yu], Carneiro, G.[Gustavo],
BoMD: Bag of Multi-label Descriptors for Noisy Chest X-ray Classification,
ICCV23(21227-21238)
IEEE DOI Code:
WWW Link. 2401
BibRef

Kim, D.[Dongkyun],
CheXFusion: Effective Fusion of Multi-View Features using Transformers for Long-Tailed Chest X-Ray Classification,
CVAMD23(2694-2702)
IEEE DOI Code:
WWW Link. 2401
BibRef

Li, X.C.[Xue-Chen], Luo, S.H.[Su-Huai], Hu, Q.M.[Qing-Mao],
An Automatic Rib Segmentation Method on X-Ray Radiographs,
MMMod15(I: 128-139).
Springer DOI 1501
BibRef

Chen, S.[Sheng], Suzuki, K.[Kenji],
Bone suppression in chest radiographs by means of anatomically specific multiple massive-training ANNs,
ICPR12(17-20).
WWW Link. 1302
BibRef

Vinhais, C.[Carlos], Campilho, A.[Aurélio],
Ribcage Boundary Delineation in Chest X-ray Images,
ICIAR04(II: 59-67).
Springer DOI 0409
BibRef

Moreira, R.[Rui], Mendonça, A.M.[Ana Maria], Campilho, A.[Aurélio],
Detection of Rib Borders on X-ray Chest Radiographs,
ICIAR04(II: 108-115).
Springer DOI 0409
BibRef

Benjelloun, M., Teran, R.,
Visceral dynamic computing,
Southwest04(177-181).
IEEE DOI 0411
study motion in breathing. BibRef

Sarkar, S., Chaudhuri, S.,
Detection of rib shadows in digital chest radiographs,
CIAP97(II: 356-363).
Springer DOI 9709
BibRef

Sullivan, B.J., Ansari, R., Giger, M.L., MacMahon, H.,
Effects of image preprocessing/resizing on diagnostic quality of compressed medical images,
ICIP95(II: 13-16).
IEEE DOI 9510
BibRef
Earlier:
Relative effects of resolution and quantization on the quality of compressed medical images,
ICIP94(II: 987-991).
IEEE DOI 9411
chest radiographs application BibRef

Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Medical Applications -- Skeleton, Bone .


Last update:May 23, 2024 at 14:31:23