ABCDEFGHIJKLMNOPQRSTUVWXYZ
1
序号是否有代码论文题目作者发表时间谷歌引用率代码链接所用数据集数据集下载地址（可选）备注
2
10Cascade of multi-scale convolutional neural networks for bone suppression of chest radiographs in gradient domainWei Yang, Yingyin Chen, Yunbi Liu
, Liming Zhong, Genggeng Qin, Zhentai Lu,Qianjin Feng, Wufan Chen		2017137646 posterior-anterior DES chest radiographs(private:南方医科大学南方医院)https://www.sciencedirect.com/science/article/pii/S1361841516301529
3
20Bone Suppression of Chest Radiographs With Cascaded Convolutional Networks in Wavelet DomainYingyin Chen; Xiaofang Gou; Xiuxia Feng; Yunbi Liu; Genggeng Qin; Qianjin Feng; Wei Yang; Wufan Chen201913a dataset that consists of 504 cases of real two-exposure DES CXRs (404 cases for training and 100 cases for test)https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8604005
4
31Image-to-Images Translation for Multi-Task Organ Segmentation and Bone Suppression in Chest X-Ray RadiographyMohammad Eslami; Solale Tabarestani; Shadi Albarqouni; Ehsan Adeli; Nassir Navab; Malek Adjouadi202042https://github.com/mohaEs/image-to-images-translationJSRT+BSE-JSRTBone suppression: https://www.kaggle.com/hmchuong/xray-bone-shadow-supression JSRT Segmentation Dataset: https://doi.org/10.25919/5c49548be0551https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8999560
5
40Deep Feature Disentanglement Learning for Bone Suppression in Chest RadiographsChunze Lin, Ruixiang Tang, Darryl D. Lin, Langechuan Liu, Jiwen Lu202024JSRT+BSE-JSRTBone suppression: https://www.kaggle.com/hmchuong/xray-bone-shadow-supressionhttps://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9098399
6
50Generating Dual-Energy Subtraction Soft-Tissue Images from Chest Radiographs via Bone Edge-Guided GANYunbi Liu, Mingxia Liu , Yuhua Xi, Genggeng Qin, Dinggang Shen,and Wei Yang20205DES(dual-energy subtraction) Dataset(private:南方医科大学南方医院)https://link.springer.com/chapter/10.1007/978-3-030-59713-9_65#Abs1
7
60GAN-based disentanglement learning for chest X-ray rib suppressionLuyi Han,Yuanyuan Lyu,Cheng Peng,S. Kevin Zhou202214two CT datasets: 896 CT volumes from LIDC-IDRI and 777 CT volumes from TianChi AI Competition for Healthcare organized by Alibaba and four CXR datasets: 11200TBX11K, 112120chest-14, 138 from Montgomery County and 662 from Shenzhen HospitalLIDC: https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=1966254https://www.sciencedirect.com/science/article/pii/S1361841522000226?via%3Dihub#sec0010
8
71DeBoNet: A deep bone suppression model ensemble to improve disease detection in chest radiographsSivaramakrishnan Rajaraman ,Gregg Cohen,Lillian Spear,Les Folio,Sameer Antani202210https://github.com/sivaramakrishnan-rajaraman/Bone-Suppresion-EnsembleBIMCV-COVID19+
Hannover Medical School, Hannover
Cohen et al.
Twitter COVID-19
RSNA CXR
NIH-CC-DES-Set 1
NIH-CC-DES-Set 2		详见原文https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0265691
9
81Generation of Virtual Dual Energy Images from Standard Single-Shot Radiographs using Multi-scale and Conditional Adversarial NetworkBo Zhou, Xunyu Lin, Brendan Eck, Jun Hou, David L. Wilson201817https://github.com/bbbbbbzhou/Virtual-Dual-EnergyPrivateExample data in https://github.com/bbbbbbzhou/Virtual-Dual-EnergyACCV
10
91Deep Learning Models for Bone Suppression in Chest RadiographsMaxim Gusarev; Ramil Kuleev; Adil Khan; Adin Ramirez Rivera; Asad Masood Khattak201749https://github.com/danielnflam/Deep-Learning-Models-for-bone-suppression-in-chest-radiographsfrom different online sources已获得https://ieeexplore.ieee.org/abstract/document/8058543
11
100Bone suppression for chest X-ray image using a convolutional neural filterMatsubara, N; Teramoto, A; (...); Fujita, H202021https://link.springer.com/article/10.1007/s13246-019-00822-w
12
110From 3D to 2D: Transferring knowledge for rib segmentation in chest X-raysHugo Oliveira, Virginia Mota, Alexei M.C. Machado, Jefersson A. dos Santos202010https://www.sciencedirect.com/science/article/pii/S0167865520303561?ref=pdf_download&fr=RR-2&rr=7e1dff7eab1a07b1
13
120Bone suppression on pediatric chest radiographs via a deep learning-based cascade modelKyungjin Cho, Jiyeon Seo, Sunggu Kyung, Mingyu Kim, Gil-Sun Hong, Namkug Kim20223seven multi-centers by the Korean obstructive lung disease cohort study, Health Examination Center of AMC.etchttps://www.sciencedirect.com/science/article/pii/S0169260722000128?via%3Dihub
14
130Bone suppression of lateral chest x-rays with imperfect and limited dual-energy subtraction imagesYunbi Liu, Fengxia Zeng, Mengwei Ma, Bowen Zheng, Zhaoqiang Yun, Genggeng Qin, Wei Yang, Qianjin Feng2023051 subjects of real lateral DES data and 240 lateral CXRs acquired(private:南方医科大学南方医院)https://www.sciencedirect.com/science/article/pii/S0895611123000046?via%3Dihub
15
140Bone structures extraction and enhancement in chest radiographs via CNN trained on synthetic dataOphir Gozes, Hayit Greenspan20209LIDC+NIH X-ray14https://wiki.cancerimagingarchive.net/pages/viewpage.action?pageId=1966254 https://www.kaggle.com/datasets/nih-chest-xrays/datahttps://arxiv.org/pdf/2003.10839.pdf
16
17
150Learning Bone Suppression from Dual Energy Chest X-rays using Adversarial NetworksDong Yul Oh, Il Dong Yun201817In DICOM formathttps://arxiv.org/abs/1811.02628
18
160Dilated conditional GAN for bone suppression in chest radiographs with enforced semantic featuresZhizhen Zhou, Luping Zhou, Kaikai Shen202011JSRT+BSE-JSRThttps://www.kaggle.com/hmchuong/xray-bone-shadow-supressionhttps://pubmed.ncbi.nlm.nih.gov/32621786/
19
170Bone Suppression on Chest Radiographs With Adversarial LearningJia Liang, Yuxing Tang, Youbao Tang, Jing Xiao, Ronald M. Summers202012Public: RSNA Pneumonia Detection Challenge Private: from the picture archiving and communication system (PACS) of their institute.https://www.kaggle.com/c/rsna-pneumonia-detection-challenge/datahttps://arxiv.org/abs/2002.03073
20
180Deep learning-based bone suppression in chest radiographs using CT-derived features：a feasibility studyGe Ren, Haonan Xiao, Sai-Kit Lam, Dongrong Yang, Tian Li, Xinzhi Teng, Jing Qin, Jing Cai20214https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8611463/
21
190Spatial feature and resolution maximization GAN for bone suppression in chest radiographsGeeta Rani, Ankit Misra, Vijaypal Singh Dhaka, Ester Zumpano, Eugenio Vocaturo 20226JSRT+BSE-JSRThttps://www.kaggle.com/hmchuong/xray-bone-shadow-supressionhttps://www.sciencedirect.com/science/article/pii/S0169260722004060
22
200Bone Suppression on Chest Radiographs for Pulmonary Nodule Detection: Comparison between a Generative Adversarial Network and Dual-Energy SubtractionBae, K (Bae, Kyungsoo); Oh, DY (Oh, Dong Yul); Yun, ID (Yun, Il Dong); Jeon, KN (Jeon, Kyung Nyeo)20228https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8743147/
23
210Autoencoder-based bone removal algorithm from x-ray images of the lungSeweryn Kalisz;Michal Marczyk202111.COVID-19 Xray
image classification, 2.the Bone Suppression set（马克西姆）		https://github.com/lindawangg/COVID-Net https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9635451
24
220Computer-aided Detection of Lung Tumors in Chest X-ray Images Using a Bone Suppression Algorithm and A Deep Learning FrameworkK Sato, N Kanno, T Ishii and Y Saijo20212https://iopscience.iop.org/article/10.1088/1742-6596/2071/1/012002/meta
25
241Chest X-Ray Bone Suppression for Improving Classification of Tuberculosis-Consistent FindingsSivaramakrishnan Rajaraman, Ghada Zamzmi, Les Folio, Philip Alderson, Sameer Antani202116https://github.com/danielnflam/CXR-bone-suppression https://github.com/sivaramakrishnan‐rajaraman/CXR‐bone‐suppressionJSRT CXR; Pediatric pneumonia CXR; RSNA CXR; Shenzhen TB CXR; Montgomery TB CXRhttps://www.kaggle.com/datasets/raddar/tuberculosis-chest-xrays-montgomery https://www.kaggle.com/datasets/andrewmvd/pediatric-pneumonia-chest-xray https://www.kaggle.com/datasets/raddar/tuberculosis-chest-xrays-shenzhen https://www.kaggle.com/competitions/rsna-pneumonia-detection-challenge/data https://ieee-dataport.org/open-access/x-ray-bone-shadow-suppressionhttps://arxiv.org/abs/2104.04518
26
251Development and validation of bone-suppressed deep learning classification of COVID-19 presentation in chest radiographsLam, NFD (Lam, Ngo Fung Daniel) ; Sun, HF (Sun, Hongfei) ; Song, LM (Song, Liming); Yang, DR (Yang, Dongrong); Zhi, SH (Zhi, Shaohua); Ren, G (Ren, Ge); Chou, PH (Chou, Pak Hei); Wan, SBN (Wan, Shiu Bun Nelson); Wong, MFE (Wong, Man Fung Esther); Chan, KK (Chan, King Kwong)20222很多模型的复现预训练的https://github.com/danielnflamX-ray Bone Shadow Suppression datasethttps://www.kaggle.com/hmchuong/xray-bone-shadow-supressionhttps://pubmed.ncbi.nlm.nih.gov/35782269/
27
260Improving Tuberculosis Recognition on Bone-Suppressed Chest X-Rays Guided by Task-Specific FeaturesYunbi Liu, Genggeng Qin, Yun Liu, Mingxia Liu & Wei Yang 20211https://link.springer.com/chapter/10.1007/978-3-030-87602-9_6
28
280Evaluation of Deep Learning Methods for Bone Suppression from Dual Energy Chest RadiographyIlyas Sirazitdinov, Konstantin Kubrak, Semen Kiselev, Alexey Tolkachev, Maksym Kholiavchenko & Bulat Ibragimov 20206https://link.springer.com/chapter/10.1007/978-3-030-61609-0_20
29
290Bone Suppression on Chest Radiographs for Pulmonary Nodule Detection: Comparison between a Generative Adversarial Network and Dual-Energy SubtractionBae, K (Bae, Kyungsoo); Oh, DY (Oh, Dong Yul); Yun, ID (Yun, Il Dong); Jeon, KN (Jeon, Kyung Nyeo)20228https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8743147/
30
300Improved detection of solitary pulmonary nodules on radiographs compared with deep bone suppression imagingWu, JF (Wu, Jiefang); Chen, WG (Chen, Weiguo); Zeng, FX (Zeng, Fengxia) ; Ma, L (Ma, Le) ; Xu, WM (Xu, Weimin); Yang, W (Yang, Wei) ; Qin, GG (Qin, Genggeng)20211https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8408784/
31
310Value of bone suppression software in chest radiographs for improving image quality and reducing radiation doseGil-Sun Hong, Kyung-Hyun Do, A-Yeon Son, Kyung-Wook Jo, Kwang Pyo Kim, Jihye Yun & Choong Wook Lee 20213https://link.springer.com/article/10.1007/s00330-020-07596-w
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100