Table 2.

The top 50 downloads for papers published in the SPIE Medical Imaging conference proceedings.

	Authors	Title	Year	Volume	Number of downloads
1	Wu et al.52	Fully automated chest wall line segmentation in breast MRI using context information	2012	8315	4030
2	Fang et al.53	Unsupervised learning-based deformable registration of temporal chest radiographs to detect interval change	2020	11313	2528
3	Koenrades et al.54	Validation of an image registration and segmentation method to measure stent graft motion on ECG-gated CT using a physical dynamic stent graft model	2017	10134	2112
4	Wegmayr et al.55	Classification of brain MRI with big data and deep 3D convolutional neural networks	2018	10575	1878
5	Ayyagari et al.56	Image reconstruction using priors from deep learning	2018	10574	1858
6	Ruiter et al.57	USCT data challenge	2017	10139	1707
7	Bar et al.43	Deep learning with non-medical training used for chest pathology identification	2015	9414	1457
8	Mattes et al.58	Nonrigid multimodality image registration	2001	4322	1398
9	Cruz-Roa et al.42	Automatic detection of invasive ductal carcinoma in whole slide images with convolutional neural networks	2014	9041	1304
10	Sun et al.45	Computer aided lung cancer diagnosis with deep learning algorithms	2016	9785	1300
11	Alex et al.59	Generative adversarial networks for brain lesion detection	2017	10133	1290
12	Ramachandran S et al.60	Using YOLO based deep learning network for real time detection and localization of lung nodules from low dose CT scans	2018	10575	1183
13	Umehara et al.61	Super-resolution convolutional neural network for the improvement of the image quality of magnified images in chest radiographs	2017	10133	1174
14	Madani et al.62	Chest x-ray generation and data augmentation for cardiovascular abnormality classification	2018	10574	1142
15	Gjesteby et al.63	Deep learning methods to guide CT image reconstruction and reduce metal artifacts	2017	10132	1122
16	Jnawali et al.64	Deep 3D convolution neural network for CT brain hemorrhage classification	2018	10575	1096
17	Wei et al.65	Anomaly detection for medical images based on a one-class classification	2018	10575	1048
18	Eppenhof et al.66	Deformable image registration using convolutional neural networks	2018	10574	1005
19	Vassallo et al.67	Hologram stability evaluation for Microsoft HoloLens	2017	10136	1002
20	Dong et al.68	Sinogram interpolation for sparse-view micro-CT with deep learning neural network	2019	10948	983
21	Seibert et al.26	Flat-field correction technique for digital detectors	1998	3336	838
22	Bowles et al.69	Modelling the progression of Alzheimer’s disease in MRI using generative adversarial networks	2018	10574	815
23	Funke et al.70	Generative adversarial networks for specular highlight removal in endoscopic images	2018	10576	807
24	Duric et al.71	Breast imaging with the SoftVue imaging system: first results	2013	8675	786
25	Choi et al.72	Fast low-dose compressed-sensing (CS) image reconstruction in four-dimensional digital tomosynthesis using on-board imager (OBI)	2018	10573	782
26	Mescher and Lemmer73	Hybrid organic-inorganic perovskite detector designs based on multilayered device architectures: simulation and design	2019	10948	777
27	Jerman et al.74	Beyond Frangi: an improved multiscale vesselness filter	2015	9413	771
28	Lauritsch and Haerer75	Theoretical framework for filtered back projection in tomosynthesis	1998	3338	750
29	Mizutani et al.37	Automated microaneurysm detection method based on double ring filter in retinal fundus images	2009	7260	735
30	Roth et al.44	Deep convolutional networks for pancreas segmentation in CT imaging	2015	9413	735
31	de Vos et al.76	2D image classification for 3D anatomy localization: employing deep convolutional neural networks	2016	9784	727
32	Ionita et al.77	Challenges and limitations of patient-specific vascular phantom fabrication using 3D Polyjet printing	2014	9038	724
33	Clark et al.78	Multi-energy CT decomposition using convolutional neural networks	2018	10573	715
34	Peng et al.79	Design, optimization and testing of a multi-beam micro-CT scanner based on multi-beam field emission x-ray technology	2010	7622	712
35	Liu et al.47	Prostate cancer diagnosis using deep learning with 3D multiparametric MRI	2017	10134	702
36	Tsehay et al.80	Convolutional neural network based deep-learning architecture for prostate cancer detection on multiparametric magnetic resonance images	2017	10134	686
37	Graff81	A new, open-source, multi-modality digital breast phantom	2016	9783	684
38	Mertelmeier et al.32	Optimizing filtered backprojection reconstruction for a breast tomosynthesis prototype device	2006	6142	671
39	Hwang et al.46	A novel approach for tuberculosis screening based on deep convolutional neural networks	2016	9785	660
40	Hamidian et al.82	3D convolutional neural network for automatic detection of lung nodules in chest CT	2017	10134	636
41	Anirudh et al.51	Lung nodule detection using 3D convolutional neural networks trained on weakly labeled data	2016	9785	632
42	Moriya et al.83	Unsupervised segmentation of 3D medical images based on clustering and deep representation learning	2018	10578	623
43	Almazroa et al.84	Retinal fundus images for glaucoma analysis: the RIGA dataset	2018	10579	620
44	Niemeijer et al.85	Comparative study of retinal vessel segmentation methods on a new publicly available database	2004	5370	618
45	Maier et al.86	Deep scatter estimation (DSE): feasibility of using a deep convolutional neural network for real-time x-ray scatter prediction in cone-beam CT	2018	10573	612
46	Zhang and Xing87	CT artifact reduction via U-net CNN	2018	10574	608
47	McKeighen25	Design guidelines for medical ultrasonic arrays	1998	3341	604
48	Pohle and Toennies88	Segmentation of medical images using adaptive region growing	2001	4322	592
49	Moore et al.89	OMERO and Bio-Formats 5: flexible access to large bioimaging datasets at scale	2015	9413	592
50	Gaonkar et al.90	Deep learning in the small sample size setting: cascaded feed forward neural networks for medical image segmentation	2016	9785	588