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Popular Articles (August 2015)Includes the top 50 most frequently downloaded documents for this publication according to the most recent monthly usage statistics.

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1. The Multimodal Brain Tumor Image Segmentation

Benchmark (BRATS)

Menze, B.H. ; Jakab, A. ; Bauer, S. ; Kalpathy-Cramer, J. ;Farahani, K. ; Kirby, J. ; Burren, Y. ; Porz, N. ; Slotboom, J. ;Wiest, R. ; Lanczi, L. ; Gerstner, E. ; Weber, M.-A. ; Arbel, T. ;Avants, B.B. ; Ayache, N. ; Buendia, P. ; Collins, D.L. ; Cordier, N.; Corso, J.J. ; Criminisi, A. ; Das, T. ; Delingette, H. ; Demiralp, C. ;Durst, C.R. ; Dojat, M. ; Doyle, S. ; Festa, J. ; Forbes, F. ;Geremia, E. ; Glocker, B. ; Golland, P. ; Guo, X. ; Hamamci, A. ;Iftekharuddin, K.M. ; Jena, R. ; John, N.M. ; Konukoglu, E. ;Lashkari, D. ; Mariz, J.A. ; Meier, R. ; Pereira, S. ; Precup, D. ;Price, S.J. ; Raviv, T.R. ; Reza, S.M.S. ; Ryan, M. ; Sarikaya, D. ;Schwartz, L. ; Shin, H.-C. ; Shotton, J. ; Silva, C.A. ; Sousa, N. ;Subbanna, N.K. ; Szekely, G. ; Taylor, T.J. ; Thomas, O.M. ;Tustison, N.J. ; Unal, G. ; Vasseur, F. ; Wintermark, M. ; Ye, D.H. ;Zhao, L. ; Zhao, B. ; Zikic, D. ; Prastawa, M. ; Reyes, M. ; VanLeemput, K.Publication Year: 2015 , Page(s): 1993 - 2024

Cited by: Papers (1)

Abstract | PDF (4393 KB) | | HTML

2. Automated Vessel Segmentation Using Infinite Perimeter

Active Contour Model with Hybrid Region Information with

Application to Retinal Images

Yitian Zhao ; Rada, L. ; Ke Chen ; Harding, S.P. ; Yalin ZhengPublication Year: 2015 , Page(s): 1797 - 1807


3. Ultrasound Volume Projection Imaging for Assessment of

Scoliosis

Cheung, C.-W.J. ; Guang-Quan Zhou ; Siu-Yin Law ; Tak-ManMak ; Ka-Lee Lai ; Yong-Ping ZhengPublication Year: 2015 , Page(s): 1760 - 1768


| Abstract | PDF (1336 KB) | | HTML

4. Automatic Segmentation of Spinal Canals in CT Images via

Iterative Topology Refinement

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BROWSE MY SETTINGS GET HELP WHAT CAN I ACCESS?

Qian Wang ; Le Lu ; Dijia Wu ; El-Zehiry, N. ; Yefeng Zheng ;

Dinggang Shen ; Zhou, K.S.

Publication Year: 2015 , Page(s): 1694 - 1704



5. Deformable Medical Image Registration: A Survey

Sotiras, A. ; Davatzikos, C. ; Paragios, N.




6. The Delay Multiply and Sum Beamforming Algorithm in

Ultrasound B-Mode Medical Imaging

Matrone, G. ; Savoia, A.S. ; Caliano, G. ; Magenes, G.



7. 3-D active appearance models: segmentation of cardiac

MR and ultrasound images

Mitchell, S.C. ; Bosch, J.G. ; Lelieveldt, B.P.F. ; van der Geest,

R.J. ; Reiber, J.H.C. ; Sonka, M.


Cited by: Papers (96) | Patents (7)


8. A Digital Preclinical PET/MRI Insert and Initial Results

Weissler, B. ; Gebhardt, P. ; Duppenbecker, P.M. ; Wehner, J. ;

Schug, D. ; Lerche, C.W. ; Goldschmidt, B. ; Salomon, A. ; Verel, I.

; Heijman, E.. ; Perkuhn, M. ; Heberling, D. ; Botnar, R.M. ;

Kiessling, F. ; Schulz, V.

Publication Year: 2015 , Page(s): 1


Multimedia

Abstract | PDF (1818 KB)

9. Segmentation of brain MR images through a hidden

Markov random field model and the expectation-

maximization algorithm

Yongyue Zhang ; Brady, M. ; Smith, S.




10. Ultrasound image segmentation: a survey

Noble, J.A. ; Boukerroui, D.




11. Towards Large-Scale Histopathological Image Analysis:

Hashing-Based Image Retrieval

Xiaofan Zhang ; Wei Liu ; Dundar, M. ; Badve, S. ; Shaoting Zhang




12. Accurate Segmentation of Vertebral Bodies and

Processes Using Statistical Shape Decomposition and

Conditional Models

Pereanez, M. ; Lekadir, K. ; Castro-Mateos, I. ; Pozo, J.M. ;Lazary, A. ; Frangi, A.F.Publication Year: 2015 , Page(s): 1627 - 1639



13. Stacked Sparse Autoencoder (SSAE) for Nuclei Detection

on Breast Cancer Histopathology images

Xu, J. ; Xiang, L. ; Liu, Q. ; Gilmore, H. ; Wu, J. ; Tang, J. ;Madabhushi, A.Publication Year: 2015 , Page(s): 1

| Abstract | PDF (20148 KB)

14. Transfer Learning Improves Supervised Image

Segmentation Across Imaging Protocols

van Opbroek, A. ; Ikram, M.A. ; Vernooij, M.W. ; de Bruijne, M.Publication Year: 2015 , Page(s): 1018 - 1030


15. Nonrigid registration using free-form deformations:

application to breast MR images

Rueckert, D. ; Sonoda, L.I. ; Hayes, C. ; Hill, D.L.G. ; Leach, M.O. ;Hawkes, D.J.Publication Year: 1999 , Page(s): 712 - 721



16. Regression Segmentation for Spinal Images

Zhijie Wang ; Xiantong Zhen ; KengYeow Tay ; Osman, S. ;Romano, W. ; Shuo LiPublication Year: 2015 , Page(s): 1640 - 1648



17. A Framework for Automated Spine and Vertebrae

Interpolation-Based Detection and Model-Based

Segmentation

Korez, R. ; Ibragimov, B. ; Likar, B. ; Pernus, F. ; Vrtovec, T.Publication Year: 2015 , Page(s): 1649 - 1662



18. Evaluation and Comparison of Current Fetal Ultrasound

Image Segmentation Methods for Biometric Measurements: A

Grand Challenge

Rueda, S. ; Fathima, S. ; Knight, C.L. ; Yaqub, M. ;Papageorghiou, A.T. ; Rahmatullah, B. ; Foi, A. ; Maggioni, M. ;Pepe, A. ; Tohka, J. ; Stebbing, R.V. ; McManigle, J.E. ; Ciurte, A. ;Bresson, X. ; Cuadra, M.B. ; Changming Sun ; Ponomarev, G.V. ;Gelfand, M.S. ; Kazanov, M.D. ; Ching-Wei Wang ; Hsiang-ChouChen ; Chun-Wei Peng ; Chu-Mei Hung ; Noble, J.A.Publication Year: 2014 , Page(s): 797 - 813



19. Retinal vessel segmentation using the 2-D Gabor waveletand supervised classification

Soares, J.V.B. ; Leandro, J.J.G. ; Cesar, R.M. ; Jelinek, H.F. ;Cree, M.J.Publication Year: 2006 , Page(s): 1214 - 1222



20. Automatic Segmentation of the Spinal Cord and SpinalCanal Coupled With Vertebral Labeling

De Leener, B. ; Cohen-Adad, J. ; Kadoury, S.Publication Year: 2015 , Page(s): 1705 - 1718



21. A contribution of image processing to the diagnosis ofdiabetic retinopathy-detection of exudates in color fundusimages of the human retina

Walter, T. ; Klein, J.-C. ; Massin, P. ; Erginay, A.Publication Year: 2002 , Page(s): 1236 - 1243



22. Estimating CT Image from MRI Data Using StructuredRandom Forest and Auto-context Model

Huynh, T. ; Gao, Y. ; Kang, J. ; Wang, L. ; Zhang, P. ; Lian, J. ;Shen, D.Publication Year: 2015 , Page(s): 1


23. Statistical Interspace Models (SIMs): Application toRobust 3D Spine SegmentationCastro-Mateos, I. ; Pozo, J.M. ; Pereanez, M. ; Lekadir, K. ;Lazary, A. ; Frangi, A.F.Publication Year: 2015 , Page(s): 1663 - 1675



24. Reverse-Time Migration Based Optical Imaging

Wang, Z. ; Ding, H. ; Lu, G. ; Bi, X.Publication Year: 2015 , Page(s): 1


25. Multi-Modality Vertebra Recognition in Arbitrary ViewsUsing 3D Deformable Hierarchical Model

Yunliang Cai ; Osman, S. ; Sharma, M. ; Landis, M. ; Shuo LiPublication Year: 2015 , Page(s): 1676 - 1693



26. Generalized Overlap Measures for Evaluation andValidation in Medical Image Analysis

Crum, W.R. ; Camara, O. ; Hill, D.L.G.Publication Year: 2006 , Page(s): 1451 - 1461



27. Spinal Navigation and Imaging: History, Trends, and

Future

Helm, P.A. ; Teichman, R. ; Hartmann, S.L. ; Simon, D.




28. Multimodality image registration by maximization of

mutual information

Maes, F. ; Collignon, A. ; Vandermeulen, D. ; Marchal, G. ;

Suetens, P.




29. A New Supervised Method for Blood Vessel Segmentation

in Retinal Images by Using Gray-Level and Moment

Invariants-Based Features

Marin, D. ; Aquino, A. ; Gegundez-Arias, M.E. ; Bravo, J.M.




30. PET Image Reconstruction Using Kernel Method

Guobao Wang ; Jinyi Qi



31. A Reconstruction-Classification Method for

Multifrequency Electrical Impedance Tomography

Malone, E. ; Sato dos Santos, G. ; Holder, D. ; Arridge, S.



32. LRTV: MR Image Super-Resolution with Low-Rank and

Total Variation Regularizations

Shi, F. ; Cheng, J. ; Wang, L. ; Yap, P. ; Shen, D.



33. Comparison and Evaluation of Methods for Liver

Segmentation From CT Datasets

Heimann, T. ; van Ginneken, B. ; Styner, M.A. ; Arzhaeva, Y. ;

Aurich, V. ; Bauer, C. ; Beck, A. ; Becker, C. ; Beichel, R. ; Bekes,

G. ; Bello, F. ; Binnig, G. ; Bischof, H. ; Bornik, A. ; Cashman, P. ;

Ying Chi ; Cordova, A. ; Dawant, B.M. ; Fidrich, M. ; Furst, J.D. ;

Furukawa, D. ; Grenacher, L. ; Hornegger, J. ; Kainmuller, D. ;

Kitney, R.I. ; Kobatake, H. ; Lamecker, H. ; Lange, T. ; Jeongjin

Lee ; Lennon, B. ; Rui Li ; Senhu Li ; Meinzer, H.-P. ; Nemeth, G. ;

Raicu, D.S. ; Rau, A.-M. ; van Rikxoort, E.M. ; Rousson, M. ;

Rusko, L. ; Saddi, K.A. ; Schmidt, G. ; Seghers, D. ; Shimizu, A. ;

Slagmolen, P. ; Sorantin, E. ; Soza, G. ; Susomboon, R. ; Waite,

J.M. ; Wimmer, A. ; Wolf, I.




34. Retinal artery-vein classification via topology estimation

Estrada, R. ; Allingham, M. ; Mettu, P. ; Cousins, S. ; Tomasi, C. ;Farsiu, S.Publication Year: 2015 , Page(s): 1


35. FPGA-Based Voltage and Current Dual Drive System for

High Frame Rate Electrical Impedance Tomography

Khan, S. ; Manwaring, P. ; Borsic, A. ; Halter, R.Publication Year: 2015 , Page(s): 888 - 901



36. Locating the optic nerve in a retinal image using the fuzzy

convergence of the blood vessels

Hoover, A. ; Goldbaum, M.Publication Year: 2003 , Page(s): 951 - 958



37. Geodesic Information Flows: Spatially-Variant Graphs

and Their Application to Segmentation and Fusion

Cardoso, M.J. ; Modat, M. ; Wolz, R. ; Melbourne, A. ; Cash, D. ;Rueckert, D. ; Ourselin, S.Publication Year: 2015 , Page(s): 1976 - 1988


38. Localization and Segmentation of 3D Intervertebral Discs

in MR Images by Data Driven Estimation

Cheng Chen ; Belavy, D. ; Weimin Yu ; Chengwen Chu ;Armbrecht, G. ; Bansmann, M. ; Felsenberg, D. ; Guoyan ZhengPublication Year: 2015 , Page(s): 1719 - 1729


Multimedia


39. A Novel Multiple-Instance Learning-Based Approach to

Computer-Aided Detection of Tuberculosis on Chest X-Rays

Melendez, J. ; van Ginneken, B. ; Maduskar, P. ; Philipsen,R.H.H.M. ; Reither, K. ; Breuninger, M. ; Adetifa, I.M.O. ; Maane,R. ; Ayles, H. ; Sanchez, C.I.Publication Year: 2015 , Page(s): 179 - 192


40. Digital Topology and Geometry in Medical Imaging: A

Survey

Saha, P.K. ; Strand, R. ; Borgefors, G.Publication Year: 2015 , Page(s): 1940 - 1964



41. Locating blood vessels in retinal images by piecewise

threshold probing of a matched filter response

Hoover, A. ; Kouznetsova, V. ; Goldbaum, M.Publication Year: 2000 , Page(s): 203 - 210



42. Cell Detection From Redundant Candidate Regions UnderNonoverlapping Constraints

Bise, R. ; Sato, Y.



43. A Stochastic Polygons Model for Glandular Structures inColon Histology Images

Sirinukunwattana, K. ; Snead, D.R.J. ; Rajpoot, N.M.


Multimedia


44. Comb-Push Ultrasound Shear Elastography (CUSE) forEvaluation of Thyroid Nodules: Preliminary In Vivo Results

Mehrmohammadi, M. ; Pengfei Song ; Meixner, D.D. ; Fazzio, R.T.

; Shigao Chen ; Greenleaf, J.F. ; Fatemi, M. ; Alizad, A.



45. Combining Ordered Subsets and Momentum forAccelerated X-Ray CT Image Reconstruction

Donghwan Kim ; Ramani, S. ; Fessler, J.A.



Multimedia


46. Probabilistic independent component analysis forfunctional magnetic resonance imagingBeckmann, C.F. ; Smith, S.M.




47. DALSA: Domain Adaptation for Supervised Learning fromSparsely Annotated MR Images

Goetz, M. ; Weber, C. ; Binczyk, F. ; Polanska, J. ; Tarnawski, R. ;

Bobek-Billewicz, B. ; Koethe, U. ; Kleesiek, J. ; Stieltjes, B. ; Maier-

Hein, K.H.



48. Transport on Riemannian Manifold for Connectivity-basedBrain Decoding

Ng, B. ; Varoquaux, G. ; Poline, J.B. ; Greicius, M. ; Thirion, B.



49. Low-rank Atlas Image Analyses in the Presence ofPathologies

Liu, X. ; Niethammer, M. ; Kwitt, R. ; Singh, N. ; McCormick, M. ;

Aylward, S.



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50. Attenuation Correction Synthesis for Hybrid PET-MR

Scanners: Application to Brain Studies

Burgos, N. ; Cardoso, M.J. ; Thielemans, K. ; Modat, M. ;Pedemonte, S. ; Dickson, J. ; Barnes, A. ; Ahmed, R. ; Mahoney,C.J. ; Schott, J.M. ; Duncan, J.S. ; Atkinson, D. ; Arridge, S.R. ;Hutton, B.F. ; Ourselin, S.Publication Year: 2014 , Page(s): 2332 - 2341



IEEE Transactions on Medical Imaging (T-MI) encourages the submission ofmanuscripts on imaging of bodystructures, morphology and function, andimaging of microscopic biological entities.The journal publishes originalcontributions on medical imaging achievedby various modalities, such as ultrasound,X-rays (including CT) magnetic resonance,radionuclides, microwaves, and light, aswell as medical image processing andanalysis, visualization, pattern recognition,and related methods. Studies involvinghighly technical perspectives are mostwelcome. The journal focuses on a unifiedcommon ground where instrumentation,systems, components, hardware andsoftware, mathematics and physicscontribute to the studies.

Aims & Scope

Editor-in-Chief

Michael Insana

Beckman Institute for Advanced Science

and Technology

Department of Bioengineering

University of Illinois at Urbana-

Champaign

Urbana, IL 61801 USA

[email protected]

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