Neuroradiology/Interventional

Research output

Research output per year 1982 1994 2000 2003 2008 2009 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2024

• 616 Article
• 77 Review article
• 21 Conference contribution
• 21 Comment/debate
• 36 More
  • 16 Letter
  • 11 Chapter
  • 6 Editorial
  • 2 Short survey
  • 1 Conference article

Research output per year

Research output per year

Search results

• A deep learning pipeline for automatic skull stripping and brain segmentation

  Yogananda, C. G. B., Wagner, B. C., Murugesan, G. K., Madhuranthakam, A. & Maldjian, J. A., Apr 2019, ISBI 2019 - 2019 IEEE International Symposium on Biomedical Imaging. IEEE Computer Society, p. 727-731 5 p. 8759465. (Proceedings - International Symposium on Biomedical Imaging; vol. 2019-April).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Cerebrospinal fluid 100%
  • Deep Learning 95%
  • Skull 68%
  • Deep learning 62%
  • Cerebrospinal Fluid 60%
  17 Scopus citations

• A machine learning pipeline for three-way classification of Alzheimer patients from structural magnetic resonance images of the brain

  Natarajan, S., Joshi, S., Saha, B. N., Edwards, A., Khot, T., Moody, E., Kersting, K., Whitlow, C. T. & Maldjian, J. A., Dec 1 2012, Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012. p. 203-208 6 p. 6406613. (Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012; vol. 1).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Magnetic resonance 100%
  • dementia 97%
  • brain 81%
  • Brain 79%
  • Magnetic resonance imaging 75%
  7 Scopus citations

• A method to investigate the size and shape variation of the lateral ventricles with age

  Urban, J. E., Maldjian, J. A., Whitlow, C. T. & Stitzel, J. D., 2012, 49th Annual Rocky Mountain Bioengineering Symposium and 49th International ISA Biomedical Sciences Instrumentation Symposium. p. 241-247 7 p. (49th Annual Rocky Mountain Bioengineering Symposium and 49th International ISA Biomedical Sciences Instrumentation Symposium).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Brain 100%
  • Magnetic resonance 41%
  • Cerebrospinal fluid 28%
  • Biomechanics 24%
  • Labels 17%
  1 Scopus citations

• A novel hierarchical level set with AR-boost for white matter lesion segmentation in diabetes

  Saha, B. N., Natarajan, S., Kota, G., Whitlow, C. T., Bowden, D., Divers, J., Freedman, B. I. & Maldjian, J. A., 2012, Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012. p. 90-95 6 p. 6406594. (Proceedings - 2012 11th International Conference on Machine Learning and Applications, ICMLA 2012; vol. 1).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Adaptive boosting 100%
  • segmentation 93%
  • Medical problems 93%
  • chronic illness 84%
  • Set theory 27%
  1 Scopus citations

• AR-Boost: Reducing overfitting by a robust data-driven regularization strategy

  Saha, B. N., Kunapuli, G., Ray, N., Maldjian, J. A. & Natarajan, S., 2013, Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Proceedings. PART 3 ed. p. 1-16 16 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 8190 LNAI, no. PART 3).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Overfitting 100%
  • Boosting 99%
  • Adaptive boosting 87%
  • Margin 84%
  • Data-driven 84%
  3 Scopus citations

• Automatic 1D convolutional neural network-based detection of artifacts in MEG acquired without electrooculography or electrocardiography

  Garg, P., Davenport, E., Murugesan, G., Wagner, B., Whitlow, C., Maldjian, J. A. & Montillo, A., Jul 14 2017, 2017 International Workshop on Pattern Recognition in Neuroimaging, PRNI 2017. Institute of Electrical and Electronics Engineers Inc., 7981506. (2017 International Workshop on Pattern Recognition in Neuroimaging, PRNI 2017).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Electrooculography 100%
  • Magnetoencephalography 93%
  • Electrocardiography 60%
  • Artifacts 60%
  • Convolutional neural networks 56%
  15 Scopus citations

• Changes in resting state MRI networks from a single season of football distinguishes controls, low, and high head impact exposure

  Murugesan, G., Famili, A., Davenport, E., Wagner, B., Urban, J., Kelley, M., Jones, D., Whitlow, C., Stitzel, J., Maldjian, J. A. & Montillo, A., Jun 15 2017, 2017 IEEE 14th International Symposium on Biomedical Imaging, ISBI 2017. IEEE Computer Society, p. 464-467 4 p. 7950561. (Proceedings - International Symposium on Biomedical Imaging).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Football 100%
  • Magnetic resonance imaging 89%
  • Sports 85%
  • Head 62%
  • Brain 42%
  4 Scopus citations

• Characterization of fluid flow properties at the basilar apex

  Shih, P., Blackburn, S., White, J. A. & Chason, D. P., 2002, Annual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings. Vol. 2. p. 1329-1330 2 p.

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Flow of fluids 100%
  • Computational fluid dynamics 84%
  • Hemodynamic 82%
  • Hemodynamics 67%
  • Shear Stress 33%

• Combining clinical neuroimaging and real-world impact data to investigate motor vehicle crash-related subarachnoid hemorrhage

  Urban, J. E., Whitlow, C. T., Maldjian, J. A., Powers, A. K. & Stitzel, J. D., Dec 1 2012, ASME 2012 Summer Bioengineering Conference, SBC 2012. p. 811-812 2 p. (ASME 2012 Summer Bioengineering Conference, SBC 2012).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

• Determining the optimal number of MEG trials: A machine learning and speech decoding perspective

  Dash, D., Ferrari, P., Malik, S., Montillo, A., Maldjian, J. A. & Wang, J., 2018, Brain Informatics - International Conference, BI 2018, Proceedings. Yang, Y., Yamamoto, V., Wang, S., Jones, E., Su, J., Mitchell, T. & Iasemidis, L. (eds.). Springer Verlag, p. 163-172 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11309 LNAI).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Magnetoencephalography 100%
  • Speech 87%
  • Decoding 72%
  • Machine Learning 72%
  • Machine learning 48%
  12 Scopus citations

• Disparity Autoencoders for Multi-class Brain Tumor Segmentation

  Bangalore Yogananda, C. G., Das, Y., Wagner, B. C., Nalawade, S. S., Reddy, D., Holcomb, J., Pinho, M. C., Fei, B., Madhuranthakam, A. J. & Maldjian, J. A., 2022, Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Revised Selected Papers. Crimi, A. & Bakas, S. (eds.). Springer Science and Business Media Deutschland GmbH, p. 116-124 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12963 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Brain Tumor 100%
  • Multi-class 80%
  • Segmentation 75%
  • Tumor 66%
  • Tumors 64%
  6 Scopus citations

• Federated Learning for Brain Tumor Segmentation Using MRI and Transformers

  Nalawade, S., Ganesh, C., Wagner, B., Reddy, D., Das, Y., Yu, F. F., Fei, B., Madhuranthakam, A. J. & Maldjian, J. A., 2022, Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Revised Selected Papers. Crimi, A. & Bakas, S. (eds.). Springer Science and Business Media Deutschland GmbH, p. 444-454 11 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12963 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Brain Tumor 100%
  • Transformer 82%
  • Segmentation 75%
  • Tumor 66%
  • Magnetic resonance imaging 65%
  5 Scopus citations

• Fully automated brain tumor segmentation and survival prediction of gliomas using deep learning and MRI

  Bangalore Yogananda, C. G., Wagner, B., Nalawade, S. S., Murugesan, G. K., Pinho, M. C., Fei, B., Madhuranthakam, A. J. & Maldjian, J. A., 2020, Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 5th International Workshop, BrainLes 2019, Held in Conjunction with MICCAI 2019, Revised Selected Papers. Crimi, A. & Bakas, S. (eds.). Springer, p. 99-112 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11993 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Brain Tumor 100%
  • Segmentation 75%
  • Tumor 66%
  • Magnetic resonance imaging 65%
  • Tumors 64%
  2 Scopus citations

• Is this good enough on expert perception of brain tumor segmentation quality

  Hoebel, K., Bridge, C. P., Ahmed, S., Akintola, O., Chung, C., Huang, R., Johnson, J., Kim, A., Ina Ly, K., Chang, K., Patel, J., Pinho, M., Batchelor, T. T., Rosen, B., Gerstner, E. & Kalpathy-Cramer, J., 2022, Medical Imaging 2022: Image Perception, Observer Performance, and Technology Assessment. Mello-Thoms, C. R., Mello-Thoms, C. R. & Taylor-Phillips, S. (eds.). SPIE, 120350P. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; vol. 12035).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Deep Learning 100%
  • Tumors 74%
  • tumors 69%
  • brain 68%
  • Brain Neoplasms 67%
  1 Scopus citations

• Multidimensional and multiresolution ensemble networks for brain tumor segmentation

  Murugesan, G. K., Nalawade, S., Ganesh, C., Wagner, B., Yu, F. F., Fei, B., Madhuranthakam, A. J. & Maldjian, J. A., 2020, Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 5th International Workshop, BrainLes 2019, Held in Conjunction with MICCAI 2019, Revised Selected Papers. Crimi, A. & Bakas, S. (eds.). Springer, p. 148-157 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 11993 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Brain Tumor 100%
  • Segmentation 75%
  • Multiresolution 74%
  • Tumor 66%
  • Tumors 64%
  5 Scopus citations

• Multidimensional and Multiresolution Ensemble Networks for Brain Tumor Segmentation

  Murugesan, G. K., Nalawade, S., Ganesh, C., Wagner, B., Yu, F. F., Fei, B., Madhuranthakam, A. J. & Maldjian, J. A., 2021, Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries - 6th International Workshop, BrainLes 2020, Held in Conjunction with MICCAI 2020, Revised Selected Papers. Crimi, A. & Bakas, S. (eds.). Springer Science and Business Media Deutschland GmbH, p. 448-457 10 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12658 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Brain Tumor 100%
  • Segmentation 75%
  • Multiresolution 74%
  • Tumor 66%
  • Tumors 64%
  1 Scopus citations

• Quantifying the association between white matter integrity changes and subconcussive head impact exposure from a single season of youth and high school football using 3D convolutional neural networks

  Saghafi, B., Murugesan, G., Davenport, E., Wagner, B., Urban, J., Kelley, M., Jones, D., Powers, A., Whitlow, C., Stitzel, J., Maldjian, J. A. & Montillo, A., 2018, Medical Imaging 2018: Computer-Aided Diagnosis. Mori, K. & Petrick, N. (eds.). SPIE, 105750E. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; vol. 10575).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Football 100%
  • integrity 90%
  • Anisotropy 79%
  • White Matter 77%
  • Convolutional neural networks 77%
  6 Scopus citations

• Quantifying the impact of type 2 diabetes on brain perfusion using deep neural networks

  Saghafi, B., Garg, P., Wagner, B. C., Smith, S. C., Xu, J., Madhuranthakam, A. J., Jung, Y., Divers, J., Freedman, B. I., Maldjian, J. A. & Montillo, A., 2017, Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support - 3rd International Workshop, DLMIA 2017 and 7th International Workshop, ML-CDS 2017 Held in Conjunction with MICCAI 2017, Proceedings. Arbel, T. & Cardoso, M. J. (eds.). Springer Verlag, p. 151-159 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10553 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Diabetes 100%
  • Medical problems 81%
  • Brain 80%
  • Deep neural networks 71%
  • Neural Networks 69%

• Radiographic-deformation and textural heterogeneity (r-DepTH): An integrated descriptor for brain tumor prognosis

  Prasanna, P., Mitra, J., Beig, N., Partovi, S., Singh, G., Pinho, M., Madabhushi, A. & Tiwari, P., 2017, Medical Image Computing and Computer Assisted Intervention − MICCAI 2017 - 20th International Conference, Proceedings. Jannin, P., Duchesne, S., Descoteaux, M., Franz, A., Collins, D. L. & Maier-Hein, L. (eds.). Springer Verlag, p. 459-467 9 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10434 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Brain Tumor 100%
  • Prognosis 87%
  • Descriptors 73%
  • Tumor 66%
  • Tumors 64%
  7 Scopus citations

• Single season changes in resting state network power and the connectivity between regions distinguish head impact exposure level in high school and youth football players

  Murugesan, G., Saghafi, B., Davenport, E., Wagner, B., Urban, J., Kelley, M., Jones, D., Powers, A., Whitlow, C., Stitzel, J., Maldjian, J. A. & Montillo, A., 2018, Medical Imaging 2018: Computer-Aided Diagnosis. Mori, K. & Petrick, N. (eds.). SPIE, 105750F. (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; vol. 10575).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  Open Access

  • Classifier 100%
  • Football 85%
  • Brain 60%
  • Head 53%
  • brain 46%
  7 Scopus citations

• Using convolutional neural networks to automatically detect eye-blink artifacts in magnetoencephalography without resorting to electrooculography

  Garg, P., Davenport, E., Murugesan, G., Wagner, B., Whitlow, C., Maldjian, J. A. & Montillo, A., 2017, Medical Image Computing and Computer Assisted Intervention − MICCAI 2017 - 20th International Conference, Proceedings. Maier-Hein, L., Franz, A., Jannin, P., Duchesne, S., Descoteaux, M. & Collins, D. L. (eds.). Springer Verlag, p. 374-381 8 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10435 LNCS).

  Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

  • Electrooculography 100%
  • Magnetoencephalography 93%
  • Independent component analysis 68%
  • Independent Component Analysis 63%
  • Neural Networks 58%
  10 Scopus citations