Deepti R. Bathula

Deepti R. Bathula

Associate Professor Department of Computer Science & Engineering

Journal Publications

  • A. Sikka, S. V. Peri, J. S. Virk, D. R. Bathula, MRI to PET Cross-Modality Translation using Globally and Locally Aware GAN (GLA-GAN) for Multi-Modal Diagnosis of Alzheimer’s Disease. Submitted to Computers in Biology & Medicine (arXiv preprint arXiv:2108.02160)
  • U. Niyaz, D. R. Bathula, Leveraging Different Learning Styles for Improved Knowledge Distillation, Computers in Biology & Medicine, 168, 2024.
  • A. S. Sambyal, U. Niyaz, N. C. Krishnan, D. R. Bathula, Understanding Calibration of Deep Neural Networks for Medical Image Classification, Computer Methods and Programs in Biomedicine, 242, 2023.
  • S. Gallo, A. ElGazzar, P. Zhutovsky, R. M. Thomas, N. Javaheripour, M. Li, D. R. Bathula, G. van Wingen, Thalamic hyperconnectivity as neurophysiological signature of major depressive disorder in two multicenter studies. Molecular Psychiatry, 2023.
  • S. Bagchi, D. R. Bathula, EEG-ConvTransformer for Single-Trial EEG based Visual Stimuli Classification. Pattern Recognition, 129, 2022.
  • S. Andersson, D. R. Bathula, S. I Iliadis, M. Walter, A. Skalkidou, Predicting women with depressive symptoms postpartum with machine learning methods. Scientific Reports, 11 (1), 1-15, April 2021.
  • A. Sikka, H. Jamalabadi, M. Krylova, S. Alizadeh, J. N. van der Meer, L. Danyeli, M. Deliano, P. Vicheva, T. Hahn, T. Koenig, D. R. Bathula, M. Walter, Investigating the temporal dynamics of electroencephalogram (EEG) microstates using recurrent neural networks. Human Brain Mapping, February 2020, Article 24949.
  • J. I. Orlando, H. Fu, J. B. Breda, K. Keer, D. R. Bathula, A. Diaz-Pinto, R. Fang, P. Heng, J. Kim, J. Lee, J. Lee, X. Li, P. Liu, S. Lu, B. Murugesan, V. Naranjo, S. R. Phaye, S. M. Shankaranarayana, H. Bogunovic, A. Sikka, REFUGE Challenge: A unified framework for evaluating automated methods for glaucoma assessment from fundus photographs}. Medical Image Analysis, Volume 59, January 2020, Article 101570.
  • D. A. Fair, J. T. Nigg, S. Iyer, D. R. Bathula, K. L. Mills, N. U. F. Dosenbach, B. L. Schlaggar, M. Mennes, D. Gutman, S. Bangaru, J. K. Buitelaar, D. P. Dickstein, A. D. Martino, D. N. Kennedy, C. Kelly, B. Luna, J. Schweitzer, K. Velanova, Y. Wang, S. H. Mostofsky, F. X. Castellanos, M. Milham,”Distinct neural signatures detected for ADHD subtypes after controlling for micro-movements in resting state functional connectivity MRI data,” Frontiers in Systems Neuroscience, 6:80, Feb 2013
  • T. G. Costa Dias, V. B. Wilson, D. R. Bathula, S. P. Iyer, K. L. Mills, B. L. Thurlow, C. A. Stevens, E. D. Musser, S. D. Carpenter, D. S. Grayson, S. H. Mitchell, J. T. Nigg, D. A. Fair, “Reward circuit connectivity relates to delay discounting in children with attention-deficit/hyperactivity disorder,” European Neuropsychopharmacology, 23(1):33-45, Jan 2013
  • D. A. Fair, D. R. Bathula, M. A. Nikolas, J. T. Nigg, “Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD,” Proceedings of the National Academy of Sciences USA, 109(17):6769-74, April 2012.
  • K. L. Mills, D. R. Bathula, T. G. Costa Dias, S. P. Iyer, M. C. Fenesy, E. D. Musser, C. A. Stevens, B. L. Thurlow, S. D. Carpenter, B. J. Nagel, J. T. Nigg, D. A. Fair, “Altered cortico-striatal-thalamic connectivity in relation to spatial working memory capacity in children with ADHD,” Frontiers in Psychiatry, 3:2, Jan 2012.
  • B. J. Nagel, D. R. Bathula, M. Herting, C. Schmitt, C. D. Kroenke, D. A. Fair, J. T. Nigg, “Altered White Matter Microstructure in Children with ADHD”, Journal of the American Academy of Child and Adolescent Psychiatry, 50(3), pp. 283-292, Mar 2011.
  • D. A. Fair, J. Posner, B. J. Nagel, D. R. Bathula, T. G. Costa Dias, K. L. Mills, M. S. Blythe, A. Giwa, C. F. Schmitt, J. T. Nigg, “Atypical Default Network Connectivity in Youth with ADHD”, Biological Psychiatry, 68(12), pp. 1084-1091, 2011.
  • D. A. Fair, D. R. Bathula, K. L. Mills, T. G. Costa Dias, M. S. Blythe, D. Zhang, A. Z. Snyder, M. E. Raichle, A. A. Stevens, J. T. Nigg, B. J. Nagel, “Maturing thalamocortical functional connectivity across development”, Frontiers in Systems Neuroscience, 4:10, May 2010.

Peer-Reviewed Conference Publications

  • A. S. Sambyal, U. Niyaz, N. C. Krishnan, D. R. Bathula, “LS+: Informed Label Smoothing for Improving Calibration in Medical Image Classification”, Medical Image Computing and Computer Assisted Interventions (MICCAI), Oct 2024.
  • U. Niyaz, A. S. Sambyal, D. R. Bathula, “Wavelet-Based Feature Compression for Improved Knowledge Distillation”, IEEE 21st Int. Sym. on Biomedical Imaging (ISBI), May 2024.
  • A. Chaudhuri, A. S. Sambyal, D. R. Bathula, “Mutually Exclusive Multi-Modal Approach for Parkinson’s Disease Classification”, 11th International Conference on Bioimging, February 2024.
  • J. S. Virk, D. Mahapatra, D. R. Bathula, “Medical VQA: MixUp Helps Keep it Simple”, The 37th International Conference on Image and Vision Computing New Zealand (IVCNZ), November 2022.
  • U. Niyaz, D. R. Bathula, “Augmenting Knowledge Distillation With Peer-To-Peer Mutual Learning For Model Compression”, IEEE 19th Int. Sym. on Biomedical Imaging (ISBI), March 2022.
  • A. S. Sambyal, N. C. Krishnan, D. R. Bathula, “Towards Reducing Aleatoric Uncertainty for Medical Imaging Tasks”, IEEE 19th Int. Sym. on Biomedical Imaging (ISBI), March 2022.
  • R. R. Chowdhury, D. R. Bathula, “Influential Prototypical Networks for Few Shot Learning: A Dermatological Case Study”, IEEE 19th Int. Sym. on Biomedical Imaging (ISBI), March 2022.
  • A. J. Thomas, D. R. Bathula, “3D Multi-voxel pattern based machine learning for multi-center fMRI data normalization”, 6th IAPR International Conference on Computer Vision & Image Processing (CVIP), December 2021.
  • S. Bagchi, D. R. Bathula, “Adequately Wide 1D CNN facilitates improved EEG based Visual Object Recognition”, 29th European Signal Processing Conference (EUSIPCO), 1276-1280, August 2021.
  • J. S. Virk, D. R. Bathula, “Domain-Specific, Semi-Supervised Transfer Learning for Medical Imaging”, ACM International Joint Conference on Data Science and Management of Data (CODS-COMAD), January 2021
  • S. Bagchi, A. Banerjee, D. R. Bathula, “Learning a meta-ensemble technique for skin lesion classification and novel class detection”, IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, June 2020.
  • A. Sikka, S. S. R. Phaye, A. Dhall, D. R. Bathula, “Multi-level Dense Capsule Networks”, Asian Conference on Computer Vision (ACCV), December 2018.
  • A. Sikka, S. V. Peri, Dr. R. Bathula, “MRI to FDG-PET: Cross-Modal Synthesis Using 3D U-Net For Multi-Modal Alzheimer’s Classification”, Medical Image Computing and Computer Assisted Intervention (MICCAI) – Simulation and Synthesis in Medical Imaging (SASHIMI) Workshop, September 2018, Spain.
  • A. Sikka, G. Mittal, D. R. Bathula, N. C. Krishnan, “Supervised deep segmentation network for brain extraction,” Proceedings of the Tenth Indian Conference on Computer Vision, Graphics and Image Processing (ICVGIP), Dec 18-22 2016, Guwahati, Assam, India.
  • G. Bansal, P. Gera and D. R. Bathula, “Template based Classification of Cardiac Arrhythmia in ECG Data”, IEEE International Conference on Recent Trends in Information Systems (ReTIS-15), Jul 9 -11, 2015, Jadavpur University, Kolkata, India.
  • A. J. Thomas and D. R. Bathula, “Reducing Inter-Scanner Variability in Multi-Site FMRI Activations Using Correction Functions: A Preliminary Study”, IEEE International Conference on Computing, Communication and Automation (ICCCA), May 15 – 16, 2015, Galgotias University, Uttar Pradesh, India.
  • A. J. Thomas and D. R. Bathula, “Reducing inter-scanner variability in multi-site fMRI data: Exploring choice of reference activation map and use of correction functions”, IEEE SPS-APSIPA Winter Workshop on Machine Intelligence and Signal Processing (MISP), Dec 20 – 23, 2014, IIIT Delhi, New Delhi, India.
  • D. R. Bathula, L. H. Staib, H. D. Tagare, X. Papademetris, R. T. Schultz and J. S. Duncan, “Multi- Group Functional MRI Analysis Using Statistical Activation Priors,” Medical Image Computing and Computer Assisted Intervention (MICCAI) – fMRI Analysis Workshop, September 2009, London.
  • D. R. Bathula, H. D. Tagare, L. H. Staib, X. Papademetris, R. T. Schultz and J. S. Duncan, “Bayesian Analysis of fMRI Data with ICA Based Spatial Prior,” Medical Image Computing and Computer Assisted Intervention (MICCAI), Part II: 246 – 254, September 2008, New York.
  • D. R. Bathula, X. Papademetris and J. S. Duncan, “Level Set-Based Clustering of Active Regions in Functional MRI,” IEEE Int. Sym. on Biomedical Imaging (ISBI), 416 – 419, April 2007, Arlington.

Extended Abstracts-Posters

  • P. Madaan, D. R. Bathula, P. Dhir, S. Negi, N. Sankhyan, S. Vyas, J. Sahu, “Resting-state functional MRI-based connectivity analysis in infantile epileptic spasms syndrome”, International Child Neurology Conference (ICNC), May 2024, Cape Town, South Africa.
  • A. Bilal, D. R. Bathula, E. Bränn, E. Fransson, J. S. Virk, F. Papadopoulos, A. Skalkidou, “Mom2B: a study of perinatal health via smartphone application and machine learning methods”, 65(S1), S574-S575, European Psychiatry, 2022.
  • M. Li, N. Sharma, L. Danyeli, L. Colic, N. Opel, T. Chand, W. Qin, D. R. Bathula, M. Goswami, B. Zhang, Z. Duygu Sen, M. Walter, “Ketamine-Induced Ego Dissolution is Related to the Functional Connectivity Reconfiguration of the Posteromedial Cortex”, 93(9), S93, Biological Psychiatry, 2023
  • H. Jamalabadi, A. Sikka, S. Alizadeh, M. Krylova, J. Van der Meer, D. R. Bathula, M. Walter, “Deep networks can learn subject-invariant electroencephalography microstate sequences”, Organization for Human Brain Mapping (OHBM), June 2018, Singapore.
  • K. L. Mills, D. R. Bathula, et. al. “Altered cortico-striatal-thalamic connectivity in relation to spatial working memory capacity in children with ADHD”, Neuroscience (SFN), November 2011, Washington, DC.
  • D. A. Fair, D. R. Bathula, Joel Nigg, et. al. “Using resting-state fcMRI to characterize the developmental course of subjects with ADHD”, Human Brain Mapping (HBM), June 2011, Québec City, Canada.
  • T. Costa Dias, E. Musser, V. Wilson, D. R. Bathula, et. al. “Reward circuit connectivity relates to delay discounting in children with ADHD”, Human Brain Mapping (HBM), June 2011, Québec City, Canada.
  • K. L. Mills T. Costa Dias,, M. S. Blythe, D. R. Bathula, et. al. “Atypical thalamocortical connectivity in ADHD youth”, Neuroscience (SFN), November 2010, Washington, DC.
  • D. R. Bathula, D. A. Fair, K. L. Mills T. Costa Dias,, M. S. Blythe, J. T. Nigg, B. J. Nagel, “Differential relations between functional and structural thalamocortical connectivity across development,” Neuroscience (SFN), November 2010, Washington, DC.
  • D. R. Bathula, X. Papademetris and J. S. Duncan, “Anatomically-Informed Clustering of Functional MRI Data”, Proc. of the Biomedical Engineering Society Annual Fall Meeting (BMES), October 2006, Chicago.