JOURNAL ARTICLES:
PEER REVIEWED CONFERENCE PUBLICATIONS
CONFERENCE ABSTRACTS
- N.S. D’Souza, M.B. Nebel, D. Crocetti, N. Wymbs, J.Robinson, S. Mostofsky and A. Venkataraman.“Deep sr-DDL: Deep Structurally Regularized Dynamic Dictionary Learning to Integrate Multimodal and Dynamic Functional Connectomics data for Multidimensional Clinical Characterizations”, in Prep NeuroImage, 2020
- N.S. D’Souza, N. Wymbs, M.B. Nebel, S. Mostofsky and A. Venkataraman. “A Joint Network Optimization Framework to Predict Clinical Severity from Resting State fMRI Data” In Proceedings, NeuroImage, 2020
PEER REVIEWED CONFERENCE PUBLICATIONS
- N.S. D’Souza, M.B. Nebel, D. Crocetti, N. Wymbs, J. Robinson, S. Mostofsky and A. Venkataraman. “A Deep-Generative Hybrid Model to Integrate Multimodal and Dynamic Connectivity for Predicting Spectrum-Level Deficits in Autism”. In Proc. MICCAI: Medical Imaging Computing and Computer Assisted Interventions, 2020
- N. Nandakumar, N.S. D’Souza, K. Manzoor, J. Pillai, S. Gujar, H. Sair and A. Venkataraman, “A Multi-Task Deep Learning Framework to Localize the Eloquent Cortex in Brain Tumor Patients Using Dynamic Functional Connectivity ” In proc. MLCN, 3rd Intl. Workshop on Machine Learning in Clinical Neuroimaging, 2020 (Best Paper Award)
- N.S. D’Souza, N. Wymbs, M.B. Nebel, S. Mostofsky and A. Venkataraman. “Integrating Neural Networks and Dictionary Learning for Multidimensional Clinical Characterizations from Functional Connectomics Data”. In Proc. MICCAI: Medical Imaging Computing and Computer Assisted Interventions, 2019
- N.S. D’Souza, N. Wymbs, M.B. Nebel, S. Mostofsky and A. Venkataraman. “A Coupled Manifold Optimization Framework to Jointly Model the Functional Connectomics and Behavioral Data Spaces.” In Proc. IPMI: Information Processing in Medical Imaging, 2019
- N.S. D’Souza, N. Wymbs, M.B. Nebel, S. Mostofsky and A. Venkataraman. “ A Generative Discriminative Basis Learning Framework to Predict Clinical Severity from Resting State Functional MRI Data.” In Proc. MICCAI: International Conference on Medical Image Computing and Computer Assisted Interventions, 2018
- N. Nandakumar, N. S. D’Souza, J. Craley, K. Manzoor, J. J. Pillai, S. K. Gujar, H. I. Sair, and A. Venkataraman “Defining Patient Specific Functional Parcellations in Lesional Cohorts via Markov Random Fields” In Proc: MICCAI Workshop on Connectomics in NeuroImaging, 2018. (Selected for Oral Presentation)
CONFERENCE ABSTRACTS
- N.S. D’Souza, M.B. Nebel, N. Wymbs, S. Mostofsky, A. Venkataraman. “A Joint Network Optimization Framework to Predict Clinical Severity from Resting-State Functional MRI Data”. In Proc. Conference on Medical Imaging and Case Reports, 2019 (Invited Talk)
- A. Venkataraman, N.S. D’Souza, M.B. Nebel, N. Wymbs, S. Mostofsky. “Predicting Behavior from Resting-State fMRI”. In Proc. SAND9: Statistical Analysis of Neuronal Data, 2019.
- N.S. D’Souza, M.B. Nebel, N. Wymbs, S. Mostofsky, A. Venkataraman “A Joint Network Optimization to Predict Clinical Severity from Resting-State Functional Connectomics” In Proc. Flux Congress, 2019
- N.S. D’Souza, M.B. Nebel, N. Wymbs, S. Mostofsky, A. Venkataraman “A Generative-Discriminative Basis Learning Framework to Predict Autism Spectrum Disorder Severity”. In Proc. ISBI: International Symposium on Biomedical Imaging, 2018.
- N. Nandakumar, N.S. D’Souza, H. Sair, A. Venkataraman. “A Modified K-Means Algorithm for Resting State FMRI Analysis of Brain Tumor Patients, As Validated by Language Localization”. In Proc. ISBI: International Symposium on Biomedical Imaging, 2018
- N.S. D’Souza, R. Sathish, A. Shahpurwala, R.K. Das, J Chatterjee, A Guha Roy, D. Sheet, “Deblurring of Fluorescence Microscopy Images using Domain Adaptive Self-Taught Autoencoders” In Proc. ISBI: International Symposium on Biomedical Imaging, 2016