Publications & Patents

Patents

1. Ghosal, S., Jacob, A. J., Sharma, P., & Gulsun, M. A. (2023). Subpopulation Based Patient Risk Prediction Using Graph Attention Networks. US Patent App. 17/647,613.
   Patent

Journal Articles

1. Sayan Ghosal, Michael C. Schatz, Archana Venkataraman, BEATRICE: Bayesian Fine-mapping from Summary Data using Deep Variational Inference.
   Under review for PLOS Genetics, 2023.
   Preprint Github

2. Sayan Ghosal, Qiang Chen, Giulio Pergola, Aaron L. Goldman, William Ulrich, Karen F. Berman, Giuseppe Blasi, Leonardo Fazio, Antonio Rampino, Alessandro Bertolino, Daniel R. Weinberger, Venkata S. Mattay, Archana Venkataraman, A generative-discriminative framework that integrates imaging, genetic, and diagnosis into coupled low dimensional space, NeuroImage, Volume 238, 2021.
   Paper

3. Sayan Ghosal, Nilanjan Ray Deep deformable registration: Enhancing accuracy by fully convolutional neural net
   Pattern Recognition Letters, 2017.
   Paper

Conference Publications

1. Sarah Wu, Archana Venkataraman, Sayan Ghosal. GIRUS-net: A Multimodal Deep Learning Model Identifying Imaging and Genetic Biomarkers Linked to Alzheimer’s Disease Severity.
   EMBC, 2023.
   Paper

2. Sayan Ghosal, Giulio Pergola, Qiang Chen, Aaron Goldman, William Ulrich, Daniel R Weinberger, Archana Venkataraman
   A Biologically Interpretable Graph Convolutional Network to Link Genetic Risk Pathways and Neuroimaging Phenotypes of Disease
   Accepted at ICLR 2022
   Preprint OpenReview

3. Akos Varga-Szemes, Teodora Chitiboi, U. Joseph Schoepf, Athira J Jacob, Sayan Ghosal, Fei Xiong, Puneet Sharma, Jonathan Aldinger, and Tilman Emrich
   Cine Image Based Cardiac Disease Classification Using Random Forest Classifier and Graph Based Deep Learning Approach
   ISMRM 2022
   Link

4. Sayan Ghosal, Qiang Chen, Giulio Pergola, Aaron L. Goldman, William Ulrich, Karen F. Berman, Giuseppe Blasi, Leonardo Fazio, Antonio Rampino, Alessandro Bertolino, Daniel R. Weinberger, Venkata S. Mattay, and Archana Venkataraman
   G-MIND: An End-to-End Multimodal Imaging-Genetics Framework for Biomarker Identification and Disease Classification
   Proc. SPIE, Medical Imaging 2021 [Selected for Special Oral Presentation, Deep Dive] - Best Paper Award.
   Preprint Slides

5. Sayan Ghosal, Qiang Chen, Aaron L. Goldman, William Ulrich, Karen F. Berman, Daniel R. Weinberger, Venkata S. Mattay, and Archana Venkataraman
   Bridging Imaging, Genetics, and Diagnosis in a Coupled Low- dimensional Framework
   MICCAI, 2019 [Acceptance Rate ≈ 30%] – Early Acceptance (Top 18% of Submissions)].
   Paper Poster

6. Sayan Ghosal, Qiang Chen, Aaron L. Goldman, William Ulrich, Daniel R. Weinberger, Venkata S. Mattay, and Archana Venkataraman
   A Generative-Predictive Framework to Capture Altered Brain Activity in fMRI and its Association with Genetic Risk: Application to Schizophrenia.
   Proc. SPIE, Medical Imaging 2019.
   Paper Poster

7. S. Ghosal, S. Banerjee, N. Tiso, E. Grisan and A. S. Chowdhury
   A novel non-rigid registration algorithm for zebrafish larval images
   EMBC, 2017.
   Paper Poster