5-D imaging and parallel automated analysis of cellular events in living immune tissue microenvironments. - Arunachalam Narayanaswamy; Ena Ladi; Yousef Al-Kofahi; Ying Chen; Christopher D. Carothers; Ellen Robey; Badrinath Roysam (ISBI, 2010)

Robust Adaptive 3-D Segmentation of Vessel Laminae From Fluorescence Confocal Microscope Images and Parallel GPU Implementation. - Arunachalam Narayanaswamy; Saritha Dwarakapuram; Christopher Björnsson; Barbara Cutler; William Shain; Badrinath Roysam (IEEE Trans. Medical Imaging, 2010)

Novel 4-D Open-Curve Active Contour and curve completion approach for automated tree structure extraction. - Yu Wang 032; Arunachalam Narayanaswamy; Badrinath Roysam (CVPR, 2011)

The FARSIGHT Trace Editor: An Open Source Tool for 3-D Inspection and Efficient Pattern Analysis Aided Editing of Automated Neuronal Reconstructions. - Jonathan Luisi; Arunachalam Narayanaswamy; Zachary Galbreath; Badrinath Roysam (Neuroinformatics, 2011)

3-D Image Pre-processing Algorithms for Improved Automated Tracing of Neuronal Arbors. - Arunachalam Narayanaswamy; Yu Wang 032; Badrinath Roysam (Neuroinformatics, 2011)

A Broadly Applicable 3-D Neuron Tracing Method Based on Open-Curve Snake. - Yu Wang 032; Arunachalam Narayanaswamy; Chia-Ling Tsai; Badrinath Roysam (Neuroinformatics, 2011)

Multi-temporal Globally-Optimal Dense 3-D Cell Segmentation and Tracking from Multi-photon Time-Lapse Movies of Live Tissue Microenvironments. - Arunachalam Narayanaswamy; Amine Merouane; Antonio Peixoto; Ena Ladi; Paul Herzmark; Ulrich H. von Andrian; Ellen Robey; Badrinath Roysam (STIA, 2012)

Assessing microscope image focus quality with deep learning. - Samuel J. Yang; Marc Berndl; D. Michael Ando; Mariya Barch; Arunachalam Narayanaswamy; Eric Christiansen; Stephan Hoyer; Chris Roat; Jane Hung; Curtis T. Rueden; Asim Shankar; Steven Finkbeiner; et al. (BMC Bioinform., 2018)

Predicting optical coherence tomography-derived diabetic macular edema grades from fundus photographs using deep learning. - Avinash V. Varadarajan; Pinal Bavishi; Paisan Raumviboonsuk; Peranut Chotcomwongse; Subhashini Venugopalan; Arunachalam Narayanaswamy; Jorge Cuadros; Kuniyoshi Kanai; George Bresnick; Mongkol Tadarati; Sukhum Silpa-Archa; Jirawut Limwattanayingyong; et al. (CoRR, 2018)

It's easy to fool yourself: Case studies on identifying bias and confounding in bio-medical datasets. - Subhashini Venugopalan; Arunachalam Narayanaswamy; Samuel J. Yang; Anton Gerashcenko; Scott Lipnick; Nina Makhortova; James Hawrot; Christine Marques; João Pereira; Michael P. Brenner; Lee Rubin; Brian Wainger; et al. (CoRR, 2019)

Scientific Discovery by Generating Counterfactuals Using Image Translation. - Arunachalam Narayanaswamy; Subhashini Venugopalan; Dale R. Webster; Lily Peng; Gregory S. Corrado; Paisan Ruamviboonsuk; Pinal Bavishi; Michael P. Brenner; Philip C. Nelson; Avinash V. Varadarajan (MICCAI (1), 2020)

Batch equalization with a generative adversarial network. - Wesley Wei Qian; Cassandra Xia; Subhashini Venugopalan; Arunachalam Narayanaswamy; Michelle Dimon; George W. Ashdown; Jake Baum; Jian Peng 001; D. Michael Ando (Bioinform., 2020)

Scientific Discovery by Generating Counterfactuals using Image Translation. - Arunachalam Narayanaswamy; Subhashini Venugopalan; Dale R. Webster; Lily Peng; Greg Corrado; Paisan Ruamviboonsuk; Pinal Bavishi; Rory Sayres; Abigail E. Huang; Siva Balasubramanian; Michael P. Brenner; Philip Q. Nelson; et al. (CoRR, 2020)

Evolving symbolic density functionals. - He Ma; Arunachalam Narayanaswamy; Patrick Riley; Li Li (CoRR, 2022)

Preserving Product Fidelity in Large Scale Image Recontextualization with Diffusion Models. - Ishaan Malhi; Praneet Dutta; Ellie Talius; Sally Ma; Brendan Driscoll; Krista Holden; Garima Pruthi; Arunachalam Narayanaswamy (CoRR, 2025)