A deep learning framework for morphologic detail beyond the diffraction limit in infrared spectroscopic imaging. - Kianoush Falahkheirkhah; Kevin Yeh; Shachi Mittal; Luke Pfister; Rohit Bhargava (CoRR, 2019)

A generative adversarial approach to facilitate archival-quality histopathologic diagnoses from frozen tissue sections. - Kianoush Falahkheirkhah; Tao Guo; Michael Hwang; Pheroze Tamboli; Christopher G. Wood; Jose A. Karam; Kanishka Sircar; Rohit Bhargava (CoRR, 2021)

Enhancing hyperspectral imaging. - Rohit Bhargava; Kianoush Falahkheirkhah (Nat. Mach. Intell., 2021)

DRB-Net: Dilated Residual Block Network for Infrared Image Restoration. - Kianoush Falahkheirkhah; Kevin Yeh; Matthew P. Confer; Rohit Bhargava (ISVC (2), 2022)

Deepfake histological images for enhancing digital pathology. - Kianoush Falahkheirkhah; Saumya Tiwari; Kevin Yeh; Sounak Gupta; Loren Herrera-Hernandez; Michael R. McCarthy; Rafael E. Jimenez; John C. Cheville; Rohit Bhargava (CoRR, 2022)

Domain adaptation using optimal transport for invariant learning using histopathology datasets. - Kianoush Falahkheirkhah; Alex Xijie Lu; David Alvarez-Melis; Grace Huynh (MIDL, 2023)

Are We Ready for Out-of-Distribution Detection in Digital Pathology? - Ji-Hun Oh; Kianoush Falahkheirkhah; Rohit Bhargava (MICCAI (10), 2024)

Detecting Hallucinations in Virtual Histology with Neural Precursors. - Ji-Hun Oh; Kianoush Falahkheirkhah; Rohit Bhargava (CoRR, 2024)

Finer Disentanglement of Aleatoric Uncertainty Can Accelerate Chemical Histopathology Imaging. - Ji-Hun Oh; Kianoush Falahkheirkhah; Rohit Bhargava (CoRR, 2025)