Medical Image Harmonization Using Deep Learning Based Canonical Mapping: Toward Robust and Generalizable Learning in Imaging. - Vishnu M. Bashyam; Jimit Doshi; Güray Erus; Dhivya Srinivasan; Ahmed Abdulkadir; Mohamad Habes; Yong Fan 001; Colin L. Masters; Paul Maruff; Chuanjun Zhuo; Henry Völzke; Sterling C. Johnson; et al. (CoRR, 2020)

Harmonization of large MRI datasets for the analysis of brain imaging patterns throughout the lifespan. - Raymond Pomponio; Güray Erus; Mohamad Habes; Jimit Doshi; Dhivya Srinivasan; Elizabeth Mamourian; Vishnu Bashyam; Ilya M. Nasrallah; Theodore D. Satterthwaite; Yong Fan 001; Lenore J. Launer; Colin L. Masters; et al. (NeuroImage, 2020)

GaNDLF: A Generally Nuanced Deep Learning Framework for Scalable End-to-End Clinical Workflows in Medical Imaging. - Sarthak Pati; Siddhesh P. Thakur; Megh Bhalerao; Ujjwal Baid; Caleb M. Grenko; Brandon Edwards; Micah J. Sheller; Jose Agraz; Bhakti Baheti; Vishnu Bashyam; Parth Sharma; Babak Haghighi; et al. (CoRR, 2021)

Applications of generative adversarial networks in neuroimaging and clinical neuroscience. - Rongguang Wang; Vishnu Bashyam; Zhijian Yang; Fanyang Yu; Vasiliki Tassopoulou; Sai Spandana Chintapalli; Ioanna Skampardoni; Lasya P. Sreepada; Dushyant Sahoo; Konstantina S. Nikita; Ahmed Abdulkadir; Junhao Wen 002; et al. (NeuroImage, 2023)

Image harmonization: A review of statistical and deep learning methods for removing batch effects and evaluation metrics for effective harmonization. - Fengling Hu; Andrew A. Chen; Hannah Horng; Vishnu Bashyam; Christos Davatzikos; Aaron Alexander-Bloch; Mingyao Li; Haochang Shou; Theodore D. Satterthwaite; Meichen Yu; Russell T. Shinohara (NeuroImage, 2023)