Feb. 6, 2024, 5:47 a.m. | Vincent Roca Gr\'egory Kuchcinski Jean-Pierre Pruvo Dorian Manouvriez Renaud Lopes

cs.LG updates on arXiv.org arxiv.org

In MRI studies, the aggregation of imaging data from multiple acquisition sites enhances sample size but may introduce site-related variabilities that hinder consistency in subsequent analyses. Deep learning methods for image translation have emerged as a solution for harmonizing MR images across sites. In this study, we introduce IGUANe (Image Generation with Unified Adversarial Networks), an original 3D model that leverages the strengths of domain translation and straightforward application of style transfer methods for multicenter brain MR image harmonization. IGUANe …

acquisition aggregation brain cs.ai cs.cv cs.lg cyclegan data deep learning hinder image images imaging mri multiple sample solution studies study translation

Senior Machine Learning Engineer

@ GPTZero | Toronto, Canada

ML/AI Engineer / NLP Expert - Custom LLM Development (x/f/m)

@ HelloBetter | Remote

Doctoral Researcher (m/f/div) in Automated Processing of Bioimages

@ Leibniz Institute for Natural Product Research and Infection Biology (Leibniz-HKI) | Jena

Seeking Developers and Engineers for AI T-Shirt Generator Project

@ Chevon Hicks | Remote

Principal Data Architect - Azure & Big Data

@ MGM Resorts International | Home Office - US, NV

GN SONG MT Market Research Data Analyst 11

@ Accenture | Bengaluru, BDC7A