@misc{BrauckhoffRoediger, author = {Brauckhoff, Tim and R{\"o}diger, Stefan}, title = {BiopixR - extended vignette for bioimage analysis package in R}, doi = {10.5281/zenodo.12744223}, language = {en} } @misc{BrauckhoffKiefferRoediger, author = {Brauckhoff, Tim and Kieffer, Coline and R{\"o}diger, Stefan}, title = {Extracting Insights from biological images}, series = {Journal of Open Source Software}, volume = {9}, journal = {Journal of Open Source Software}, number = {102}, issn = {2475-9066}, doi = {10.21105/joss.07074}, pages = {7}, language = {en} } @misc{BrauckhoffRublackRoediger, author = {Brauckhoff, Tim and Rublack, Julius and R{\"o}diger, Stefan}, title = {Exploring image analysis in R :applications and advancements}, series = {The R journal}, volume = {17}, journal = {The R journal}, number = {3}, publisher = {The R Foundation}, address = {Frederiksberg}, issn = {2073-4859}, doi = {10.32614/rj-2025-030}, pages = {212 -- 260}, abstract = {This review offers an overview of image processing packages in R, covering applications such as multiplex imaging, cell tracking, and general-purpose tools. We found 38 R packages for image analysis, with adimpro and EBImage being the oldest, published in 2006, and biopixR among the newest, released in 2024. Of these packages, over 90 \% are still active, with two-thirds receiving updates within the last 1.5 years. The pivotal role of bioimage informatics in life sciences is emphasized in this review, along with the ongoing advancements of R's functionality through novel code releases. It focuses on complete analysis pipelines for extracting valuable information from biological images and includes real-world examples. Demonstrating how researchers can use R to tackle new scientific challenges in image analysis, the review provides a comprehensive understanding of R's utility in this field.}, language = {en} }