  In the past decade, enormous progress has been made in advancing the
state-of-the-art in bioimage analysis - a young computational field that works
in close collaboration with the life sciences on the quantitative analysis of
scientific image data. In many cases, tremendous effort has been spent to
package these new advances into usable software tools and, as a result, users
can nowadays routinely apply cutting-edge methods to their analysis problems
using software tools such as ilastik [1], cellprofiler [2], Fiji/ImageJ2 [3,4]
and its many modern plugins that build on the BigDataViewer ecosystem [5], and
many others. Such software tools have now become part of a critical
infrastructure for science [6]. Unfortunately, overshadowed by the few
exceptions that have had long-lasting impact, many other potentially useful
tools fail to find their way into the hands of users. While there are many
reasons for this, we believe that at least some of the underlying problems,
which we discuss in more detail below, can be mitigated. In this opinion piece,
we specifically argue that embedding teams of research software engineers
(RSEs) within imaging and image analysis core facilities would be a major step
towards sustainable bioimage analysis software.
