  The need for fast diagnostic image viewing in zero footprint web applications
and the ever increasing image sizes for new modalities such as digital
pathology have painfully brought to light that the currently available image
compression methods fall short. JPEG2000 delivers the image quality required
for medical grade viewing, but is supported on fewer than 10% of desktop web
browsers installed today (caniuse.com) and even then it does not support the
high bit depth images required by medical applications. JPEG2000's high
computational complexity and inability to do fast compression and viewing of
images undoubtedly contributed to its lack of adoption. The venerable JPEG
standard is supported in all installed web browsers today, and allows for fast
viewing and compression, but it cannot provide medical grade image quality,
lossless compression, or high bit depths. To remedy the situation medical image
web applications need to take full control of the image path by implementing
the image decompression in the application itself, instead of relying on web
browser implementations. This will give users and manufacturers the confidence
that medical images will be displayed in their full intended fidelity! This
paper introduces a simple, fast, yet efficient image compression method that
can be implemented in zero footprint web applications to provide fast medical
grade image viewing on today's web browser installed base, on the premise and
in the cloud. Due to its efficiency it is very suitable for fast and affordable
compression and viewing of very large images, and is used as such by Philips in
the iSyntax file format in use in its digital pathology products today.
