Seems very similar to how maps work on the web these days, in particular protomap files [0]. I wonder if you could view the medical images in leaflet or another frontend map library with the addition of a shim layer? Cool work!
Interesting - I'm not so familiar with S3 but I wonder if this would work for WSI stored on-premises. Imposing lower network requirememts and a lightweight web viewer is very advantageous in this use case. I'll have to try it out!
Interesting guide to the Whole Slide Images (WSI) format. The surprising thing for me is that compression is used, and they note does not affect use in diagnostics.
Back in the day we used TIFF for a similar application (X-ray detector images).
You could probably do it completely clientside. I have a parser for 12 scanner formats in js. It doesnt read the pixels, just parses metadata but jpeg is easy and most common anyway
Maybe a bit pedantic, but if you're streaming it, then you're still downloading portions of it, yah? Just not persisting the whole thing locally before viewing it.
Edit: Looks like this is a slight discrepancy between the HN title and the GitHub description.
The generalized form of this range-request-based streaming approach looks something like my project VirtualiZarr [0].
Many of these scientific file formats (HDF5, netCDF, TIFF/COG, FITS, GRIB, JPEG and more) are essentially just contiguous multidimensional array(/"tensor") chunks embedded alongside metadata about what's in the chunks. Efficiently fetching these from object storage is just about efficiently fetching the metadata up front so you know where the chunks you want are [1].
The data model of Zarr [2] generalizes this pattern pretty well, so that when backed by Icechunk [3], you can store a "datacube" of "virtual chunk references" that point at chunks anywhere inside the original files on S3.
This allows you to stream data out as fast as the S3 network connection allows [4], and then you're free to pull that directly, or build tile servers on top of it [5].
In the Pangeo project and at Earthmover we do all this for Weather and Climate science data. But the underlying OSS stack is domain-agnostic, so works for all sorts of multidimensional array data, and VirtualiZarr has a plugin system for parsing different scientific file formats.
I would love to see if someone could create a virtual Zarr store pointing at this WSI data!
> Many of these scientific file formats (HDF5, netCDF, TIFF/COG, FITS, GRIB, JPEG and more) are essentially just contiguous multidimensional array(/"tensor") chunks
Yeah, a recurring thought is that these should condense into Apache Arrow queried by DuckDB but there must be some reason for this not to have already happened.
A while back I worked on a project where s3 held giant zip files containing zip files (turtles all the way down) and also made good use of range requests. I came up with seekable-s3-stream[1] to generalize working with them via an idiomatic C# stream.
I did something similar once for a mining technique called “core logging”. It’s a single photo about 1000 pixels wide and several million “deep”: what the earth looks like for a few km down.
Existing solutions are all complicated and clunky, I put something together with S3 and bastardised CoGeoTIFF, instant view of any part of the image.
I'm curious about the "core logging" photo. Where can I find one? Do you have an implementation of your solution? I would be curious to have a look at it.
I don't know enough about the science side to take it any further on my own.
The "tech" part of what I started building is really quite simple: convert the images to Cloud-optimised GeoTIFF, then do range requests to S3 from the browser.
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[ 3.0 ms ] story [ 39.3 ms ] thread0: https://protomaps.com/
Interesting guide to the Whole Slide Images (WSI) format. The surprising thing for me is that compression is used, and they note does not affect use in diagnostics.
Back in the day we used TIFF for a similar application (X-ray detector images).
Was there a requirement to work with these formats directly without converting?
Edit: Looks like this is a slight discrepancy between the HN title and the GitHub description.
Many of these scientific file formats (HDF5, netCDF, TIFF/COG, FITS, GRIB, JPEG and more) are essentially just contiguous multidimensional array(/"tensor") chunks embedded alongside metadata about what's in the chunks. Efficiently fetching these from object storage is just about efficiently fetching the metadata up front so you know where the chunks you want are [1].
The data model of Zarr [2] generalizes this pattern pretty well, so that when backed by Icechunk [3], you can store a "datacube" of "virtual chunk references" that point at chunks anywhere inside the original files on S3.
This allows you to stream data out as fast as the S3 network connection allows [4], and then you're free to pull that directly, or build tile servers on top of it [5].
In the Pangeo project and at Earthmover we do all this for Weather and Climate science data. But the underlying OSS stack is domain-agnostic, so works for all sorts of multidimensional array data, and VirtualiZarr has a plugin system for parsing different scientific file formats.
I would love to see if someone could create a virtual Zarr store pointing at this WSI data!
[0]: https://virtualizarr.readthedocs.io/en/stable/
[1]: https://earthmover.io/blog/fundamentals-what-is-cloud-optimi...
[2]: https://earthmover.io/blog/what-is-zarr
[3]: https://earthmover.io/blog/icechunk-1-0-production-grade-clo...
[4]: https://earthmover.io/blog/i-o-maxing-tensors-in-the-cloud
[5]: https://earthmover.io/blog/announcing-flux
Yeah, a recurring thought is that these should condense into Apache Arrow queried by DuckDB but there must be some reason for this not to have already happened.
[1] https://github.com/mlhpdx/seekable-s3-stream
Existing solutions are all complicated and clunky, I put something together with S3 and bastardised CoGeoTIFF, instant view of any part of the image.
Wish I knew how to commercialise it…
These are some of the existing commercial solutions (just found these on Google, can't remember which I was comparing my own work against):
- https://koregeosystems.com/digital-core-logging/
- https://mountsopris.com/wellcad/core-logging-software/
- https://www.geologicai.com/logging/
I don't know enough about the science side to take it any further on my own.
The "tech" part of what I started building is really quite simple: convert the images to Cloud-optimised GeoTIFF, then do range requests to S3 from the browser.
You've already done the "building v1" part, and have started to do the "talking about it" part.
Next step is to write up how one could use it, how it is better than the alternatives, and put it up on a website.
I'm happy to chat about it if you like. My email is in my profile.
Once you have real users, they will pull the v2 out of you, and that will be what you'll sell.
What I've written above sounds like a business proposition, but I want to clarify that I'm just offering to share what I know for free :-)