HMS Image Analysis Collaboratory

@hms-iac.bsky.social

News from the Image Analysis Collaboratory at Harvard Medical School. Teaching, research and promoting best practices in Bioimage Analysis. Get in touch: https://iac.hms.harvard.edu/.

๐Ÿ“ฃย We are accepting applications for the 2026 Boston Bioimage Analysis Course (BoBiAC): bobiac.github.io! Join us this July at Harvard Medical School for aย 6-day intensive hands-on courseย to learn bioimage analysis with Python! Apply by May 18th! No prior Python experience required! ๐Ÿงซ->๐Ÿ”ฌ->๐Ÿ’ป->๐Ÿ“Š

Bild

๐ŸŽ€โœจRecording now available โœจ๐ŸŽ€ youtu.be/jtDunWK8g1o?...

Talley Lambert (PhD): Simulating realistic light microscopy images using microsim

YouTube video by IAC HMS

youtu.be

HMS Image Analysis Collaboratory@hms-iac.bsky.social ยท last yr.

We are proudly hosting ๐ƒ๐ซ. ๐“๐š๐ฅ๐ฅ๐ž๐ฒ ๐‹๐š๐ฆ๐›๐ž๐ซ๐ญ @talley.codes (CITE, Harvard Medical School): ๐’๐ข๐ฆ๐ฎ๐ฅ๐š๐ญ๐ข๐ง๐  ๐ซ๐ž๐š๐ฅ๐ข๐ฌ๐ญ๐ข๐œ ๐ฅ๐ข๐ ๐ก๐ญ ๐ฆ๐ข๐œ๐ซ๐จ๐ฌ๐œ๐จ๐ฉ๐ฒ ๐ข๐ฆ๐š๐ ๐ž๐ฌ ๐ฎ๐ฌ๐ข๐ง๐  ๐ฆ๐ข๐œ๐ซ๐จ๐ฌ๐ข๐ฆ When: ๐Œ๐š๐ฒ ๐Ÿ๐Ÿ—๐ญ๐ก @ ๐Ÿ๐Ÿ ๐š๐ฆ ๐„๐ƒ๐“ (Boston time) Join us on Zoom! harvard.zoom.us/j/9762343464...

We are proudly hosting ๐ƒ๐ซ. ๐“๐š๐ฅ๐ฅ๐ž๐ฒ ๐‹๐š๐ฆ๐›๐ž๐ซ๐ญ @talley.codes (CITE, Harvard Medical School): ๐’๐ข๐ฆ๐ฎ๐ฅ๐š๐ญ๐ข๐ง๐  ๐ซ๐ž๐š๐ฅ๐ข๐ฌ๐ญ๐ข๐œ ๐ฅ๐ข๐ ๐ก๐ญ ๐ฆ๐ข๐œ๐ซ๐จ๐ฌ๐œ๐จ๐ฉ๐ฒ ๐ข๐ฆ๐š๐ ๐ž๐ฌ ๐ฎ๐ฌ๐ข๐ง๐  ๐ฆ๐ข๐œ๐ซ๐จ๐ฌ๐ข๐ฆ When: ๐Œ๐š๐ฒ ๐Ÿ๐Ÿ—๐ญ๐ก @ ๐Ÿ๐Ÿ ๐š๐ฆ ๐„๐ƒ๐“ (Boston time) Join us on Zoom! harvard.zoom.us/j/9762343464...

Bild

โœจWe are proudly hosting ๐๐ซ๐จ๐Ÿ. ๐’๐ข๐ฑ๐ข๐š๐ง ๐˜๐จ๐ฎ (MIT)โœจ โ€œ๐‚๐จ๐ฆ๐ฉ๐ฎ๐ญ๐š๐ญ๐ข๐จ๐ง๐š๐ฅ ๐š๐ฑ๐ข๐š๐ฅ ๐๐ž๐›๐ฅ๐ฎ๐ซ๐ซ๐ข๐ง๐  ๐Ÿ๐จ๐ซ ๐ข๐ฌ๐จ๐ญ๐ซ๐จ๐ฉ๐ข๐œ ๐Ÿ‘๐ƒ ๐ฆ๐ข๐œ๐ซ๐จ๐ฌ๐œ๐จ๐ฉ๐ฒโ€ ๐€๐ฉ๐ซ๐ข๐ฅ ๐Ÿ๐Ÿ’๐ญ๐ก @ ๐Ÿ๐Ÿ ๐š๐ฆ ๐„๐ƒ๐“ (๐๐จ๐ฌ๐ญ๐จ๐ง ๐ญ๐ข๐ฆ๐ž, ๐”๐’๐€) Join us on Zoom! harvard.zoom.us/j/9307790905...

Abstract: 
Three-dimensional subcellular imaging is often hampered by diffraction limits in thick, heterogeneous tissues and invalid assumptions about data distribution and imaging systems.

We introduce SSAI-3D, a weakly physics-informed, domain-shift-resistant framework that robustly achieves isotropic 3D imaging.

Demonstrations in various label-free samples, plus validation on publicly available 3D datasets with unknown blurring and noise, confirm its potential for more accurate subcellular analysis.