No. 01
CVPR 2026 · Highlight
Unsupervised cryo-ET segmentation with a Stable Diffusion foundation model
Multi-scale segmentation of cellular cryo-electron tomograms, with no labels.
Read paper →AI VIETNAM ✦ AIO 2026 cohort ✦ Anno MMXXVI
AIMA Research is where Vietnamese students become researchers in translational AI for health. In two years our groups have published 47 papers. This page is the record, and the invitation to AIO 2026.
The Record
Every number below is counted from the paper list on this page. Tap a bar to open that year in the library.
| Year | Conference | Journal | Total |
|---|
One bar per journal article. Tap to read.
Sized by paper count. Tap a venue to filter the library.
Conferences & workshops
Journals
Cabinet of 2026
Drag or scroll sideways through the year's highlights.
No. 01
CVPR 2026 · Highlight
Multi-scale segmentation of cellular cryo-electron tomograms, with no labels.
Read paper →No. 02
ISBI 2026 · CXR-LT Challenge
Chest X-ray classification when most diseases have few or no training examples.
No. 03
ISBI 2026 · 5 orals
Scribble supervision, SAM on unlabeled images, histopathology prototypes, white blood cells and chest X-rays.
See the orals →No. 04
npj Digital Medicine · IF 12.4
Our highest-impact journal paper to date.
Read paper →No. 05
Medical Image Analysis · IF 11.8
Which patient subgroups a long-tailed chest X-ray classifier underdiagnoses.
Read paper →No. 06
ECCV 2026
Vision-language models that catch and correct their own mistakes.
Read paper →No. 07
Pattern Recognition · IF 7.6
Adaptive knowledge transfer for semi-supervised medical image segmentation.
Read paper →Next
The AIO 2026 cohort starts here.
See the 2026 projects →The Library
Search, filter and cite. Names in gold are AIMA mentors.
Atlas of Themes
A paper can sit in more than one theme. Hover a theme to trace its papers; tap it to open them in the library.
For AIO 2026
The same route the authors above took. Most of them were AI VIETNAM students first.
When the cohort opens, pick a project prototype and tell us your background and what you want to learn.
A research group of 4–6 members, led by a PhD student, postdoc or professor in the US or Australia.
Read papers critically, build reproducible PyTorch pipelines, handle medical images, and use AI coding agents without losing rigor.
Own a question, run the experiments, defend the results in weekly meetings. Mentors guide; they do not do it for you.
Workshop, then conference, then journal. A record for graduate school and a network that lasts.
Six projects, now closed. They show the scale and targets to expect.
The Mentors