---
{}
---

# ATLAS-1: 3D Drug-Treated Cancer Cells

**ATLAS-1** is a research dataset of single-cell **3D morphologies** captured under different drug treatments.  
It contains **1,500** WM266-4 human melanoma cells embedded in **collagen** and imaged using **oblique-plane light-sheet microscopy**. Each cell is released as a **1024-point point cloud** sampled from a reconstructed **surface mesh**.

- **Total cells:** 1,500  
- **Classes / conditions:**  
  - `nocodazole` (500) — microtubule inhibitor; rounded morphology  
  - `blebbistatin` (500) — myosin II inhibitor; elongated/spindle morphology  
  - `control` (500) — untreated baseline variability  
- **Representations:** point clouds (1024 pts/cell) and watertight meshes  
- **Intended use:** benchmarking point-cloud models on real biological shapes; studying drug-induced 3D morphology

> This dataset accompanies the **PointMIL** project (inherently interpretable point-cloud classification via MIL).

---

## Dataset Summary

Cells were segmented, meshed with **marching cubes** (+ Laplacian smoothing), then **uniformly sampled** to 1024 points per cell from the surface mesh. Files are organized by condition with a metadata CSV that holds labels and basic experiment info.

**Why ATLAS-1?**
- Real, noisy, heterogeneous 3D cell shapes (not synthetic CAD)
- Clear treatment effects (rounded vs elongated) for interpretable benchmarks
- Comes with both **mesh** and **point-cloud** views for flexible pipelines

---

## Repository Layout

🚀 PointMIL is an ICCV 2025 Highlight — powering interpretable 3D cell shape analysis at Sentinal4D



At Sentinal4D, we’re pioneering the analysis of 3D cell shapes, and we believe models should be trustworthy by design.



PointMIL is our unified Multiple Instance Learning (MIL) framework that delivers state-of-the-art accuracy across 3D biomedical datasets and inherent interpretability.



Why this matters for biology

- Mapping drug effects in 3D: See which cell regions the drug affects, e.g., rounding vs. elongation, lost protrusions, altered curvature.

- New dataset, ATLAS-1: Drug-treated 3D melanoma cells in collagen (control, nocodazole, blebbistatin) to evaluate both performance and interpretability on real data. Available on Hugging Face 🤗 

- Higher accuracy than black-box models. 

- Plug-in head: Works with popular point-cloud backbones.



Try it for yourself:

🌐 Project page + live demo: https://sentinal4d.github.io/PointMIL/

💾 Code: https://github.com/Sentinal4D/PointMIL/

🧪 Dataset (ATLAS-1): https://sentinal4d.github.io/ATLAS-1/

If you work on cell morphology, drug discovery, or explainable 3D AI, we’d love your feedback and collaborations.



#ICCV2025 #Sentinal4D #PointMIL #3D #CellBiology #Morphology #ExplainableAI #XAI #ComputerVision #MIL #OpenScience