| --- |
| language: |
| - en |
| license: apache-2.0 |
| pipeline_tag: image-feature-extraction |
| tags: |
| - cytology |
| - hematology |
| - pathology |
| - vision |
| - pytorch |
| - self-supervised |
| - vit |
| --- |
| |
| # GenBloom |
|
|
| [GenBloom](https://huggingface.co/papers/2605.29980) is a genetically-aligned foundation model for peripheral blood smears. It aligns single white blood cell images with chromosomal aberrations (karyotype) and somatic mutations from targeted gene panels. |
|
|
| For the source code, setup, and evaluation scripts, see the [GenBloom GitHub repository](https://github.com/marrlab/GenBloom). |
|
|
| ## Model Description |
|
|
| GenBloom is a patient-level encoder trained using a two-stage approach: |
| 1. **GenBloom-V (Self-supervised Pretraining)**: Vision-only pretraining of a transformer aggregator using an iBOT head on a cohort of over 1,500 patients. |
| 2. **GenBloom-G (Genetic Alignment)**: Further alignment of visual features with chromosomal aberrations and somatic mutations via supervised contrastive loss on acute myeloid leukemia patients. |
|
|
| The model provides improved representations for hematological diagnostic tasks and provides off-the-shelf retrieval capabilities for diseases and genetic alterations. |
|
|
| ## Checkpoints |
|
|
| This repository contains the model weights used for the public visual downstream reproduction: |
|
|
| ```text |
| checkpoints/ |
| genbloom_v/ |
| genbloom_v.pth |
| genbloom_g/ |
| genbloom_g_fold0.pth |
| genbloom_g_fold1.pth |
| genbloom_g_fold2.pth |
| genbloom_g_fold3.pth |
| genbloom_g_fold4.pth |
| ``` |
|
|
| - The `genbloom_v` checkpoint corresponds to image-only pretraining. |
| - The `genbloom_g` checkpoints were further genetically aligned. |
|
|
| ## Usage |
|
|
| ### Download Checkpoints |
| You can download the checkpoints using the `huggingface_hub` library: |
|
|
| ```python |
| from huggingface_hub import snapshot_download |
| |
| snapshot_download("MarrLab/GenBloom", local_dir="checkpoints") |
| ``` |
|
|
| ### Inference |
| A minimal end-to-end inference example is available in the [`inference_genbloom.ipynb`](https://github.com/marrlab/GenBloom/blob/main/inference_genbloom.ipynb) notebook in the official repository. |
|
|
| ## Citation |
|
|
| If you use GenBloom in your research, please cite: |
|
|
| ```bibtex |
| @article{genbloom2024, |
| title={Genetically Aligned Patient Representations Improve Hematological Diagnosis}, |
| author={Adelpantidis, Georgios and others}, |
| journal={arXiv preprint arXiv:2605.29980}, |
| year={2024} |
| } |
| ``` |
