Encoder features for the four-modality pathology embedding model
This repo holds the frozen-encoder features and the data splits used to train and evaluate the model
iLOVE2D/fourmodal-pathology-bind.
That repo's reproduce.sh downloads these files into its own folder, so cache/ and splits/ sit next to the code.
No raw images, raw counts or raw mIF are stored here: only encoder features, gene and caption tables, and split files.
Licence: non-commercial research only. The features derive from ORION CRC, HEST-1k (CC-BY-NC-SA), TCGA / PathGen-1.6M, STPath and MIPHEI, and the frozen encoders listed in the model card. Each source's terms apply.
Real pairs (used for training and testing)
| File | Content | Shape |
|---|---|---|
cache/he_uni2.npy, cache/he_medvtok.npy |
ORION H&E. UNI2-h CLS and MedVTok global features. 8 dihedral views. | (3187, 8, 1536) and (3187, 8, 1152) |
cache/if_virtues_m16.npy |
ORION mIF. VirTues patch-summary mean over 16 markers. 8 views. | (3187, 8, 512) |
cache/hest/he_uni2.npy, he_medvtok.npy |
HEST H&E spot crops. | (9484, 1, ·) |
cache/hest/hvg.npy, hvg_genes.csv |
HEST RNA: log1p CP10k over 2000 HVGs. | (9484, 2000) |
cache/rnafm/{tahoex1,se600m,aidocell}_hest.npy |
HEST RNA foundation-model features. | (9484, ·) |
cache/hest/he_img_missing.csv |
Spots without an H&E crop. These are excluded. | |
cache/allimg_he_{uni2,medvtok}.npy |
TCGA / PathGen H&E patches. 8 views. | (6144, 8, ·) |
cache/alltxt_text_{keep,biomedclip,qwen3-0.6b}.npy |
Caption features. | (N_text, 1, ·) |
cache/alltxt_meta.csv, cache/alltxt_junk.csv |
Captions, the image index of each caption, and the cleaning flags. |
Virtual and synthetic data (used for testing only)
| File | Content | Shape |
|---|---|---|
cache/stpath/{orion,tcga_text}_{pred.npy,genes.csv} |
STPath virtual RNA for ORION and TCGA images. | |
cache/rnafm/*_{orion_v,tcga_v}.npy |
Foundation-model features of that virtual RNA. | |
cache/if_virtues_m16_virtual_miphei_tcga_text.npy |
MIPHEI virtual mIF of the TCGA images, encoded with VirTues. | |
cache/orion_gentext_text_*.npy |
GPT-generated (synthetic) descriptions of the ORION tiles. |
Splits
splits/patient_5fold/fold{k}.csv: ORION, grouped by patient.splits/final/hest_fold{k}.csv: HEST, grouped by study / patient.splits/final/tcga_fold{k}.csv: TCGA, grouped by patient.
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