FlexiCT 2D

--- license: cc-by-nc-nd-4.0 library_name: transformers pipeline_tag: image-feature-extraction tags: - medical-imaging - ct - vision --- # FlexiCT-2D FlexiCT-2D is the slice-level CT encoder in the FlexiCT family. ## Input and preprocessing Default processor output shape is `[B, 1, 512, 512]`. Preprocessing clips HU to `[-1000, 1000]`, z-score normalizes, selects a slice when given a volume, center-pads the slice to square, and bilinear-resizes to `512 x 512`. Path inputs are loaded in LPS orientation when SimpleITK is available. ```python from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("ricklisz/FlexiCT-2D", trust_remote_code=True) model = AutoModel.from_pretrained("ricklisz/FlexiCT-2D", trust_remote_code=True) inputs = processor("/path/to/ct.nii.gz", return_tensors="pt", slice_index=80) outputs = model(**inputs) cls_token = outputs.cls_token patch_tokens = outputs.patch_tokens ``` ## Outputs `cls_token` is a global slice embedding. `patch_tokens` are spatial patch embeddings. ## Limitations This model is a feature extractor, not a diagnostic system. It expects CT-like HU inputs and has not been validated for clinical decision-making.

Source context: 137 downloads · 0 likes · Pipeline image-feature-extraction · Library transformers · Repo ricklisz123/FlexiCT-2D

Source context: 128 downloads · 0 likes · Pipeline image-feature-extraction · Library transformers · Repo ricklisz123/FlexiCT-2D