FlexiCT 3D

--- license: cc-by-nc-nd-4.0 library_name: transformers pipeline_tag: image-feature-extraction tags: - medical-imaging - ct - vision --- # FlexiCT-3D FlexiCT-3D is the whole-volume CT encoder in the FlexiCT family. ## Input and preprocessing Default processor output shape is `[B, 1, 160, 160, 160]`. The `default` preset orients/resamples path inputs to LPS at 2 mm spacing when spacing is available, clips HU to `[-1000, 1000]`, z-score normalizes, pads with the tensor minimum to at least `160^3`, and center crops to `160^3`. Optional presets: - `local_path`: pad to a cube, then trilinear-resize to `160^3` for arbitrary local CT files. - `retrieval_roi`: crop an ROI from coordinates, a mask, or a bounding box, pad boundary crops, then resize to `160^3`. ```python from transformers import AutoImageProcessor, AutoModel processor = AutoImageProcessor.from_pretrained("ricklisz123/FlexiCT-3D", trust_remote_code=True) model = AutoModel.from_pretrained("ricklisz123/FlexiCT-3D", trust_remote_code=True) inputs = processor("/path/to/ct.nii.gz", return_tensors="pt") outputs = model(**inputs) cls_token = outputs.cls_token patch_tokens = outputs.patch_tokens ``` ## Outputs `cls_token` is a global volume embedding. `patch_tokens` are 3D patch embeddings. ## Limitations This model is a research feature extractor. The `local_path` and `retrieval_roi` presets are convenience paths and may not match training or evaluation preprocessing exactly.

Source context: 36 downloads · 0 likes · Pipeline image-feature-extraction · Library transformers · Repo ricklisz123/FlexiCT-3D

Source context: 59 downloads · 0 likes · Pipeline image-feature-extraction · Library transformers · Repo ricklisz123/FlexiCT-3D