Description
Pretrained pipeline for doing Dicom De-identification, attempting to remove the least possible amount of tags and image texts.
Predicted Entities
How to use
dicom_df = spark.read.format("binaryFile").load(dicom_path)
pipeline = PretrainedPipeline("dicom_deid_generic_augmented_minimal", "en", "clinical/ocr")
result = pipeline.transform(dicom_df).cache()
val dicom_df = spark.read.format("binaryFile").load(dicom_path)
val pipeline = new PretrainedPipeline("dicom_deid_generic_augmented_minimal", "en", "clinical/ocr")
val result = pipeline.transform(dicom_df).cache()
Example
Input:
Output:
Model Information
| Model Name: | dicom_deid_generic_augmented_minimal |
| Type: | pipeline |
| Compatibility: | Visual NLP 5.5.0+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |