Description
This pipeline can be used to mask PHI information in Dicom. Masked entities include AGE, BIOID, CITY, COUNTRY, DATE, DEVICE, DOCTOR, EMAIL, FAX, HEALTHPLAN, HOSPITAL, IDNUM, LOCATION, MEDICALRECORD, ORGANIZATION, PATIENT, PHONE, PROFESSION, STATE, STREET, URL, USERNAME, ZIP, ACCOUNT, LICENSE, VIN, SSN, DLN, PLATE, and IPADDR. The output is a Dicom document, similar to the one at the input, but with black bounding boxes on top of the targeted entities and de-identified metadata.
How to use
from sparknlp.pretrained import PretrainedPipeline
deid_pipeline = PretrainedPipeline(“dicom_died_pipeline”, “en”, “clinical/models”)
from sparknlp.pretrained import PretrainedPipeline
deid_pipeline = PretrainedPipeline("dicom_died_pipeline", "en", "clinical/models")
Model Information
| Model Name: | dicom_died_pipeline |
| Type: | pipeline |
| Compatibility: | Healthcare NLP 5.3.3+ |
| License: | Licensed |
| Edition: | Official |
| Language: | en |
| Size: | 1.8 GB |
Included Models
- DicomToMetadata
- DicomToImageV3
- ImageTextDetectorV2
- ImageToTextV3
- DicomDeidentifier
- PipelineModel
- PositionFinder
- DicomDrawRegions
- DicomMetadataDeidentifier