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MHub / GC - Minor cleanup gc_lunglobes #42

Merged
merged 8 commits into from
Mar 4, 2024
6 changes: 1 addition & 5 deletions models/gc_lunglobes/config/default.yml
Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,6 @@ execute:
- DicomImporter
- MhaConverter
- LobeSegmentationRunner
- NiftiConverter
- DsegConverter
- DataOrganizer

Expand All @@ -20,10 +19,7 @@ modules:
mod: ct

MhaConverter:
engine: plastimatch

NiftiConverter:
in_datas: mha:mod=seg
engine: panimg

DsegConverter:
model_name: GCLungLobes
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6 changes: 3 additions & 3 deletions models/gc_lunglobes/dockerfiles/Dockerfile
Original file line number Diff line number Diff line change
@@ -1,7 +1,7 @@
FROM mhubai/base:latest

# Update authors label
LABEL authors="s[email protected],[email protected],[email protected]"
LABEL authors="sil[email protected],[email protected],[email protected]"

# Install system dependencies for OpenCV
RUN apt-get update && apt-get install ffmpeg libsm6 libxext6 -y
Expand All @@ -19,8 +19,8 @@ RUN pip3 install --no-cache-dir --force-reinstall SimpleITK==1.2.4
ARG MHUB_MODELS_REPO
RUN buildutils/import_mhub_model.sh gc_lunglobes ${MHUB_MODELS_REPO}

# Install Xie's pulmonary lobe segmentation algorithm and model weights
RUN git clone https://github.com/DIAGNijmegen/bodyct-pulmonary-lobe-segmentation.git src && \
# Install Xie's pulmonary lobe segmentation algorithm and model weights (release gclobe165 v1.6.5)
RUN git clone --depth 1 --branch v1.6.5 https://github.com/DIAGNijmegen/bodyct-pulmonary-lobe-segmentation.git src && \
sed -i 's/from models import CTSUNet/from src.models import CTSUNet/g' src/test.py

# Default run script
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12 changes: 6 additions & 6 deletions models/gc_lunglobes/meta.json
Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,7 @@
"format": "DICOM",
"modality": "CT",
"bodypartexamined": "Chest",
"slicethickness": "2.5mm",
"slicethickness": "0.75mm",
"non-contrast": true,
"contrast": false
} ],
Expand All @@ -26,7 +26,7 @@
} ],
"model": {
"architecture": "Relational two-stage U-net",
"training": "Supervised",
"training": "supervised",
"cmpapproach": "3D"
},
"data": {
Expand All @@ -36,7 +36,7 @@
"evaluation": {
"vol_samples": 1155
},
"public": "Partially",
"public": false,
"external": true
}
},
Expand All @@ -46,9 +46,9 @@
"devteam": "DIAGNijmegen (Diagnostic Image Analysis Group, Radboud UMC, The Netherlands)",
"type": "Relational two-stage U-Net (Cascade of two relational U-Net, trained end-to-end)",
"date": {
"weights": "14/02/22",
"code": "n/a",
"pub": "n/a"
"weights": "2022-02-14",
"code": "2023-11-27",
"pub": "2020-05-15"
},
"cite": "W. Xie, C. Jacobs, J. -P. Charbonnier and B. van Ginneken, 'Relational Modeling for Robust and Efficient Pulmonary Lobe Segmentation in CT Scans,' in IEEE Transactions on Medical Imaging, vol. 39, no. 8, pp. 2664-2675, Aug. 2020, doi: 10.1109/TMI.2020.2995108.",
"license": {
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