[](https://pypi.python.org/pypi/tptbox/)
[](https://pypi.org/project/tptbox/)
[](https://pypi.python.org/pypi/tptbox/)
[](https://github.com/Hendrik-code/TPTBox/actions/workflows/tests.yml)
[](https://codecov.io/gh/Hendrik-code/TPTBox)
[](https://www.gnu.org/licenses/agpl-3.0)
# Torso Processing ToolBox (TPTBox)
This is a multi-functional package to handle any sort of bids-conform dataset (CT, MRI, ...)
It can find, filter, search any BIDS_Family and subjects, and has many functionalities, among them:
- Easily loop over datasets, and the required files
- Read, Write Niftys, centroid jsons, ...
- Reorient, Resample, Shift Niftys, Centroids, labels
- Modular 2D snapshot generation (different views, MIPs, ...)
- 3D Mesh generation from segmentation and snapshots from them
- Registration
- Logging everything consistently
- ...
## Install the package
```bash
conda create -n 3.10 python=3.10
conda activate 3.10
pip install TPTBox
```
### Install via github:
(you should be in the project folder)
```bash
pip install poetry
poetry install
```
or:
Develop mode is really, really nice:
```bash
pip install poetry
poetry install --with dev
```
## Functionalities
Each folder in this package represents a different functionality.
The top-level-hierarchy incorporates the most important files, the BIDS_files.
### BIDS_Files
This file builds a data model out of the BIDS file names.
It can load a dataset as a BIDS_Global_info file, from which search queries and loops over the dataset can be started.
See ```tutorial_BIDS_files.ipynb``` for details.
### bids_constants
Defines constants for the BIDS nomenclature (sequence-splitting keys, naming conventions...)
### vert_constants
Contains definitions and sort order for our intern labels, for vertebrae, POI, ...
### Rotation and Resampling
Example rotate and resample.
```python
from TPTBox import NII
nii = NII.load("...path/xyz.nii.gz", seg=True)
# R right, L left
# S superior/up, I inferior/down
# A anterior/front, P posterior/back
img_rot = nii.reorient(axcodes_to=("P", "I", "R"))
img_scale = nii.rescale((1.5, 5, 1)) # in mm as currently rotated
# resample to an other image
img_resampled_to_other = nii.resample_from_to(img_scale)
nii.get_array() # get numpy array
nii.affine # Affine matrix
nii.header # NIFTY header
nii.orientation # Orientation in 3-Letters
nii.zoom # Scale of the three image axis
nii.shape #shape
```
### Stitching
Python function and script for arbitrary image stitching. [See Details](TPTBox/stitching/)
### Spineps and Points of Interests (POI) integration
For our Spine segmentation pipline follow the installation of [SPINEPS](https://github.com/Hendrik-code/spineps).
SPINEPS will produce two mask: instance and semantic labels. With these we can compute our POIs. There are either center of mass points or surface points with bioloical meaning. See [Validation of a Patient-Specific Musculoskeletal Model for Lumbar Load Estimation Generated by an Automated Pipeline From Whole Body CT](https://pubmed.ncbi.nlm.nih.gov/35898642/)
```python
from TPTBox import NII, POI, Location, calc_poi_from_subreg_vert
from TPTBox.core.vert_constants import v_name2idx
p = "/dataset-DATASET/derivatives/A/"
semantic_nii = NII.load(f"{p}sub-A_sequ-stitched_acq-sag_mod-T2w_seg-spine_msk.nii.gz", seg=True)
instance_nii = NII.load(f"{p}sub-A_sequ-stitched_acq-sag_mod-T2w_seg-vert_msk.nii.gz", seg=True)
poi_path = f"{p}sub-A_sequ-stitched_acq-sag_mod-T2w_seg-spine_ctd.json"
poi = POI.load(poi_path)
poi = calc_poi_from_subreg_vert(
instance_nii,
semantic_nii,
# buffer_file=poi_path,
subreg_id=[
Location.Vertebra_Full,
Location.Arcus_Vertebrae,
Location.Spinosus_Process,
Location.Costal_Process_Left,
Location.Costal_Process_Right,
Location.Superior_Articular_Left,
Location.Superior_Articular_Right,
Location.Inferior_Articular_Left,
Location.Inferior_Articular_Right,
# Location.Vertebra_Corpus_border, CT only
Location.Vertebra_Corpus,
Location.Vertebra_Disc,
Location.Muscle_Inserts_Spinosus_Process,
Location.Muscle_Inserts_Transverse_Process_Left,
Location.Muscle_Inserts_Transverse_Process_Right,
Location.Muscle_Inserts_Vertebral_Body_Left,
Location.Muscle_Inserts_Vertebral_Body_Right,
Location.Muscle_Inserts_Articulate_Process_Inferior_Left,
Location.Muscle_Inserts_Articulate_Process_Inferior_Right,
Location.Muscle_Inserts_Articulate_Process_Superior_Left,
Location.Muscle_Inserts_Articulate_Process_Superior_Right,
Location.Ligament_Attachment_Point_Anterior_Longitudinal_Superior_Median,
Location.Ligament_Attachment_Point_Posterior_Longitudinal_Superior_Median,
Location.Ligament_Attachment_Point_Anterior_Longitudinal_Inferior_Median,
Location.Ligament_Attachment_Point_Posterior_Longitudinal_Inferior_Median,
Location.Additional_Vertebral_Body_Middle_Superior_Median,
Location.Additional_Vertebral_Body_Posterior_Central_Median,
Location.Additional_Vertebral_Body_Middle_Inferior_Median,
Location.Additional_Vertebral_Body_Anterior_Central_Median,
Location.Ligament_Attachment_Point_Anterior_Longitudinal_Superior_Left,
Location.Ligament_Attachment_Point_Posterior_Longitudinal_Superior_Left,
Location.Ligament_Attachment_Point_Anterior_Longitudinal_Inferior_Left,
Location.Ligament_Attachment_Point_Posterior_Longitudinal_Inferior_Left,
Location.Additional_Vertebral_Body_Middle_Superior_Left,
Location.Additional_Vertebral_Body_Posterior_Central_Left,
Location.Additional_Vertebral_Body_Middle_Inferior_Left,
Location.Additional_Vertebral_Body_Anterior_Central_Left,
Location.Ligament_Attachment_Point_Anterior_Longitudinal_Superior_Right,
Location.Ligament_Attachment_Point_Posterior_Longitudinal_Superior_Right,
Location.Ligament_Attachment_Point_Anterior_Longitudinal_Inferior_Right,
Location.Ligament_Attachment_Point_Posterior_Longitudinal_Inferior_Right,
Location.Additional_Vertebral_Body_Middle_Superior_Right,
Location.Additional_Vertebral_Body_Posterior_Central_Right,
Location.Additional_Vertebral_Body_Middle_Inferior_Right,
Location.Additional_Vertebral_Body_Anterior_Central_Right,
Location.Ligament_Attachment_Point_Flava_Superior_Median,
Location.Ligament_Attachment_Point_Flava_Inferior_Median,
Location.Vertebra_Direction_Posterior,
Location.Vertebra_Direction_Inferior,
Location.Vertebra_Direction_Right,
],
)
# poi.save(poi_path)
poi = poi.round(2)
print("Vertebra T4 Vertebra Corpus Center of mass:", poi[v_name2idx["T4"], Location.Vertebra_Corpus])
# rescale/reorante like nii
poi_new = poi.reorient(("P", "I", "R")).rescale((1, 1, 1))
poi_new = poi.resample_from_to(other_nii_or_poi)
```
### Snapshot2D Spine
The snapshot function automatically generates sag, cor, axial cuts in the center of a segmentation.
```python
from TPTBox.spine.snapshot2D import Snapshot_Frame, create_snapshot
ct = Path("Path to CT")
mri = Path("Path to MRI")
vert = Path("Path to Vertebra segmentation")
subreg = Path("Path to Vertebra subregions")
poi_ct = Path("Path to Vertebra poi")
poi_mr = Path("Path to Vertebra poi")
ct_frame = Snapshot_Frame(image=ct, segmentation=vert, centroids=poi_ct, mode="CT", coronal=True, axial=True)
mr_frame = Snapshot_Frame(image=mri, segmentation=vert, centroids=poi_mr, mode="MRI", coronal=True, axial=True)
create_snapshot(snp_path="snapshot.jpg", frames=[ct_frame, mr_frame])
```
### Snapshot3D
Requires additonal python packages: vtk fury xvfbwrapper
```python
from TPTBox.mesh3D.snapshot3D import make_snapshot3D
# all segmentation; view give the rotation of an image
make_snapshot3D("sub-101000_msk.nii.gz","snapshot3D.png",view=["A", "L", "P", "R"])
# Select witch segmentation per panel are chosen.
make_snapshot3D("sub-101000_msk.nii.gz","snapshot3D_v2.png",view=["A"], ids_list=[[1,2],[3]])
```
### Logger
```python
TBD
```
### Point registration with POIs
```python
TBD
```
> [!Note]
> Notably, ...
> [!TIP]
> A Tip
> [!IMPORTANT]
> Importantly
Raw data
{
"_id": null,
"home_page": "https://github.com/Hendrik-code/TPTBox",
"name": "TPTBox",
"maintainer": null,
"docs_url": null,
"requires_python": "<4.0,>=3.10",
"maintainer_email": null,
"keywords": null,
"author": "Robert Graf",
"author_email": "robert.graf@tum.de",
"download_url": null,
"platform": null,
"description": "[](https://pypi.python.org/pypi/tptbox/)\n[](https://pypi.org/project/tptbox/)\n[](https://pypi.python.org/pypi/tptbox/)\n[](https://github.com/Hendrik-code/TPTBox/actions/workflows/tests.yml)\n[](https://codecov.io/gh/Hendrik-code/TPTBox)\n[](https://www.gnu.org/licenses/agpl-3.0)\n\n# Torso Processing ToolBox (TPTBox)\n\nThis is a multi-functional package to handle any sort of bids-conform dataset (CT, MRI, ...)\nIt can find, filter, search any BIDS_Family and subjects, and has many functionalities, among them:\n- Easily loop over datasets, and the required files\n- Read, Write Niftys, centroid jsons, ...\n- Reorient, Resample, Shift Niftys, Centroids, labels\n- Modular 2D snapshot generation (different views, MIPs, ...)\n- 3D Mesh generation from segmentation and snapshots from them\n- Registration\n- Logging everything consistently\n- ...\n\n## Install the package\n```bash\nconda create -n 3.10 python=3.10\nconda activate 3.10\npip install TPTBox\n```\n### Install via github:\n(you should be in the project folder)\n```bash\npip install poetry\npoetry install\n```\nor:\nDevelop mode is really, really nice:\n```bash\npip install poetry\npoetry install --with dev\n```\n\n## Functionalities\n\nEach folder in this package represents a different functionality.\n\nThe top-level-hierarchy incorporates the most important files, the BIDS_files.\n\n### BIDS_Files\n\nThis file builds a data model out of the BIDS file names.\nIt can load a dataset as a BIDS_Global_info file, from which search queries and loops over the dataset can be started.\nSee ```tutorial_BIDS_files.ipynb``` for details.\n\n### bids_constants\nDefines constants for the BIDS nomenclature (sequence-splitting keys, naming conventions...)\n\n### vert_constants\n\nContains definitions and sort order for our intern labels, for vertebrae, POI, ...\n\n### Rotation and Resampling\n\nExample rotate and resample.\n\n```python\nfrom TPTBox import NII\n\nnii = NII.load(\"...path/xyz.nii.gz\", seg=True)\n# R right, L left\n# S superior/up, I inferior/down\n# A anterior/front, P posterior/back\nimg_rot = nii.reorient(axcodes_to=(\"P\", \"I\", \"R\"))\nimg_scale = nii.rescale((1.5, 5, 1)) # in mm as currently rotated\n# resample to an other image\nimg_resampled_to_other = nii.resample_from_to(img_scale)\n\nnii.get_array() # get numpy array\nnii.affine # Affine matrix\nnii.header # NIFTY header\nnii.orientation # Orientation in 3-Letters\nnii.zoom # Scale of the three image axis\nnii.shape #shape\n```\n### Stitching\nPython function and script for arbitrary image stitching. [See Details](TPTBox/stitching/)\n### Spineps and Points of Interests (POI) integration\nFor our Spine segmentation pipline follow the installation of [SPINEPS](https://github.com/Hendrik-code/spineps).\n\nSPINEPS will produce two mask: instance and semantic labels. With these we can compute our POIs. There are either center of mass points or surface points with bioloical meaning. See [Validation of a Patient-Specific Musculoskeletal Model for Lumbar Load Estimation Generated by an Automated Pipeline From Whole Body CT](https://pubmed.ncbi.nlm.nih.gov/35898642/)\n```python\nfrom TPTBox import NII, POI, Location, calc_poi_from_subreg_vert\nfrom TPTBox.core.vert_constants import v_name2idx\n\np = \"/dataset-DATASET/derivatives/A/\"\nsemantic_nii = NII.load(f\"{p}sub-A_sequ-stitched_acq-sag_mod-T2w_seg-spine_msk.nii.gz\", seg=True)\ninstance_nii = NII.load(f\"{p}sub-A_sequ-stitched_acq-sag_mod-T2w_seg-vert_msk.nii.gz\", seg=True)\npoi_path = f\"{p}sub-A_sequ-stitched_acq-sag_mod-T2w_seg-spine_ctd.json\"\npoi = POI.load(poi_path)\npoi = calc_poi_from_subreg_vert(\n instance_nii,\n semantic_nii,\n # buffer_file=poi_path,\n subreg_id=[\n Location.Vertebra_Full,\n Location.Arcus_Vertebrae,\n Location.Spinosus_Process,\n Location.Costal_Process_Left,\n Location.Costal_Process_Right,\n Location.Superior_Articular_Left,\n Location.Superior_Articular_Right,\n Location.Inferior_Articular_Left,\n Location.Inferior_Articular_Right,\n # Location.Vertebra_Corpus_border, CT only\n Location.Vertebra_Corpus,\n Location.Vertebra_Disc,\n Location.Muscle_Inserts_Spinosus_Process,\n Location.Muscle_Inserts_Transverse_Process_Left,\n Location.Muscle_Inserts_Transverse_Process_Right,\n Location.Muscle_Inserts_Vertebral_Body_Left,\n Location.Muscle_Inserts_Vertebral_Body_Right,\n Location.Muscle_Inserts_Articulate_Process_Inferior_Left,\n Location.Muscle_Inserts_Articulate_Process_Inferior_Right,\n Location.Muscle_Inserts_Articulate_Process_Superior_Left,\n Location.Muscle_Inserts_Articulate_Process_Superior_Right,\n Location.Ligament_Attachment_Point_Anterior_Longitudinal_Superior_Median,\n Location.Ligament_Attachment_Point_Posterior_Longitudinal_Superior_Median,\n Location.Ligament_Attachment_Point_Anterior_Longitudinal_Inferior_Median,\n Location.Ligament_Attachment_Point_Posterior_Longitudinal_Inferior_Median,\n Location.Additional_Vertebral_Body_Middle_Superior_Median,\n Location.Additional_Vertebral_Body_Posterior_Central_Median,\n Location.Additional_Vertebral_Body_Middle_Inferior_Median,\n Location.Additional_Vertebral_Body_Anterior_Central_Median,\n Location.Ligament_Attachment_Point_Anterior_Longitudinal_Superior_Left,\n Location.Ligament_Attachment_Point_Posterior_Longitudinal_Superior_Left,\n Location.Ligament_Attachment_Point_Anterior_Longitudinal_Inferior_Left,\n Location.Ligament_Attachment_Point_Posterior_Longitudinal_Inferior_Left,\n Location.Additional_Vertebral_Body_Middle_Superior_Left,\n Location.Additional_Vertebral_Body_Posterior_Central_Left,\n Location.Additional_Vertebral_Body_Middle_Inferior_Left,\n Location.Additional_Vertebral_Body_Anterior_Central_Left,\n Location.Ligament_Attachment_Point_Anterior_Longitudinal_Superior_Right,\n Location.Ligament_Attachment_Point_Posterior_Longitudinal_Superior_Right,\n Location.Ligament_Attachment_Point_Anterior_Longitudinal_Inferior_Right,\n Location.Ligament_Attachment_Point_Posterior_Longitudinal_Inferior_Right,\n Location.Additional_Vertebral_Body_Middle_Superior_Right,\n Location.Additional_Vertebral_Body_Posterior_Central_Right,\n Location.Additional_Vertebral_Body_Middle_Inferior_Right,\n Location.Additional_Vertebral_Body_Anterior_Central_Right,\n Location.Ligament_Attachment_Point_Flava_Superior_Median,\n Location.Ligament_Attachment_Point_Flava_Inferior_Median,\n Location.Vertebra_Direction_Posterior,\n Location.Vertebra_Direction_Inferior,\n Location.Vertebra_Direction_Right,\n ],\n)\n# poi.save(poi_path)\npoi = poi.round(2)\nprint(\"Vertebra T4 Vertebra Corpus Center of mass:\", poi[v_name2idx[\"T4\"], Location.Vertebra_Corpus])\n# rescale/reorante like nii\npoi_new = poi.reorient((\"P\", \"I\", \"R\")).rescale((1, 1, 1))\npoi_new = poi.resample_from_to(other_nii_or_poi)\n\n```\n\n\n### Snapshot2D Spine\n\nThe snapshot function automatically generates sag, cor, axial cuts in the center of a segmentation.\n\n```python\nfrom TPTBox.spine.snapshot2D import Snapshot_Frame, create_snapshot\n\nct = Path(\"Path to CT\")\nmri = Path(\"Path to MRI\")\nvert = Path(\"Path to Vertebra segmentation\")\nsubreg = Path(\"Path to Vertebra subregions\")\npoi_ct = Path(\"Path to Vertebra poi\")\npoi_mr = Path(\"Path to Vertebra poi\")\n\nct_frame = Snapshot_Frame(image=ct, segmentation=vert, centroids=poi_ct, mode=\"CT\", coronal=True, axial=True)\nmr_frame = Snapshot_Frame(image=mri, segmentation=vert, centroids=poi_mr, mode=\"MRI\", coronal=True, axial=True)\ncreate_snapshot(snp_path=\"snapshot.jpg\", frames=[ct_frame, mr_frame])\n```\n\n\n### Snapshot3D\n\nRequires additonal python packages: vtk fury xvfbwrapper\n\n```python\nfrom TPTBox.mesh3D.snapshot3D import make_snapshot3D\n# all segmentation; view give the rotation of an image\nmake_snapshot3D(\"sub-101000_msk.nii.gz\",\"snapshot3D.png\",view=[\"A\", \"L\", \"P\", \"R\"])\n# Select witch segmentation per panel are chosen.\nmake_snapshot3D(\"sub-101000_msk.nii.gz\",\"snapshot3D_v2.png\",view=[\"A\"], ids_list=[[1,2],[3]])\n```\n\n### Logger\n\n```python\nTBD\n```\n\n### Point registration with POIs\n```python\nTBD\n```\n\n\n> [!Note]\n> Notably, ...\n\n> [!TIP]\n> A Tip\n\n> [!IMPORTANT]\n> Importantly\n\n",
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