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https://github.com/touhoue/convertscripts
Convert raw .dcm file into .nii.gz file for easier training and analysis.
https://github.com/touhoue/convertscripts
dcm2niix python
Last synced: 24 days ago
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Convert raw .dcm file into .nii.gz file for easier training and analysis.
- Host: GitHub
- URL: https://github.com/touhoue/convertscripts
- Owner: TouHouE
- Created: 2024-05-07T11:08:32.000Z (9 months ago)
- Default Branch: master
- Last Pushed: 2024-12-26T08:41:51.000Z (27 days ago)
- Last Synced: 2024-12-26T09:30:24.805Z (27 days ago)
- Topics: dcm2niix, python
- Language: Python
- Homepage:
- Size: 689 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Taipei-1 Usage Convert Scripts
## 1. Requirements
- pydicom
- nibabel
- pandas
- numpy
## 2. Using to convert *.dcm file to *.nii.gz file
- `dcm2niix_HsinChu.py`
- This script is using to convert *.dcm file that come from HsinChu Hospital
- You might notice that there is no extension name in the raw file, and we also can't read each file directly; fortunately, `dcm2niix.exe` is still working!
- The dictionary from HsinChu be like:
```
/mnt/HsinChu
├── batch1 <-- the data_root must indicate this location
│ ├──S000001 <-- The dictionary at this layer is meaning a patient
│ ├──S000010
│ └──......
│
└── batch2
├── 2023.01-2023.12.... <-- the data_root must indicate this location
│ ├── S000001 <-- therefore, this meaining patient
│ ├── S000010
│ └── ......
├── 2024.01-2024.03.... <-- this one also indicate as data_root
│ └── ......
└── .....
```
- The batch1 is already uploaded on doctor's dropbox.
- The storage structure will same as original
- ex: \/\/\/\/\.nii.gz
- Example:
Follow the example dictionary structure, suppose we want to convert `/mnt/HsinChu/batch2/2023.01-2023.12`, and the target dictionary called `/mnt/hsinchu_dst`, the `dcm2niix.exe` place at `/mnt/lib/dcm2niix.exe`, then we simply named `out`, `buf`, `err` for output, buffer, error storage dictionary, and using 10 process, the command will look like:
```bash=
python dcm2niix_HsinChu.py --data_root=/mnt/HsinChu/batch2/2023.01-2023.12 --out_dir=/mnt/hsinchu_dst/out --buf_dir=/mnt/hsinchu_dst/buf --err_dir=/mnt/hsinchu_dst/err --num_workers=10 --dcm2niix=/mnt/lib/dcm2niix.exe
```
- `dcm2niix_Taipei.py`
- This script is using to convert *.dcm file that come from Taipei Hospital
- The dictionary from Taipei be like:
- The 502-dicom:
```
/mnt/usbB/'502-CT(dicom-format) <-- That is for argument --data_root
├── 0001 <-- here are the patient
├── 0003
└── ......
/mnt/usbB/'CCTA Result' <-- That one should pass into --isp_root
├── 0001 # Almost like 502-CT
├── 0003
└── ......
```
- PS: Because in this part got some chaos
1. I already convert around 4 / 5 of raw data(the *.dcm)
2. But I just put around 300 patient on doctor's dropbox
3. For ignore already processed part, the `--meta_dir` should point to the /mnt/usbA/502CT/meta
- But, for 2500+ dicom, that got different:
```
/mnt/usbC
├── CGMH <-- That dictionary is for argument --data_root
│ ├── 1557.zip <-- I suggest unzip after uploaded, send single file should faster than single dictionary.
│ ├── 0003
│ └── ......
├── CMUH <-- That is for argument --data_root
│ ├── 0001 <-- here are the patient
│ ├── 0003
│ └── ......
├── MMH
│ └── ......
├── MMH
│ └── ......
├── ......
└── CT標註result <-- That one is --isp_root
```
- The progress
- if the status show **Skip ISP** it represent the isp folder didn't contain any tissue labels.
## 2. Generate the prompt file
- Using `prompt_generate.py` to generate the VQA prompt
- This script should be launch after `dcm2niix_HsinChu.py` processed.
- The `--report_file` is placed at /mnt/usbB/HsinChu/text/*.xlsx
- I do some rename, if you see "batch1" in file name, this table should match the batch1 nii folder
- But, if is batch2, you should combine all of 3 table as 1 table then running the `prompt_generate.py`
- The `prompt_scripts_utils.py` should place at same path.
## PS
1. The dcm2niix program just download from [dcm2niix](https://github.com/rordenlab/dcm2niix/releases)