z-rad

Name	z-rad JSON
Version	25.9.0 JSON
	download
home_page	None
Summary	Z-Rad is a radiomic feature extraction software with GUI and API.
upload_time	2025-09-03 11:39:01
maintainer	None
docs_url	None
author	None
requires_python	>=3.10
license	MIT
keywords	radiomics feature-extraction python gui api
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

# Z-RAD

Radiomics is the high-throughput extraction of quantitative features from medical images,
revolutionizing personalized medicine and enhancing clinical decision-making.
Despite its potential, radiomics faces several challenges, including the need for programming skills
and lack of standardization.

**Z-Rad (Zurich Radiomics)**, developed by the Radiation Oncology Department at the University Hospital Zurich,
addresses these issues by offering a user-friendly, IBSI-compliant, and open-source solution for radiomics analysis.

## Z-Rad Features
<img src="https://raw.githubusercontent.com/medical-physics-usz/z-rad/master/doc/images/zrad_screenshot.png" width="600" alt="Z-Rad screenshot"/>

### User-Friendly Interface
- **Graphical User Interface (GUI)**: Designed for medical professionals with no programming skills.
- **Application Programming Interface (API)**: Allows researchers to customize, automate, and extend Z-Rad functionalities using Python.

### Compatibility
- **Medical Data Formats**: Supports CT, PET, and MR imaging modalities in both DICOM and NIfTI formats.
- **Operating Systems**: Windows, macOS, and Linux.

### Standard Compliance
- **IBSI Compliance**: Adheres to [IBSI I](https://arxiv.org/abs/1612.07003) and [IBSI II](https://arxiv.org/abs/2006.05470) standards for reproducible and comparable radiomics features.

## Software Architecture and Design

### Backend
- **Programming Language**: Python.
- **Dependencies**:
- Joblib
- NumPy
- OpenCV
- OpenPyXL
- Pandas
- PyDicom
- PyQt5
- PyWavelets
- Scikit-image
- Scikit-learn
- SciPy
- SimpleITK
- tqdm

### Radiomics Extraction Pathways
<img src="https://raw.githubusercontent.com/medical-physics-usz/z-rad/master/doc/images/ZRadExtractionPathways.png" width="600" alt="Z-Rad Pathways"/>

## Graphical User Interface (GUI) and Application Programming Interface (API)
Both GUI and API are structured into three primary classes: **Resampling**, **Filtering**, and **Radiomics**:

### Resampling
Z-Rad supports image resampling alone, alongside regions of interest (ROI) masks, or converting DICOM files to NIfTI
images and masks without resampling. Resampling can be performed in 3D or 2D (axial slice-wise), with nearest
neighbors, linear, B-spline, and Gaussian strategies.

### Filtering
This tab requires users to define the desired filter settings.
The current version of Z-Rad supports mean, Laplace of Gaussian, Laws kernels,
and wavelet (Daubechies 2, Daubechies 3, first-order Coiflet, and Haar) filters.

### Radiomics Feature Extraction
Parameters for radiomics feature extraction include the intensity re-segmentation
(e.g., HU for CT or SUV for PET within ROIs) and intensity outlier filtering,
discretisation strategies, and a variety of radiomics feature aggregation methods covering 2D, 2.5D, and 3D options.
Radiomic features include shape, intensity, grey level co-occurrence matrix (GLCM),
grey level run length matrix (GLRLM), grey level distance zone matrix (GLDZM),
neighbouring gray tone difference matrix (NGTDM),
and neighbouring gray level dependance matrix (NGLDM) features families.

## Error and Warning Handling

- **GUI**: Uses warning pop-up messages for immediate feedback.
- **API**: Records processes in log files for comprehensive documentation.

## Installation and Get Started

### Windows executable file:
The simplest way to run Z-Rad on Windows is to start the `z-rad.exe` attached to every Z-Rad release.

Executables can be also generated for Windows, MacOS, and Linux by running
```sh
python generate_executable.py
```
Creating an executable requires [PyInstaller](https://pyinstaller.readthedocs.io).
The executable is going to be saved in *dist/* directory.

### Windows, Linux, and macOS
For users familiar with Python programming langauage, we recommend:

1. Download the Z-Rad repository
2. Open the terminal and navigate to the project directory
3. Install requirements by typing in the terminal:

```sh
pip install -r requirements.txt
```

4. Run the `main.py` file:

```sh
python main.py
```

### API
```sh
pip install z-rad
```

## License

Z-Rad is an open-source project licensed under the MIT License.

## Contact

For any questions or feedback, please contact us at [zrad@usz.ch](mailto:zrad@usz.ch).

---

Raw data

            {
    "_id": null,
    "home_page": null,
    "name": "z-rad",
    "maintainer": null,
    "docs_url": null,
    "requires_python": ">=3.10",
    "maintainer_email": null,
    "keywords": "radiomics, feature-extraction, python, GUI, API",
    "author": null,
    "author_email": "Radiomics Team of Radiation Oncology Department at University Hospital Zurich <zrad@usz.ch>",
    "download_url": "https://files.pythonhosted.org/packages/83/90/f00a261cb6567f6c7a18bc2763d355141bdc6fd56a4ea025459d54b85c84/z_rad-25.9.0.tar.gz",
    "platform": null,
    "description": "# Z-RAD\n\n<img src=\"https://raw.githubusercontent.com/medical-physics-usz/z-rad/master/doc/logos/ZRadLogo.jpg\" width=\"600\" alt=\"Z-Rad logo\"/>\n\nRadiomics is the high-throughput extraction of quantitative features from medical images, \nrevolutionizing personalized medicine and enhancing clinical decision-making. \nDespite its potential, radiomics faces several challenges, including the need for programming skills \nand lack of standardization.\n\n**Z-Rad (Zurich Radiomics)**, developed by the Radiation Oncology Department at the University Hospital Zurich, \naddresses these issues by offering a user-friendly, IBSI-compliant, and open-source solution for radiomics analysis.\n\n## Z-Rad Features\n<img src=\"https://raw.githubusercontent.com/medical-physics-usz/z-rad/master/doc/images/zrad_screenshot.png\" width=\"600\" alt=\"Z-Rad screenshot\"/>\n\n### User-Friendly Interface\n- **Graphical User Interface (GUI)**: Designed for medical professionals with no programming skills.\n- **Application Programming Interface (API)**: Allows researchers to customize, automate, and extend Z-Rad functionalities using Python.\n\n### Compatibility\n- **Medical Data Formats**: Supports CT, PET, and MR imaging modalities in both DICOM and NIfTI formats.\n- **Operating Systems**: Windows, macOS, and Linux.\n\n### Standard Compliance\n- **IBSI Compliance**: Adheres to [IBSI I](https://arxiv.org/abs/1612.07003) and [IBSI II](https://arxiv.org/abs/2006.05470) standards for reproducible and comparable radiomics features.\n\n\n## Software Architecture and Design\n\n### Backend\n- **Programming Language**: Python.\n- **Dependencies**:\n  - Joblib\n  - NumPy\n  - OpenCV\n  - OpenPyXL\n  - Pandas\n  - PyDicom\n  - PyQt5\n  - PyWavelets\n  - Scikit-image\n  - Scikit-learn\n  - SciPy\n  - SimpleITK\n  - tqdm\n\n### Radiomics Extraction Pathways\n<img src=\"https://raw.githubusercontent.com/medical-physics-usz/z-rad/master/doc/images/ZRadExtractionPathways.png\" width=\"600\" alt=\"Z-Rad Pathways\"/>\n\n## Graphical User Interface (GUI) and Application Programming Interface (API)\nBoth GUI and API are structured into three primary classes: **Resampling**, **Filtering**, and **Radiomics**:\n\n### Resampling\nZ-Rad supports image resampling alone, alongside regions of interest (ROI) masks, or converting DICOM files to NIfTI \nimages and masks without resampling. Resampling can be performed in 3D or 2D (axial slice-wise), with nearest \nneighbors, linear, B-spline, and Gaussian strategies.\n\n### Filtering\nThis tab requires users to define the desired filter settings. \nThe current version of Z-Rad supports mean, Laplace of Gaussian, Laws kernels, \nand wavelet (Daubechies 2, Daubechies 3, first-order Coiflet, and Haar) filters.\n\n### Radiomics Feature Extraction\nParameters for radiomics feature extraction include the intensity re-segmentation \n(e.g., HU for CT or SUV for PET within ROIs) and intensity outlier filtering, \ndiscretisation strategies, and a variety of radiomics feature aggregation methods covering 2D, 2.5D, and 3D options. \nRadiomic features include shape, intensity, grey level co-occurrence matrix (GLCM), \ngrey level run length matrix (GLRLM), grey level distance zone matrix (GLDZM), \nneighbouring gray tone difference matrix (NGTDM), \nand neighbouring gray level dependance matrix (NGLDM) features families.\n\n## Error and Warning Handling\n\n- **GUI**: Uses warning pop-up messages for immediate feedback.\n- **API**: Records processes in log files for comprehensive documentation.\n\n## Installation and Get Started\n\n### Windows executable file:\nThe simplest way to run Z-Rad on Windows is to start the `z-rad.exe` attached to every Z-Rad release.\n\nExecutables can be also generated for Windows, MacOS, and Linux by running\n```sh\npython generate_executable.py\n```\nCreating an executable requires [PyInstaller](https://pyinstaller.readthedocs.io).\nThe executable is going to be saved in *dist/* directory.\n\n### Windows, Linux, and macOS\nFor users familiar with Python programming langauage, we recommend: \n\n1. Download the Z-Rad repository\n2. Open the terminal and navigate to the project directory\n3. Install requirements by typing in the terminal:\n\n```sh\npip install -r requirements.txt\n```\n\n4. Run the `main.py` file:\n\n```sh\npython main.py\n```\n\n### API\n```sh\npip install z-rad\n```\n\n## License\n\nZ-Rad is an open-source project licensed under the MIT License.\n\n## Contact\n\nFor any questions or feedback, please contact us at [zrad@usz.ch](mailto:zrad@usz.ch).\n\n---\n",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "Z-Rad is a radiomic feature extraction software with GUI and API.",
    "version": "25.9.0",
    "project_urls": null,
    "split_keywords": [
        "radiomics",
        " feature-extraction",
        " python",
        " gui",
        " api"
    ],
    "urls": [
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "8dbf31ea81f93d90471023c30cf044b8ae558eb84a5310eefc4508a1eac47e9a",
                "md5": "ed57792cab6d8e992e8b2a88dc6b4407",
                "sha256": "41a51f29bffd41bd23f3f606d4388c49a456b1ac9767674be32d61a421c1541b"
            },
            "downloads": -1,
            "filename": "z_rad-25.9.0-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "ed57792cab6d8e992e8b2a88dc6b4407",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": ">=3.10",
            "size": 14271,
            "upload_time": "2025-09-03T11:39:00",
            "upload_time_iso_8601": "2025-09-03T11:39:00.557327Z",
            "url": "https://files.pythonhosted.org/packages/8d/bf/31ea81f93d90471023c30cf044b8ae558eb84a5310eefc4508a1eac47e9a/z_rad-25.9.0-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "8390f00a261cb6567f6c7a18bc2763d355141bdc6fd56a4ea025459d54b85c84",
                "md5": "f252ba5d8bd0f63e3d3ad64f4ae3134f",
                "sha256": "135c84097bbc07431c6d211155157e9dc75838cd963ad35792521b30c5002b1f"
            },
            "downloads": -1,
            "filename": "z_rad-25.9.0.tar.gz",
            "has_sig": false,
            "md5_digest": "f252ba5d8bd0f63e3d3ad64f4ae3134f",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": ">=3.10",
            "size": 21401,
            "upload_time": "2025-09-03T11:39:01",
            "upload_time_iso_8601": "2025-09-03T11:39:01.667557Z",
            "url": "https://files.pythonhosted.org/packages/83/90/f00a261cb6567f6c7a18bc2763d355141bdc6fd56a4ea025459d54b85c84/z_rad-25.9.0.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2025-09-03 11:39:01",
    "github": false,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "lcname": "z-rad"
}

None