Porting hazen to python 3.9

.github/workflows/cli-test.yml

@@ -15,10 +15,10 @@ jobs:
     steps:
     - uses: actions/checkout@v2
 
-    - name: Set up Python 3.6
+    - name: Set up Python 3.9
       uses: actions/setup-python@v2
       with:
-        python-version: 3.6
+        python-version: 3.9.7
 
     - name: Install dependencies
       run: |

.github/workflows/tests_development.yml

@@ -11,6 +11,9 @@ on:
 jobs:
   test:
     runs-on: ubuntu-latest
+    defaults:
+      run:
+        shell: bash -l {0}
     # Service containers to run with `container-job`
     services:
       # Label used to access the service container
@@ -30,20 +33,27 @@ jobs:
           --health-interval 10s
           --health-timeout 5s
           --health-retries 5
-
     steps:
     - uses: actions/checkout@v2
 
-    - name: Set up Python 3.6
-      uses: actions/setup-python@v2
+    - name: Set up Conda
+      uses: conda-incubator/setup-miniconda@v2.1.1
       with:
-        python-version: 3.6
+        activate-environment: anaconda-client-env
+        environment-file: environment.yml
+        python-version: 3.9.7
+        auto-activate-base: false
+
+    - name: Conda info
+      run: conda info
+
+    - name: Conda list
+      run: conda list
 
-    - name: Install dependencies
+    - name: Install flake8 & pytest
       run: |
         python -m pip install --upgrade pip
         pip install flake8 pytest pytest-cov
-        if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
 
     - name: Setup flake8 annotations
       uses: rbialon/flake8-annotations@v1

.github/workflows/tests_release.yml

@@ -35,10 +35,10 @@ jobs:
     steps:
     - uses: actions/checkout@v2
 
-    - name: Set up Python 3.6
+    - name: Set up Python 3.9
       uses: actions/setup-python@v2
       with:
-        python-version: 3.6
+        python-version: 3.9.7
 
     - name: Install dependencies
       run: |

README.md

@@ -1,47 +1,79 @@
 <!-- PROJECT HEADING -->
 <br />
 <p align="center">
-<a href="https://github.com/github_username/repo_name">
-    <img src="https://raw.githubusercontent.com/GSTT-CSC/gstt-csc.github.io/main/assets/transparent-CSC-logo-cropped.png" alt="Logo" width="40%">
-  </a>
-<h1 align="center">Hazen</h1>
+   <img src="https://raw.githubusercontent.com/GSTT-CSC/hazen/readme-dev/docs/assets/ibn-al-haytham.jpeg" alt="Ibn Al-Haytham">
+</p>   
+<h1 align="center">hazen</h1>
 <p align="center">
-Quality assurance framework for Magnetic Resonance Imaging
-<br />
-<a href="https://github.com/github_username/repo_name"><strong>Explore the docs »</strong></a>
-<br />
-<br />
-<a href="https://github.com/GSTT-CSC/hazen">View repo</a>
-·
-<a href="https://github.com/GSTT-CSC/hazen/issues">Report Bug</a>
-·
-<a href="https://github.com/GSTT-CSC/hazen/issues">Request Feature</a>
+   Quality assurance framework for Magnetic Resonance Imaging
+   <br />
+   <a href="https://github.com/github_username/repo_name"><strong>Explore the docs »</strong></a>
+   <br />
+   <br />
+   <a href="https://github.com/GSTT-CSC/hazen">View repo</a>
+   ·
+   <a href="https://github.com/GSTT-CSC/hazen/issues">Report Bug</a>
+   ·
+   <a href="https://github.com/GSTT-CSC/hazen/issues">Request Feature</a>
 </p>
 <p align="center">
   <img src="https://github.com/GSTT-CSC/hazen/actions/workflows/tests_release.yml/badge.svg?branch=master">
   <img src="https://img.shields.io/endpoint?url=https://gist.githubusercontent.com/laurencejackson/ba102d5f3e592fcd50451c2eff8a803d/raw/hazen_pytest-coverage-comment.json">
 </p>
+<p align="center">Please <b>STAR</b> this repo to receive updates about new versions of hazen!</p>
+
+---
 
 ## Overview
 
----
+hazen is a software framework for performing automated analysis of magnetic resonance imaging (MRI) Quality Assurance data.
 
+It provides automatic quantitative analysis for the following measurements of MRI phantom data:
+- Signal-to-noise ratio (SNR)
+- Spatial resolution
+- Slice position and width
+- Uniformity
+- Ghosting
+- MR Relaxometry
 
+Some example outputs from hazen:
 
-## Usage
+| hazen snr          | hazen ghosting                  |
+| ------------------ | ------------------------------- |
+| ![](docs/assets/snr-example.png) | ![](docs/assets/ghosting-example.png)      |
 
 ---
-### Docker
-To use the docker version of hazen simply run the `hazen-app` script in a terminal. Docker must be installed on the host 
-system for this method to work, see [docker installation instructions](https://docs.docker.com/engine/install).
-For ease of use it is recommended to copy the hazen-app script to location accessible on the path such as `/usr/local/bin` 
-so you can run it from any location.
 
-e.g.
+## Installation
+
+### Prerequisites
+
+ - Python v3.9
+   - conda is required for hazen installation on Mac M1 silicon (arm64 architecture)
+ - Git
+ - Docker
+
+### Install
+
+First, clone this repo, then follow the instructions for your operating system. To clone:
 ```bash
+git clone [email protected]:GSTT-CSC/hazen.git
+```
+
+#### Docker
+
+We recommend using the Docker version of hazen as it is easy to get up-and-running and is linked to the most stable release. Refer to the [Docker installation instructions](https://docs.docker.com/engine/install) to install Docker on your host computer.
+
+For ease of use, it is recommended to copy the `hazen-app` script to a location accessible on the path such as `/usr/local/bin`. This will allow you to run hazen from any location on your computer. Then, to use Docker hazen, simply run the `hazen-app` script appended with the function you want to use (e.g.: `snr`). 
+
+In Terminal:
+
+```bash 
+cd hazen
 cp ./hazen-app /usr/local/bin
 
-./hazen-app snr tests/data/snr/Siemens/
+# run hazen
+hazen-app snr tests/data/snr/Siemens/
 
 latest: Pulling from gsttmriphysics/hazen
 Digest: sha256:18603e40b45f3af4bf45f07559a08a7833af92a6efe21cb7306f758e8eeab24a
@@ -55,15 +87,92 @@ docker.io/gsttmriphysics/hazen:latest
     'snr_subtraction_normalised_seFoV250_2meas_slice5mm_tra_repeat_PSN_noDC_2_1': 2154.69}
 ```
 
+#### Linux & MacOS
+
+For developers, hazen can be installed using `pip`. We highly recommend using a virtual environment.
+
+```bash
+# Go to local hazen repo directory
+cd hazen
+
+# Create and activate a virtual environment
+python3 -m venv ./hazen-venv
+source hazen-venv/bin/activate
+
+# Install requirements
+pip install --upgrade pip setuptools wheel
+pip install -r requirements.txt
+
+# Install hazen
+python setup.py install
+
+# Run tests to ensure everything is working
+pytest tests/
+```
+
+#### MacOS using M1 processors (Apple silicon arm64 architecture)
+
+For developers using MacOS with M1 processors, installation via `conda` is required. This is because various Python packages have not been updated to install with `pip`. Installation of hazen via conda is a temporary workaround. 
+
+```bash
+# Download and install conda (we have tested with both Miniforge and Miniconda):
+brew update
+brew upgrade
+brew install miniforge
+
+# Create and activate virtual environment
+conda create --name hazen-venv --file environment.yml
+conda activate hazen-venv
+
+# Build hazen
+cd hazen
+python setup.py install
+
+# Run tests to ensure everything is working
+pytest tests/
+```
+
+---
+
+## Usage
+
+### Command Line
+
+The CLI version of hazen is designed to be pointed at single folders containing DICOM file(s). Example datasets are provided in the `tests/data/` directory. If you are not using the Docker version of hazen, replace `hazen-app` with `hazen` in the following commands.
+
+To perform an SNR measurement on the provided example Philips DICOMs:
+
+`hazen-app snr tests/data/snr/Philips`
+
+To perform a spatial resolution measurement on example data provided by the East Kent Trust:
+
+`hazen-app spatial_resolution tests/data/resolution/philips`
+
+To see the full list of available tools, enter:
+
+`hazen-app -h`
+
+The `--report` option provides additional information for some of the functions. For example, the user can gain additional insight into the performance of the snr function by entering:
+
+`hazen-app snr tests/data/snr/Philips --report`
+
+### Web Interface
+
+WIP: we are developing a web interface for hazen.
+
+---
 
 ## Contributors
 
-Read CONTRIBUTING.md
+If you want to contribute to the development of hazen, please take a look at: `CONTRIBUTING.md`.
 
 ---
 
 ## Users
 
-Nothing to see here. Maybe see hazen/docs.
+Please [raise an Issue](https://github.com/GSTT-CSC/hazen/issues) if you have any problems installing or running hazen.
+
+We have used hazen with MRI data from a handful of different MRI scanners, including multiple different vendors. If your MRI data doesn't work with hazen, or the results are unexpected, please submit an Issue and we will investigate. 
+
+
 
----

contributors.txt

@@ -4,4 +4,6 @@ Dika Vilic
 Elizabeth Gabriel
 Jane Ansell
 Neil Heraghty
+Tom Roberts
+Lucrezia Cester
 Haris Shuaib

environment.yml

@@ -0,0 +1,46 @@
+name: hazen-3.9-miniforge
+
+dependencies:
+  - pip #=21.3.1
+  - python=3.9.7
+  - scikit-image=0.18.3
+  - pip:
+    - SQLAlchemy_Utils==0.33.11
+    - alembic==1.0.10
+    - celery==4.3.1
+    - numpy==1.21.0
+    - Werkzeug==0.15.6
+    - opencv-python==4.5.4.58
+    - Flask_Migrate==2.5.1
+    - pytest>=6.2
+    - coverage>=6.0.2
+    - Flask_Moment==0.7.0
+    - flask_heroku==0.1.9
+    - Flask==1.0.3
+    - pydicom==1.4.1
+    - WTForms==2.2.1
+    - Flask_Dropzone==1.5.3
+    - Flask_Mail==0.9.1
+    - Flask_Login==0.4.1
+    - Flask_Bootstrap4==4.0.2
+    - imutils==0.5.3
+    - matplotlib==3.4.3
+    - Flask_SQLAlchemy==2.4.0
+    - scipy==1.7.2
+    - docopt==0.6.2
+    - SQLAlchemy==1.3.3
+    - Flask_WTF==0.14.2
+    - flask_bootstrap==3.3.7.1
+    - PyJWT==1.7.1
+    - gunicorn==19.9.0
+    - psycopg2-binary==2.8.4
+    - arrow==0.13.2
+    - amqp==2.4.2
+    - sphinxcontrib-needs==0.4.3
+    - sphinxcontrib-napoleon
+    - sphinx_rtd_theme
+    - m2r
+    - python-dateutil
+    - email_validator
+    - colorlog
+

hazenlib/slice_width.py

@@ -362,7 +362,7 @@ def get_initial_trapezoid_fit_and_coefficients(profile, slice_thickness):
         n_ramp = 47
         n_plateau = 55
 
-    trapezoid_centre = round(np.median(np.argwhere(profile < np.mean(profile)))).astype(int)
+    trapezoid_centre = int(round(np.median(np.argwhere(profile < np.mean(profile)))))
 
     n_total = len(profile)
     n_left_baseline = int(trapezoid_centre - round(n_plateau / 2) - n_ramp - 1)

hazenlib/spatial_resolution.py

@@ -174,15 +174,25 @@ def thresh_image(img, bound=150):
 
 
 def find_square(img):
-    cnts = cv.findContours(img.copy(), cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE)
+    cnts = cv.findContours(img.copy(), cv.RETR_LIST, cv.CHAIN_APPROX_SIMPLE)[0]
 
-    for c in cnts[1]:
+    for c in cnts:
         perimeter = cv.arcLength(c, True)
         approx = cv.approxPolyDP(c, 0.1 * perimeter, True)
         if len(approx) == 4:
             # compute the bounding box of the contour and use the
             # bounding box to compute the aspect ratio
             rect = cv.minAreaRect(approx)
+
+            # OpenCV 4.5 adjustment
+            # - cv.minAreaRect() output tuple order changed since v3.4
+            # - swap rect[1] order & rotate rect[2] by -90
+            # – convert tuple>list>tuple to do this
+            rectAsList = list(rect)
+            rectAsList[1] = (rectAsList[1][1], rectAsList[1][0])
+            rectAsList[2] = rectAsList[2] - 90
+            rect = tuple(rectAsList)
+
             box = cv.boxPoints(rect)
             box = np.int0(box)
             w, h = rect[1]

hazenlib/tools.py

@@ -129,6 +129,11 @@ def get_shape(self, shape):
 
         if shape == 'rectangle' or shape == 'square':
             (x,y), size, angle = cv.minAreaRect(contour)
+            # OpenCV v4.5 adjustment
+            # - cv.minAreaRect() output tuple order changed since v3.4
+            # - swap size order & rotate angle by -90
+            size = (size[1], size[0])
+            angle = angle-90
             return (x,y), size, angle