diff --git a/joss/paper.md b/joss/paper.md index 00960c158921d354f8671e9697950700f7b91a64..e6d4ede308d231327947a68089988c916b99126d 100644 --- a/joss/paper.md +++ b/joss/paper.md @@ -22,7 +22,7 @@ bibliography: paper.bib --- # Summary -The increasing accessibility of digitised surface scanners are giving users the ability to accurately digitise the 3D surface geometry of real world objects which may then be 3D printed. In addition to hobbyist applications, these devices are being increasingly used within prosthetics and orthotics clinics where they are used to capture the patients individual geometry. These scans are imported into computer-aided design packages to generate patient-specific medical devices, such as prosthetic sockets or ankle-foot orthosis. This increasing digitsiation of patient data provides great potential for analysis of these scans in order to inform and improve clinical practice. While this has been an area of academic interest for several decades [@Sanders: 2005], clinical use is minimal. One of the reasons for this is the lack of tools available for clinicians to analyse the geometry of their patient datasets. +The increasing accessibility of surface scanners are giving users the ability to accurately digitise the 3D surface geometry of real world objects which may then be 3D printed. In addition to hobbyist applications, these devices are being increasingly used within prosthetics and orthotics clinics where they are used to capture the patients individual geometry. These scans are imported into computer-aided design packages to generate patient-specific medical devices, such as prosthetic sockets or ankle-foot orthosis. This increasing digitsiation of patient data provides great potential for analysis of these scans in order to inform and improve clinical practice. While this has been an area of academic interest for several decades [@Sanders: 2005], clinical use is minimal. One of the reasons for this is the lack of tools available for clinicians to analyse the geometry of their patient datasets. In a previously published paper [@Dickinson:2016], a method was detailed for comparing between pairs of surface scans using alignment, registration and visualisation. In this paper, this method was used for evaluation of the accuracy and inter- and intra-reliability of the scanners. Further studies have also demonstrated using this package for comparing the consistency of casting techniques [Dickinson: APOSM], statistical shape modeling across the population [@Worsley: ISPO World] and quantifying rectifications between the residual limb and the prosthetic socket [@Steer: AOPA]. @@ -30,7 +30,7 @@ In a previously published paper [@Dickinson:2016], a method was detailed for com This method was written in MATLAB, however, this was considered restrictive for other researchers to access as they may not possess a MATLAB license. In order to maximise access to the developed techniques and improve performance, especially for 3D visualisation, the methods were rewritten from scratch within Python, including updated algorithms for each stage of the aforementioned process. -The AmpScan package has been designed with clinical researchers in mind, with an appreciation that they may not have an extensive background in coding. To this aim, this software has been developed in Python and leverages the commonly used libraries of NumPy, SciPy, matplotlib, vtk and pyqt. As such, full functionality of the software can be accessed without requiring additional installs. The core analysis of the package can be carried out with, additionally, a simple GUI has been supplied to allow the user to access the core functionality of AmpScan without scripting. +The AmpScan package has been designed with clinical researchers in mind, with an appreciation that they may not have an extensive background in coding. To this aim, the software has been developed in Python and leverages the commonly used libraries of NumPy, SciPy, matplotlib, vtk and pyqt. As such, full functionality of the software can be accessed without requiring additional installs. The core analysis of the package can be carried out with, additionally, a simple GUI has been supplied to allow the user to access the core functionality of AmpScan without scripting. The core functionality of AmpScan is summarised below with a more detailed description available in the online [documentation](https://ampscan.readthedocs.io/en/latest/): - **[AmpObject](https://ampscan.readthedocs.io/en/latest/source/AmpScan.html#AmpScan.core.AmpObject)**: this is the key object of the package and holds the key data and methods. The key data held within the AmpObject is the mesh data including arrays of the vertices, faces, normals and field values. Additionally, the vtk actor for visualisation is also stored. The [core](https://ampscan.readthedocs.io/en/latest/source/core.html) methods of the AmpObject include imports for .stl files, saving .stl files, rotation and translation. Additional methods are added via mixins for [analysis](https://ampscan.readthedocs.io/en/latest/source/analyse.html), [smoothing](https://ampscan.readthedocs.io/en/latest/source/smooth.html), [trimming](https://ampscan.readthedocs.io/en/latest/source/trim.html) and [visualisation](https://ampscan.readthedocs.io/en/latest/source/ampVis.html).