Fix typos

Author: ObedDzik

paper/paper.md

@@ -7,7 +7,7 @@ tags:
   - spect
   - image reconstruction
 authors:
-  - name: Obed K. Dzikunu
+  - name: Obed Dzikunu
     orcid: 0000-0002-1122-0629
     corresponding: true # (This is how to denote the corresponding author)
     affiliation: "2, 3" # (Multiple affiliations must be quoted)
@@ -22,7 +22,7 @@ authors:
   - name: Luke Polson
     affiliation: "1, 2"    
 affiliations:
- - name: Deparment of Physics & Astronomy, University of British Columbia, Vancouver Canada
+ - name: Department of Physics & Astronomy, University of British Columbia, Vancouver Canada
    index: 1
  - name: Department of Integrative Oncology, BC Cancer Research Institute, Vancouver Canada
    index: 2
@@ -63,19 +63,19 @@ Once the raw data is loaded into the 3D slicer interface, the user can select th
 
 The `System Modeling` component considers the system matrix $H$, as well as additional corrections such as scatter $s$. Selecting `Attenuation Correction` enables attenuation correction during reconstruction; users must specify a corresponding CT image used to generate a mu-map. Selecting `Collimator Detector Response Modeling` enables modeling of the collimator and detector spatial resolution in image reconstruction. Users must specify the collimator code, defined on [the PyTomography data page](https://pytomography.readthedocs.io/en/latest/data_tables/collimator_data.html#collimator-data-index), as well as the intrinsic spatial resolution of the scintillator crystals. Selecting `Scatter Correction` enables scatter correction during reconstruction; users must select the scatter correction method as well as supporting data required for the method.
 
-The third component, likelihoods, considers the likelihood function $L$. Currently, the extension only supports the `PoissonLogLikelihood` likelihood, which correctly describes the data acquired in SPECT imaging. It may be desirable in the future to test alternative likelihood functions, so this is left as a seperate module.
+The third component, likelihoods, considers the likelihood function $L$. Currently, the extension only supports the `PoissonLogLikelihood` likelihood, which correctly describes the data acquired in SPECT imaging. It may be desirable in the future to test alternative likelihood functions, so this is left as a separate module.
 
 The fourth component, algorithms, considers the reconstruction algorithm $A$. Currently, the extension supports the ordered subset expectation maximum (OSEM) [@osem], block sequential regularized expectation maximum (BSREM) [@BSREM] and ordered subset maximum a posteriori one step late (OSMAPOSL) [@OSL] algorithms. Regularized algorithms can use the quadratic, log-cosh, and relative difference penalty [@RDP] priors; these priors can also utilize a provided anatomical image to modify the weighting by only including contributions from the top N neighbours. Additional algorithms may be added based on community request.
 
  The `Data Converters` component permits the conversion of raw SPECT data from various file formats (such as `SIMIND` [@simind] and `GATE` [@gate]) into DICOM format so it can be loaded using the native data readers of `3D Slicer`. While the extension currently has support for the conversion of `SIMIND` data, more data converters may be added in the future depending on community request. The `Post-Reconstruction` component contains functionality that is applicable for use on reconstructed images. One such example is the computation of uncertainty on total counts within segmented regions of interest.
 
 \autoref{fig:fig1} contains a screenshot of the extension along with a sample reconstructed image in the 3D Slicer viewer.   
 
-![Left: user interface for the proposed extension. Right: reconstructed coronal slice from a patient receiving ${}^{177}$Lu-PSMA-617 radiopharmaceutical therapy (color) overlayed on a corresponding CT (greyscale). Raw SPECT data consisted of two bed positions that were automatically stitched together after each was reconstructed; the raw data was acquired on a GE Discovery 670 camera.\label{fig:fig1}](with_recon.png)
+![Left: user interface for the proposed extension. Right: reconstructed coronal slice from a patient receiving ${}^{177}$Lu-PSMA-617 radiopharmaceutical therapy (color) overlaid on a corresponding CT (greyscale). Raw SPECT data consisted of two bed positions that were automatically stitched together after each was reconstructed; the raw data was acquired on a GE Discovery 670 camera.\label{fig:fig1}](with_recon.png)
 
 
 # Acknowledgements
 
 We would like to acknowledge Peyman Sh.Zadeh from the Faculty of Medicine at the Tehran University of Medical Science for providing the patient data used in the paper. Also, we acknowledge funding from the Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery Grant RGPIN-2019-06467, and Canadian Institutes of Health Research (CIHR) Project Grant PJT-162216.
 
-# References
+# References