WIP: Added some more text, references and figures to the initial vers…

…ion of the JOSS paper. ALive-research#260

paper.bib

@@ -1,4 +1,4 @@
-@article{10.1038/sj.bjc.6603033,
+@article{Simmonds:2006,
         year = {2006},
         title = {{Surgical resection of hepatic metastases from colorectal cancer: A systematic review of published studies}},
         author = {Simmonds, P C and Primrose, J N and Colquitt, J L and Garden, O J and Poston, G J and Rees, M},
@@ -12,7 +12,7 @@ @article{10.1038/sj.bjc.6603033
         volume = {94}
 }
 
-@article{10.1007/s11548-013-0937-0,
+@article{Hansen:2014,
         year = {2014},
         title = {{Impact of model-based risk analysis for liver surgery planning}},
         author = {Hansen, C. and Zidowitz, S. and Preim, B. and Stavrou, G. and Oldhafer, K. J. and Hahn, H. K.},
@@ -25,7 +25,7 @@ @article{10.1007/s11548-013-0937-0
         volume = {9}
 }
 
-@article{10.1007/s00464-010-0915-3,
+@article{Lamata:2010,
        year = {2010},
        title = {{Use of the Resection Map system as guidance during hepatectomy}},
        author = {Lamata, Pablo and Lamata, Félix and Sojar, Valentin and Makowski, Piotr and Massoptier, Laurent and Casciaro, Sergio and Ali, Wajid and Stüdeli, Thomas and Declerck, Jérôme and Elle, Ole Jakob and Elle, Ole Jackov and Edwin, Bjørn and Edwin, Björn},
@@ -39,7 +39,7 @@ @article{10.1007/s00464-010-0915-3
        volume = {24}
 }
 
-@article{10.1016/j.cmpb.2017.03.019,
+@article{Palomar:2017,
        year = {2017},
        rating = {0},
        title = {{A novel method for planning liver resections using deformable Bézier surfaces and distance maps}},
@@ -54,3 +54,38 @@ @article{10.1016/j.cmpb.2017.03.019
        language = {English},
        month = {06}
 }
+
+@book{Preim:2013,
+  title={Visual computing for medicine: theory, algorithms, and applications},
+  author={Preim, Bernhard and Botha, Charl P},
+  year={2013},
+  publisher={Newnes}
+}
+@article{Warmann:2016,
+  title={Computer-assisted surgery planning in children with complex liver tumors identifies variability of the classical Couinaud classification},
+  author={Warmann, Steven W and Schenk, Andrea and Schaefer, Juergen F and Ebinger, Martin and Blumenstock, Gunnar and Tsiflikas, Ilias and Fuchs, Joerg},
+  journal={Journal of Pediatric Surgery},
+  volume={51},
+  number={11},
+  pages={1801--1806},
+  year={2016},
+  publisher={Elsevier}
+}
+@article{Bismuth:2013,
+  title={Revisiting liver anatomy and terminology of hepatectomies},
+  author={Bismuth, Henri},
+  journal={Annals of surgery},
+  volume={257},
+  number={3},
+  pages={383--386},
+  year={2013},
+  publisher={LWW}
+}
+@incollection{Kikinis:2013,
+  title={3D Slicer: a platform for subject-specific image analysis, visualization, and clinical support},
+  author={Kikinis, Ron and Pieper, Steve D and Vosburgh, Kirby G},
+  booktitle={Intraoperative imaging and image-guided therapy},
+  pages={277--289},
+  year={2013},
+  publisher={Springer}
+}

paper.md

@@ -8,7 +8,7 @@ tags:
   - Geometric modelling
 authors:
   - name: Rafael Palomar
-    orcid: 0000-0000-0000-0000
+    orcid: 0000-0002-9136-4154
     equal-contrib: true
     corresponding: true
     affiliation: "1, 2" # (Multiple affiliations must be quoted)
@@ -21,15 +21,11 @@ authors:
     equal-contrib: true # (This is how you can denote equal contributions between multiple authors)
     affiliation: 1
   - name: Ole V. Solberg
-    orcid: 0000-0000-0000-0000
+    orcid: 0009-0004-9488-3621
     equal-contrib: true # (This is how you can denote equal contributions between multiple authors)
     affiliation: 3
   - name: Geir Arne Tangen
-    orcid: 0000-0000-0000-0000
-    affiliation: 3
-  - given-names: Ludwig
-    dropping-particle: van
-    surname: Beethoven
+    orcid: 0000-0003-0032-8500
     affiliation: 3
 affiliations:
  - name: The Intervention Centre, Oslo University Hospital, Oslo, Norway
@@ -50,7 +46,7 @@ aas-journal: Astrophysical Journal <- The name of the AAS journal.
 # Summary
 
 This paper introduces SlicerLiver, a software extension to the [3D Slicer](https://slicer.org "3D Slicer")
-image computing platform. The software address challenges in liver surgery planning by 
+image computing platform [@Kikinis:2013]. The software address challenges in liver surgery planning by 
 applying geometric modeling and artificial intelligence to generate liver tumor 
 resection plans for complex cases, developing parameterized patient-specific 
 vascular models, and creating computational methods for resection visualization 
@@ -63,49 +59,62 @@ planning and potentially improving patient outcomes.
 
 Liver cancer, both primary and secondary types, is a global health concern with 
 increasing incidence rates [1]. Surgical resection is the most effective treatment 
-for some of these cancers [2], and the evolution of computer-assisted surgical systems 
+for some of these cancers [@Simmonds:2006], and the evolution of computer-assisted surgical systems 
 over the past two decades has significantly improved tumor localization and surgeons 
-confidence during surgery [3], [4]. However, despite these advances, several challenges 
+confidence during surgery [@Hansen:2014], [@Lamata:2010]. However, despite these advances, several challenges 
 remain in liver surgical practice.
 While patient-specific 3D models are systematically generated for surgical planning 
 and guidance, surgery planning remains a manual process. This is particularly problematic 
 for patients with multiple metastases, where manual surgery planning becomes intricate. 
 The current techniques for planning virtual resections, namely, drawing-on-slices and 
-deformable surfaces [5], [6], have shown limitations. Therefore, there is a pressing 
+deformable surfaces [@Preim:2013], [@Palomar:2017], have shown limitations. Therefore, there is a pressing 
 need for new algorithms capable of generating precise, rapid, and straightforward 
 resection plans, even in complex cases.
 
 
-# Mathematics
-
-Single dollars ($) are required for inline mathematics e.g. $f(x) = e^{\pi/x}$
-
-Double dollars make self-standing equations:
-
-$$\Theta(x) = \left\{\begin{array}{l}
-0\textrm{ if } x < 0\cr
-1\textrm{ else}
-\end{array}\right.$$
-
-You can also use plain \LaTeX for equations
-\begin{equation}\label{eq:fourier}
-\hat f(\omega) = \int_{-\infty}^{\infty} f(x) e^{i\omega x} dx
-\end{equation}
-and refer to \autoref{eq:fourier} from text.
-
-# Citations
-
-Citations to entries in paper.bib should be in
-[rMarkdown](http://rmarkdown.rstudio.com/authoring_bibliographies_and_citations.html)
-format.
-
-If you want to cite a software repository URL (e.g. something on GitHub without a preferred
-citation) then you can do it with the example BibTeX entry below for @fidgit.
-
-For a quick reference, the following citation commands can be used:
-- `@author:2001`  ->  "Author et al. (2001)"
-- `[@author:2001]` -> "(Author et al., 2001)"
-- `[@author1:2001; @author2:2001]` -> "(Author1 et al., 2001; Author2 et al., 2002)"
+# Implementation
+
+# Results
+
+**Improved Definition of Virtual Resections**
+We developed computer-aided preoperative planning systems \autoref{fig:1},
+streamlining the resection planning process and introducing
+real-time 3D cutting path visualization. Our approach empowers surgeons to make decisions based on individual patient
+needs, enhancing outcomes for both atypical and anatomical
+resections. Notably, our proposed a new resection method
+aiming to obtain better parenchyma preservation compared to
+existing methods.
+**Improved Visualization of Virtual Resections**
+We successfully implemented the Resectograms method (Fig. 1.b),
+a real-time 2D representation of resections within the ALive
+project. The Resectogram provides an intuitive and occlusionfree visualization of virtual liver resection plans, with three
+components: resection cross-section, resection anatomy segments, and resection safety margins. Notably, Resectograms
+effectively identify and characterize invalid resection types due
+to inadequate visualization during virtual planning, thus improving surgical accuracy and decision-making. Resectograms
+enhance the liver surgery workflow, empowering surgeons with
+valuable insights for optimized liver resection strategies and
+improved patient outcomes.
+**Improved Classification of Liver Segments**
+As part of the ALive project, our study introduces a novel approach to
+segmenting liver functional segments \autoref{fig:3}. The method
+uses the liver morphology, the interior vascular network,
+and user-defined landmarks to provide enhanced flexibility in
+marker placement, distinguishing it from existing methods. By
+departing from the standardized Couinaud classification, our
+approach enables a more individualized representation of liver
+segmental distribution. Particularly noteworthy is the method’s
+accurate estimation of the challenging Segment 1, resulting in
+a comprehensive and precise segmentation of the caudate lobe.
+While improvements, particularly in automating the landmark
+marking process, are needed, our approach holds significant
+promise for improving liver surgery planning and has the
+potential to optimize surgical outcomes within the broader
+context of the ALive project.
+
+
+
+![Specification of a virtual resection with visualization of safety margins.\label{fig:1}](Screenshots/Slicer-Liver_screenshot_04.png)
+![Visializing liver segments.\label{fig:3}](Screenshots/Slicer-Liver_screenshot_14.jpg)
 
 # Figures
 
@@ -117,8 +126,7 @@ Figure sizes can be customized by adding an optional second parameter:
 ![Caption for example figure.](figure.png){ width=20% }
 
 # Acknowledgements
+This work was conducted as part of the ALive project, funded by the Research Council of Norway under IKTPLUSS (grant nr. 311393).
 
-We acknowledge contributions from Brigitta Sipocz, Syrtis Major, and Semyeong
-Oh, and support from Kathryn Johnston during the genesis of this project.
 
 # References