imagingTable.Rmd

---
title: "**Imaging Platforms**"
output: html_document
---

### **Overview**

The following table contains a list of imaging informatics platforms. These platforms work with several imaging data types, ranging from pathology imaging to radiographic imaging. These platforms allow researchers to create custom workflows, view and interact with analysis results, utilize imaging algorithms, as well as visualize and report analysis results.

```{r,echo=FALSE,results='hide',,message=FALSE, warning=FALSE}
#Load DT, dplyr
library(DT)
#library(dplyr)
library(here)
library(tidyverse)
library(magrittr)
#library(RCurl)
```

**Table keys:**
<div title="Table keys">
<img src="resources/images/Hyperlink2.png"  height="30"> </img> = Main Link, <img src="resources/images/Documentation2.png" height="30"> </img> = Documentation, <img src="resources/images/Publication2.png" height="30"> </img> = Publications, &nbsp; <img src="ITCRLogo.png" height="25"> </img> = ITCR Funded
</div>

```{r,echo=FALSE,results='hide',,message=FALSE, warning=FALSE}
# Load file for Imaging Table and make any additions/edits within this block
imaging <- read_csv(file = here::here("data/itcr_table_imaging.csv"))

## CaPTk: Submitted 06/01/2023, 11:12 (sbakas@upenn.edu)
new_imaging_CaPTk <- tibble(
  Name = "The Cancer Imaging Phenomics Toolkit (CaPTk)",
  `Link (Hyperlinked Over Name)` = "https://www.med.upenn.edu/cbica/captk/",
  Subcategories = "Radiomics",
  `Unique Factor` = "CaPTk is a stand-alone software client that allows for free image analysis through the Image Processing Portal (IPP) that offers compute power through CaPTk's supporting high performance computing cluster.",
  `Data Types (Clean)` = "Radiographic Imaging",
  Price = "Free",
  Documentation = "https://cbica.github.io/CaPTk/",
  `Data Provided` = "Sample Data available within CaPTk",
  Publications = "https://doi.org/10.1117/1.jmi.5.1.011018",
  `Summary` = "CaPTk is a software platform for analysis of radiographic cancer images, currently focusing on brain, breast, and lung cancer that integrates advanced, validated tools performing various aspects of medical image analysis, that have been developed in the context of active clinical research studies and collaborations toward addressing real clinical needs. CaPTk aims to facilitate the swift translation of advanced computational algorithms into routine clinical quantification, analysis, decision making, and reporting workflow.",
  Funding = "Yes",
  PLink = "https://github.com/CBICA/CaPTk/#downloads")

## Add new rows to the existing dataset
imaging <- dplyr::rows_insert(imaging, new_imaging_CaPTk, conflict = "ignore")
```

```{r,echo=FALSE,results='hide',,message=FALSE, warning=FALSE}
# Mutate the tibble to alter three of the columns
modified_imaging <- formatTheTables(imaging, "Imaging", non_resource = TRUE)

# save to the data folder
#write_csv(modified_imaging, file = "data/modified_imaging.csv")
```

```{r,echo=FALSE,results='hide',message=FALSE, warning=FALSE}
# Create an Imaging Table

columnDefsListOfLists <- list(list(className = 'dt-center', targets = "_all"),
                                     list(width = '280px', targets = c(2)) ,
                                     list(width = '130px', targets = c(3))
                              )

ITCR_imaging <- setup_dt_datatable(modified_imaging, columnDefsListOfLists)
```

```{r,echo=FALSE,message=FALSE, warning=FALSE}
#Display the imaging table
ITCR_imaging
```