# Quantification of Liver Fibrosis--A Comparative Study
## 3 Literature Review
### Image Analysis Method
#### 3.5.2 DIA Systems Using Manual Thresholding
The higher magnification did not result in any noticeable difference in fibrosis measurement, therefore the magnification of \(\times 40\) was chosen. More technically, interactive thresholding was applied to eachimage sample to highlight the area of fibrosis, followed by binary conversion, so that the CPA could be measured by direct pixel counting. All digitized images in [PERSON] et al. [26] were edited with the Adobe Photoshop 5.02i (Adobe Systems Inc., San Jose, CA, USA) environment. In particular, fibrosis appeared as blue-colored tissue, and then, National Institute of Health (NIH, Bethesda, MD, USA) image software was used for the quantification of the fibrotic areas. In [PERSON] et al. [27], the image analysis system was based on the Image-Pro plus 6.0 software. According to the research team, the magnification of \(\times\)40 was the ideal choice, where the image size consisted of \(1280\times 960\) pixels. The light intensity was adjusted according to the magnification level and three non-overlapping visual fields were randomly selected. Subsequently, the areas of red collagen fibers in each visual field were measured according to Equation (1), in which the total area of the biopsy sample indicated the sum of the three visual fields. [PERSON] et al. [30; 31] measured the CPA in liver biopsy images using the Zeiss KS300 (Zeiss, Hertfordshire, UK) image analysis software. Both the threshold estimation and the artifact elimination have been performed manually for each image according to the utilities of the software. The same stands for [PERSON] et al. [32], where the Zeiss KS300 was the system of choice. Here, the digital image analysis process included a manual RGB threshold for the elimination of unnecessary artifacts, as well as the quantitative measurement of nodule size, septal width, and fibrous tissue expressed in CPA. Several works including both [PERSON] et al. studies [33; 34] operated the Aperio ImageScope (Aperio, Vista, CA, USA) software for manually processing the liver images. The optimal threshold for positive pixel values corresponding to the areas of Sirius red or Masson's trichrome staining was determined by the ImageScope software and by parameterizing the hue and color saturation values. As a result, a binary image was exported, and the CPA was expressed as the percentage of positive pixels to the total number of pixels. [PERSON] et al. [36] also benefited from using ImageScope (version 10.0), for including large portal tracts and vessels within each scanned slide. Batch analysis was then performed on every image using the Aperio PixelCount (version 9) algorithm, which calculated the prevalence ratio of positive disease pixels (Equation (1)). Another manual approach for the quantification of the fibrosis percentage was proposed by [PERSON] et al. [37]. This work used techniques from Adobe Photoshop to extract the pixels of the stained tissue, as well as the fibrosis areas. The regions of interest were extracted by thresholding different channels of the image. In [PERSON] et al. [38], each sample was digitized using a magnification of \(\times\)40. All images were captured, providing a maximum resolution of \(3748\times 2736\) pixels as 24-bit RGB Joint Photographic Experts Group (JPEG) images. By applying several commands in Adobe Photoshop, the background and other undesired elements were excluded. Then, the red/magenta area of the biopsy specimen, corresponding to the fibrotic tissue, was selected and the fibrosis index (FI) calculation, expressed as a percentage of red pixels throughout the entire tissue region, was finally applied. [PERSON] et al. [41] edited all histological images using the Adobe Photoshop CS6 platform to exclude collagenous structures that were mainly structural, such as portal tracts, liver capsules, and others. The threshold was set by consensus between hepatologists and pathologists. The stained collagen and the tissue regions were calculated in pixels by using the Image-Pro 7.0 software (Media Cybernetics Inc., Rockville, MD, USA).