| Input: OCT Image for Processing. |
| Output: Return the ROI Segmented Portion. |
| Step-1: Flush out all the cache images and accumulate the input image from the respective system. |
| Step-2: Define the variable to acquire the image with specific format inclusions. |
| Step-3: Use the function for reading the image called “imread” to obtain the input image into the created object on Step-2. |
| Step-4: Crop the selected OCT image by using image cropping function called “imcrop”. |
| Step-5: Show the Cropped portion of the image to the user to select the respective ROI area from that noise free image. |
| Pseudocode: |
| clear all_cache; |
| [F_name, p_name] = UI_get_file[{“.jpg; .png; .tif”},“Image_File_Formats”]; |
| Def I = imread(p_name F_name); |
| I = imresize(I,[256 256]); |
| out = imcrop(I); img_show(out); |
| Step-6: Analyze the Red, Green and Blue (RGB) color portions of the ROI selected and processed image. |
| Pseudocode: |
| Red_plane = out[:,:,1]; Green_plane = out[:,:,2]; Blue_plane = out[:,:,3]; |
| Step-7: Plot the selected portions to the user view for identification and validations. |
| Pseudocode: |
| Subplot(1); image_show[out]; image_head[“ROI”]; |
| Subplot(2); image_show[Red_plane]; image_head[“Red_Palne”]; |
| Subplot(3); image_show[Green_plane]; image_head[“Green_Plane”]; |
| Subplot(4); image_show[Blue_plane]; image_head[“Blue_Plane”]; |
| ROI_img = image[Red_plane, Green_plane, Blue_plane]; |
| Step-8: Return the ROI Selected image for further processing. |
| Pseudocode: |
| return ROI_img; |