Couch Elimination
One of the main steps in data preparation for the deep learning models is to remove non-related components/regions from the input images to enhance the overall efficiency of the model. To this end, the couches were removed from the input CT images by applying an intensity-based thresholding method. To remove the couches from the entire slices, a CT intensity profile in the posterior-anterior direction was drawn to detect the coach intensity ranges (− 405 HU < couch intensity <  − 340 HU) (Fig. Intensity-based thresholding approach was employed to remove couches from CT images. Left: an example of a 2D CT image with a line profile in the posterior-anterior direction. Right: CT intensity profile along the line depicted on the CT image shows the specific intensity of the CT couchFurthermore, the original CT images, stored in a 512 × 512 matrix, were cropped to a 256 × 512 matrix to fit the body contour in order to enhance memory and computational efficiencies and image were checked to avoid removing body regions in cropped images.