Comparison of image pre-processing methods in liver segmentation task

Automatic liver segmentation of Computed Tomography (CT) images is becoming increasingly important. Although there are many publications in this field there is little explanation why certain pre-processing methods were utilised. This paper presents a comparison of the commonly used approach of Hounsfield Units (HU) windowing, histogram equalisation, and a combination of these methods to try to ascertain what are the differences between them and how big the differences are. All experiments were conducted on the LiTS dataset. To achieve comparable and reliable results only one architecture of neural network is used which is U-Net with ResNet34 blocks.