A Lumen Segmentation Method in Ureteroscopy Images based on a Deep Residual U-Net architecture

01/13/2021
by   Jorge F. Lazo, et al.
0

Ureteroscopy is becoming the first surgical treatment option for the majority of urinary affections. This procedure is performed using an endoscope which provides the surgeon with the visual information necessary to navigate inside the urinary tract. Having in mind the development of surgical assistance systems, that could enhance the performance of surgeon, the task of lumen segmentation is a fundamental part since this is the visual reference which marks the path that the endoscope should follow. This is something that has not been analyzed in ureteroscopy data before. However, this task presents several challenges given the image quality and the conditions itself of ureteroscopy procedures. In this paper, we study the implementation of a Deep Neural Network which exploits the advantage of residual units in an architecture based on U-Net. For the training of these networks, we analyze the use of two different color spaces: gray-scale and RGB data images. We found that training on gray-scale images gives the best results obtaining mean values of Dice Score, Precision, and Recall of 0.73, 0.58, and 0.92 respectively. The results obtained shows that the use of residual U-Net could be a suitable model for further development for a computer-aided system for navigation and guidance through the urinary system.

READ FULL TEXT

page 2

page 5

04/17/2020

Multi-Scale Supervised 3D U-Net for Kidneys and Kidney Tumor Segmentation

Accurate segmentation of kidneys and kidney tumors is an essential step ...
05/31/2021

Refined Deep Neural Network and U-Net for Polyps Segmentation

The Medico: Multimedia Task 2020 focuses on developing an efficient and ...
04/27/2020

OR-UNet: an Optimized Robust Residual U-Net for Instrument Segmentation in Endoscopic Images

Segmentation of endoscopic images is an essential processing step for co...
10/27/2021

QU-net++: Image Quality Detection Framework for Segmentation of 3D Medical Image Stacks

Automated segmentation of pathological regions of interest has been show...
01/13/2022

Realistic Endoscopic Image Generation Method Using Virtual-to-real Image-domain Translation

This paper proposes a realistic image generation method for visualizatio...
06/30/2020

Hand-drawn Symbol Recognition of Surgical Flowsheet Graphs with Deep Image Segmentation

Perioperative data are essential to investigating the causes of adverse ...