Hepatic vessel segmentation using a reduced filter 3D U-Net in ultrasound imaging

Accurate hepatic vessel segmentation on ultrasound (US) images can be an important tool in the planning and execution of surgery, however proves to be a challenging task due to noise and speckle. Our method comprises a reduced filter 3D U-Net implementation to automatically detect hepatic vasculatur...

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Bibliographic Details
Published in:arXiv.org 2019-07
Main Authors: Thomson, Bart R, Nijkamp, Jasper, Ivashchenko, Oleksandra, van der Heijden, Ferdinand, Smit, Jasper N, Kok, Niels F M, Kuhlmann, Koert F D, Ruers, Theo J M, Fusaglia, Matteo
Format: Article
Language:English
Subjects:
Blood vessels
Image acquisition
Image segmentation
Ultrasonic imaging
Ultrasound
Online Access:Get full text
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Summary:Accurate hepatic vessel segmentation on ultrasound (US) images can be an important tool in the planning and execution of surgery, however proves to be a challenging task due to noise and speckle. Our method comprises a reduced filter 3D U-Net implementation to automatically detect hepatic vasculature in 3D US volumes. A comparison is made between volumes acquired with a 3D probe and stacked 2D US images based on electromagnetic tracking. Experiments are conducted on 67 scans, where 45 are used in training, 12 in validation and 10 in testing. This network architecture yields Dice scores of 0.740 and 0.781 for 3D and stacked 2D volumes respectively, comparing promising to literature and inter-observer performance (Dice = 0.879).
ISSN:2331-8422