Fully automated segmentation of bladder sac and measurement of detrusor wall thickness from transabdominal ultrasound images

Zeynettin Akkus, Bae Hyung Kim, Rohit Nayak, Adriana Gregory, Azra Alizad, Mostafa Fatemi

Research output: Contribution to journalLetterpeer-review

Abstract

Ultrasound measurements of detrusor muscle thickness have been proposed as a diagnostic biomarker in patients with bladder overactivity and voiding dysfunction. In this study, we present an approach based on deep learning (DL) and dynamic programming (DP) to segment the bladder sac and measure the detrusor muscle thickness from transabdominal 2D B-mode ultrasound images. To assess the performance of our method, we compared the results of automated methods to the manually obtained reference bladder segmentations and wall thickness measurements of 80 images obtained from 11 volunteers. It takes less than a second to segment the bladder from a 2D B-mode image for the DL method. The average Dice index for the bladder segmentation is 0.93 ± 0.04 mm, and the average root-mean-square-error and standard deviation for wall thickness measurement are 0.7 ± 0.2 mm, which is comparable to the manual ground truth. The proposed fully automated and fast method could be a useful tool for segmentation and wall thickness measurement of the bladder from transabdominal B-mode images. The computation speed and accuracy of the proposed method will enable adaptive adjustment of the ultrasound focus point, and continuous assessment of the bladder wall during the filling and voiding process of the bladder.

Original languageEnglish (US)
Article number4175
Pages (from-to)1-11
Number of pages11
JournalSensors (Switzerland)
Volume20
Issue number15
DOIs
StatePublished - Aug 1 2020

Keywords

  • Bladder segmentation
  • Deep learning
  • Detrusor muscle thickness
  • Dynamic programming
  • Transabdominal ultrasound

ASJC Scopus subject areas

  • Analytical Chemistry
  • Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Instrumentation
  • Electrical and Electronic Engineering

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