AUTOMATED COMPUTED TOMOGRAPHY-ULTRASOUND CROSS-MODALITY 3-D CONTOURING ALGORITHM FOR PROSTATE

Denis Ermacora, Silvia Pesente, Francesco Pascoli, Sebastian Raducci, Rudy Mauro, Imad Abu Rumeileh, Frank Verhaegen, Davide Fontanarosa*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

A novel fully automated algorithm is introduced for 3-D cross-modality image segmentation of the prostate, based on the simultaneous use of co-registered computed tomography (CT) and 3-D ultrasound (US) images. By use of a Gabor feature detector, the algorithm can outline in three dimensions and in cross-modality the prostate, and it can be trained and optimized on specific patient populations. We applied it to 16 prostate cancer patients and evaluated the conformity between the automatically segmented prostate contours and the contours manually outlined by an experienced physician, on the CT-US fusion, using the mean distance to conformity (MDC) index. When only the CT scans were used, the average MDC value was 4.5 +/- 1.7 mm (maximum value - 9.0 mm). When the US scans also were considered, the mean +/- standard deviation was reduced to 3.9 +/- 0.7 mm (maximum value = 5.5 mm). The cross-modality approach acted on all the largest distance values, reducing them to acceptable discrepancies. (E-mail: [email protected])
Original languageEnglish
Pages (from-to)2646-2662
JournalUltrasound in Medicine and Biology
Volume41
Issue number10
DOIs
Publication statusPublished - Oct 2015

Keywords

  • Ultrasound imaging
  • Computed tomography imaging
  • Automated image segmentation
  • Cross-modality
  • Radiotherapy
  • Image-guided radiation therapy

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