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.
Subject(s)
Imaging, Three-Dimensional/methods , Multimodal Imaging/methods , Pattern Recognition, Automated/methods , Prostatic Neoplasms/diagnosis , Subtraction Technique , Ultrasonography/methods , Aged , Humans , Image Enhancement/methods , Image Interpretation, Computer-Assisted/methods , Italy , Machine Learning , Male , Middle Aged , Netherlands , Observer Variation , Reproducibility of Results , Sensitivity and SpecificityABSTRACT
Conventional ultrasound (US) devices use the time of flight (TOF) of reflected US pulses to calculate distances inside the scanned tissues and thus create images. The speed of sound (SOS) is assumed to be constant in all human soft tissues at a generally accepted average value of 1540 m s(-1). This assumption is a source of systematic errors up to several millimeters and of image distortion in quantitative US imaging. In this work, an extension of a method recently published by Fontanarosa et al (2011 Med. Phys. 38 2665-73) is presented: the aim is to correct SOS aberrations in three-dimensional (3D) US images in those cases where a spatially co-registered computerized tomography (CT) scan is also available; the algorithm is then applicable to a more general case where the lines of view (LOV) of the US device are not necessarily parallel and coplanar, thus allowing correction also for US transducers other than linear. The algorithm was applied on a multi-modality pelvic US phantom, scanned through three different liquid layers on top of the phantom with different SOS values; the results show that the correction restores a better match between the CT and the US images, reducing the differences to sub-millimeter agreement. Fifteen clinical cases of prostate cancer patients were also investigated: the SOS corrections of prostate centroids were on average +3.1 mm (max + 4.9 mm-min + 1.3 mm). This is in excellent agreement with reports in the literature on differences between measured prostate positions by US and other techniques, where often the discrepancy was attributed to other causes.
