Onal S, Lai-Yuen S, Bao P, Weitzenfeld A, Greene K, Kedar R, Hart S
Department of Industrial & Management Systems Engineering, University of South Florida, 4202 East Fowler Avenue, ENB 118, Tampa, FL, 33620, USA,
Int Urogynecol J. 2014 Jun;25(6):767-73. doi: 10.1007/s00192-013-2287-4. Epub 2014 Jan 16.
The objective of this study was to assess the performance of a semiautomated pelvic floor measurement algorithmic model on dynamic magnetic resonance imaging (MRI) images compared with manual pelvic floor measurements for pelvic organ prolapse (POP) evaluation.
We examined 15 MRIs along the midsagittal view. Five reference points used for pelvic floor measurements were identified both manually and using our semiautomated measurement model. The two processes were compared in terms of accuracy and precision.
The semiautomated pelvic floor measurement model provided highly consistent and accurate locations for all reference points on MRI. Results also showed that the model can identify the reference points faster than the manual-point identification process.
The semiautomated pelvic floor measurement model can be used to facilitate and improve the process of pelvic floor measurements on MRI. This will enable high throughput analysis of MRI data to improve the correlation analysis with clinical outcomes and potentially improve POP assessment.
本研究的目的是评估一种半自动盆底测量算法模型在动态磁共振成像（MRI）图像上的性能，并与用于盆腔器官脱垂（POP）评估的手动盆底测量进行比较。
我们沿正中矢状面检查了15幅MRI图像。通过手动和使用我们的半自动测量模型确定了用于盆底测量的五个参考点。在准确性和精确性方面对这两个过程进行了比较。
半自动盆底测量模型为MRI上的所有参考点提供了高度一致且准确的位置。结果还表明，该模型比手动点识别过程能更快地识别参考点。
半自动盆底测量模型可用于促进和改进MRI上的盆底测量过程。这将使MRI数据的高通量分析成为可能，以改善与临床结果的相关性分析，并有可能改善POP评估。
