Is STAPLE algorithm confident to assess segmentation methods in PET imaging?

Dewalle-Vignion Anne-Sophie; Betrouni Nacim; Baillet Clio; Vermandel Maximilien

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Is STAPLE algorithm confident to assess segmentation methods in PET imaging?

机译：STAPLE算法是否有信心评估PET成像中的分割方法？

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Accurate tumor segmentation in [F-18]-fluorodeoxyglucose positron emission tomography is crucial for tumor response assessment and target volume definition in radiation therapy. Evaluation of segmentation methods from clinical data without ground truth is usually based on physicians' manual delineations. In this context, the simultaneous truth and performance level estimation (STAPLE) algorithm could be useful to manage the multi-observers variability. In this paper, we evaluated how this algorithm could accurately estimate the ground truth in PET imaging.

机译：[F-18]-氟脱氧葡萄糖正电子发射断层显像中的准确肿瘤分割对于放射治疗中的肿瘤反应评估和目标体积定义至关重要。在没有地面真理的情况下从临床数据中评估分割方法通常是基于医师的手册描述。在这种情况下，同时真相和性能水平估计（STAPLE）算法可能对管理多观察者变异性有用。在本文中，我们评估了该算法如何准确估计PET成像中的地面真实性。

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《Physics in medicine and biology.》 |2015年第24期|共19页
作者
Dewalle-Vignion Anne-Sophie; Betrouni Nacim; Baillet Clio; Vermandel Maximilien;
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正文语种 eng
中图分类 R35;
关键词
PET imaging; tumor segmentation; STAPLE algorithm; ground truth; segmentation methods; manual delineations;

机译：PET成像;肿瘤分割;STAPLE算法;地面真实性;分割方法;人工勾画;

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1. Is STAPLE algorithm confident to assess segmentation methods in PET imaging? [J] . Dewalle-Vignion Anne-Sophie, Betrouni Nacim, Baillet Clio, Physics in medicine and biology. . 2015,第24期

机译：STAPLE算法是否有信心评估PET成像中的分割方法？
2. Brain MR images segmentation using statistical ratio: mapping between watershed and competitive Hopfield clustering network algorithms. [J] . Kuo WF, Lin CY, Sun YN Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice . 2008,第3期

机译：使用统计比率进行脑MR图像分割：分水岭和竞争性Hopfield聚类网络算法之间的映射。
3. Cell-competition algorithm: a new segmentation algorithm for multiple objects with irregular boundaries in ultrasound images. [J] . Chen CM, Chou YH, Chen CS, Ultrasound in Medicine and Biology . 2005,第12期

机译：细胞竞争算法：一种新的分割算法，用于超声图像中边界不规则的多个对象。
4. Segmentation method for breast tumor diagnosis based on Artificial Neural Network algorithm applied to dynamic 18F-FDG PET images [C] . Xinyue Zhang, Yinlin Li, Raúl Sánchez-Jurado, IEEE Nuclear Science Symposium and Medical Imaging Conference . 2015

机译：基于人工神经网络算法的乳腺肿瘤诊断分割方法在动态18F-FDG PET图像中的应用
5. PET Image Segmentation and Reconstruction Using Level Set Method. [D] . Cheng-Liao, Jinxiu. 2010

机译：使用Level Set方法进行PET图像分割和重建。
6. Esophagus Segmentation in CT Images via Spatial Attention Network and STAPLE Algorithm [O] . Minh-Trieu Tran, Soo-Hyung Kim, Hyung-Jeong Yang, 2021

机译：通过空间关注网络和钉算法在CT图像中的食道分割
7. Is STAPLE algorithm confident to assess segmentation methods in PET imaging? [O] . Anne-Sophie Dewalle-Vignion, Nacim Betrouni, Clio Baillet, 2015

机译：主题算法是否有信心评估宠物成像中的分段方法？

Is STAPLE algorithm confident to assess segmentation methods in PET imaging?

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