Literature DB >> 22894427

Intelligent scanning: automated standard plane selection and biometric measurement of early gestational sac in routine ultrasound examination.

Ling Zhang1, Siping Chen, Chien Ting Chin, Tianfu Wang, Shengli Li.   

Abstract

PURPOSE: To assist radiologists and decrease interobserver variability when using 2D ultrasonography (US) to locate the standardized plane of early gestational sac (SPGS) and to perform gestational sac (GS) biometric measurements.
METHODS: In this paper, the authors report the design of the first automatic solution, called "intelligent scanning" (IS), for selecting SPGS and performing biometric measurements using real-time 2D US. First, the GS is efficiently and precisely located in each ultrasound frame by exploiting a coarse to fine detection scheme based on the training of two cascade AdaBoost classifiers. Next, the SPGS are automatically selected by eliminating false positives. This is accomplished using local context information based on the relative position of anatomies in the image sequence. Finally, a database-guided multiscale normalized cuts algorithm is proposed to generate the initial contour of the GS, based on which the GS is automatically segmented for measurement by a modified snake model.
RESULTS: This system was validated on 31 ultrasound videos involving 31 pregnant volunteers. The differences between system performance and radiologist performance with respect to SPGS selection and length and depth (diameter) measurements are 7.5% ± 5.0%, 5.5% ± 5.2%, and 6.5% ± 4.6%, respectively. Additional validations prove that the IS precision is in the range of interobserver variability. Our system can display the SPGS along with biometric measurements in approximately three seconds after the video ends, when using a 1.9 GHz dual-core computer.
CONCLUSIONS: IS of the GS from 2D real-time US is a practical, reproducible, and reliable approach.

Entities:  

Mesh:

Year:  2012        PMID: 22894427     DOI: 10.1118/1.4736415

Source DB:  PubMed          Journal:  Med Phys        ISSN: 0094-2405            Impact factor:   4.071


  7 in total

1.  SonoNet: Real-Time Detection and Localisation of Fetal Standard Scan Planes in Freehand Ultrasound.

Authors:  Christian F Baumgartner; Konstantinos Kamnitsas; Jacqueline Matthew; Tara P Fletcher; Sandra Smith; Lisa M Koch; Bernhard Kainz; Daniel Rueckert
Journal:  IEEE Trans Med Imaging       Date:  2017-07-11       Impact factor: 10.048

2.  Graph-based segmentation of abnormal nuclei in cervical cytology.

Authors:  Ling Zhang; Hui Kong; Shaoxiong Liu; Tianfu Wang; Siping Chen; Milan Sonka
Journal:  Comput Med Imaging Graph       Date:  2017-01-31       Impact factor: 4.790

3.  Rapid and automatic assessment of early gestational age using computer vision and biometric measurements based on ultrasound video.

Authors:  Yuanyuan Pei; Wenjing Gao; Longjiang E; Changpin Dai; Jin Han; Haiyu Wang; Huiying Liang
Journal:  Quant Imaging Med Surg       Date:  2022-04

4.  Automatic Recognition of Fetal Facial Standard Plane in Ultrasound Image via Fisher Vector.

Authors:  Baiying Lei; Ee-Leng Tan; Siping Chen; Liu Zhuo; Shengli Li; Dong Ni; Tianfu Wang
Journal:  PLoS One       Date:  2015-05-01       Impact factor: 3.240

Review 5.  Artificial Intelligence in Prenatal Ultrasound Diagnosis.

Authors:  Fujiao He; Yaqin Wang; Yun Xiu; Yixin Zhang; Lizhu Chen
Journal:  Front Med (Lausanne)       Date:  2021-12-16

6.  Recognition of Thyroid Ultrasound Standard Plane Images Based on Residual Network.

Authors:  Minghui Guo; Kangjian Wang; Shunlan Liu; Yongzhao Du; Peizhong Liu; Qichen Su; Guorong Lv
Journal:  Comput Intell Neurosci       Date:  2021-06-02

7.  Recognition of Fetal Facial Ultrasound Standard Plane Based on Texture Feature Fusion.

Authors:  Xiaoli Wang; Zhonghua Liu; Yongzhao Du; Yong Diao; Peizhong Liu; Guorong Lv; Haojun Zhang
Journal:  Comput Math Methods Med       Date:  2021-06-03       Impact factor: 2.238

  7 in total

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