A computerized diagnostic system for the interpretation of umbilical artery blood flow velocity waveforms

Date

1996-01-01

Author

Beksac, MS
Basaran, F
Eskiizmirliler, S
Erkmen, Aydan Müşerref
Yorukan, S

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

154
views

0
downloads

Objective: Development of ail artificial intelligent diagnostic system for the interpretation of umbilical artery blood flow velocity waveform measurements. Study design: Study design comprised several stages including data acquisition, image processing and analysis, training of artificial neural network and testing the predictive value of the system. The clinical material was handled in two groups. The training group consisted of 952 umbilical artery blood flow velocity waveform images of 174 normal pregnancies with normal outcome, while the testing group was composed of 138 images derived from 20 normal pregnancies with normal outcome and 68 images of 16 high risk pregnancies with poor outcome. All subjects were evaluated by Doppler ultrasonography and umbilical artery blood flow velocity waveform images were transferred to the computer environment by means of a special data acquisition system. Automated image processing and analysis were performed to derive indices such as A/B ratio, resistance index. pulse related index, area ratio of wave and angle of coincident slopes. We have used a supervised artificial neural network (back propagation learning algorithm) to develop an intelligent diagnostic system which is called the BOLU system. Results: This version of the system was trained with the umbilical artery blood flow velocity waveform images of normal pregnancies. Thus. the BOLU system decides whether the tested image is normal for a given gestational week or not. The specificity and sensitivity of this system were estimated to be 98.6% and 51.5% respectively. Conclusion: We have developed an artificial intelligent diagnostic system for the interpretation of umbilical artery blood flow velocity waveform measurements. Waveform indices were obtained automatically by image processing and analysis. The predictive value of the system was found to be satisfactory.

Subject Keywords

Obstetrics and Gynaecology, Reproductive Medicine

URI

https://hdl.handle.net/11511/42813

Journal

EUROPEAN JOURNAL OF OBSTETRICS & GYNECOLOGY AND REPRODUCTIVE BIOLOGY

DOI

https://doi.org/10.1016/0301-2115(95)02256-2

Collections

Department of Electrical and Electronics Engineering, Article

Suggestions

OpenMETU
Core

A NONINVASIVE FOCAL FIELD INTENSITY ESTIMATION METHOD USING FINITE-AMPLITUDE EFFECTS IN ULTRASOUND HYPERTHERMIA OZYAR, MS; KOYMEN, H (1991-12-11) A method for noninvasive in situ estimation of intensity in ultrasound hyperthermia is presented. The method employs the nonlinear theory of sound propagation in a focused ultrasound hyperthermia system in order to determine the focal field intensity, where the sound intensity levels are relatively high in the focal volume.
Is umbilicocerebral ratio better than cerebroplacental ratio for predicting adverse pregnancy and neonatal outcomes? Kalafat, Erkan; Kalaylioglu, Zeynep; Thilaganathan, Basky; Khalil, Asma (Elsevier BV, 2020-09-01) Objective A secondary analysis of the trial of randomized umbilical and fetal flow in Europe suggested that the umbilicocerebral ratio (UCR) provides better differentiation of neurodevelopmental outcome in the abnormal range compared with that of the cerebroplacental ratio (CPR).1 However, the reported superiority of UCR is controversial.2 This study aimed to compare the CPR and the UCR for predicting operative delivery for presumed fetal compromise and prolonged neonatal unit (NNU) admission in term fetus...
A Robust Normalization Method for fMRI Data for Brain Decoding Yildiz, Ozan; Dogan, Fethiye Irmak; GİLLAM, İLKE; Mizrak, Eda; Yarman Vural, Fatoş Tunay (2016-05-19) Functional Magnetic Resonance Imaging (fMRI) methods produce high dimensional representation of cognitive processes under heavy noise due to the limitations of hardware and measurement techniques. In order to reduce the noise and extract useful information from the fMRI data, a sequence of pre-processing techniques, such as smoothing with spatial filters and z-scoring, are used. In this study, we suggest an additional normalization technique based upon a statistical property of fMRI data. We, first, define ...
A Hybrid geo-activity recommendation system using advanced feature combination and semantic activity similarity Sattari, Masoud; Toroslu, İsmail Hakkı; Department of Computer Engineering (2013) In this study, a new method for analyzing and representing the discriminative information, distributed in functional Magnetic Resonance Imaging (fMRI) data, is proposed. For this purpose, a local mesh with varying size is formed around each voxel, called the seed voxel. The relationships among each seed voxel and its neighbors are estimated using a linear regression equation by minimizing the expectation of the squared error. This squared error coming from linear regression is used to calculate various info...
A Crack Phase-field Model to Analyze Aortic Dissections Holzapfel, Gerhard A.; Gültekin, Osman; Hager, Sandra P.; Dal, Hüsnü (2019-09-05) This study analyzes the lethal clinical condition of aortic dissections from a numerical point of view.On the basis of our previous contributions [1,2], we apply a holistic geometrical approach to fracture,namely the crack phase-field, which inherits the intrinsic features of gradient damage and variationalfracture mechanics. The continuum framework captures anisotropy, is thermodynamically consistentand based on finite strains. The balance of linear momentum and the crack evolution equation governthe coupl...

Citation Formats

M. Beksac, F. Basaran, S. Eskiizmirliler, A. M. Erkmen, and S. Yorukan, “A computerized diagnostic system for the interpretation of umbilical artery blood flow velocity waveforms,” EUROPEAN JOURNAL OF OBSTETRICS & GYNECOLOGY AND REPRODUCTIVE BIOLOGY, pp. 37–42, 1996, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/42813.