CTG-OAS


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CTG-OAS


CTG-OAS is an open-access software for analyzing cardiotocography (CTG) signals. The software is developed via Matlab. The main aim of this software is to ensure a computational platform for research purpose. The significant processes such as preprocessing, feature transform and classification in terms of the automated CTG analysis have been embedded into the software to develop new algorithms. 

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Lastest Publication

  1. [ Haploid Maize Seeds ] Identification of haploid and diploid maize seeds using convolutional neural networks and a transfer learning approach
  2. [ Haploid Maize Seeds ] Identification of Haploid Maize Seeds using Gray Level Co-occurrence Matrix and Machine Learning Techniques
  3. [ CTG-OAS ] Prediction of intrapartum fetal hypoxia considering feature selection algorithms and machine learning models
  4. [ CTG-OAS ] Fetal Hypoxia Detection Based on Deep Convolutional Neural Network with Transfer Learning Approach
  5. [ CTG-OAS ] Analysis of Fetal Heart Rate Signal based on Neighborhood-based Variance Compression Method
  6. [ CTG-OAS ] The influences of different window functions and lengths on image-based time-frequency features of fetal heart rate signals
  7. [ CTG-OAS ] Performance evaluation of Empirical Mode Decomposition and Discrete Wavelet Transform for computerized hypoxia detection and prediction
  8. [ CTG-OAS ] A novel software for comprehensive analysis of cardiotocography signals “CTG-OAS”
  9. [ CTG-OAS ] A study of artificial neural network training algorithms for classification of cardiotocography signals
  10. [ CTG-OAS ] Cardiotocography analysis based on segmentation-based fractal texture decomposition and extreme learning machine
  11. [ CTG-OAS ] Using wavelet transform for cardiotocography signals classification
  12. [ CTG-OAS ] Evaluation of Fetal Distress Diagnosis during Delivery Stages based on Linear and Nonlinear Features of Fetal Heart Rate for Neural Network Community
  13. [ CTG-OAS ] A Study Based on Gray Level Co-Occurrence Matrix and Neural Network Community for Determination of Hypoxic Fetuses
  14. [ CTG-OAS ] Cardiotocography signals with artificial neural network and extreme learning machine
  15. [ CTG-OAS ] Comparison of Machine Learning Techniques for Fetal Heart Rate Classification
  16. [ CTG-OAS ] Prognostic model based on image-based time-frequency features and genetic algorithm for fetal hypoxia assessment
  17. [ CTG-OAS ] Open-access software for analysis of fetal heart rate signals
  18. [ CTG-OAS ] Fetal Hypoxia Detection Based on Deep Convolutional Neural Network with Transfer Learning Approach
  19. [ CTG-OAS ] Computer-Aided Diagnosis System of Fetal Hypoxia Incorporating Recurrence Plot With Convolutional Neural Network
  20. [ CTG-OAS ] A Simple and Effective Approach for Digitization of the CTG Signals from CTG Traces

Research Community


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Publications

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Please feel free to meet and join us.


This is an academic platform. Please feel free to meet and join us. A wide variety of talented members give our team the opportunity to innovate in nearly every domain of Biomedical Signal Processing, especially Cardiotocography.

The lastest publications!

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