Skip to main content
Log in

Review of neural network applications in medical imaging and signal processing

  • Review
  • Published:
Medical and Biological Engineering and Computing Aims and scope Submit manuscript

Abstract

The current applications of neural networks to in vivo medical imaging and signal processing are reviewed. As is evident from the literature neural networks have already been used for a wide variety of tasks within medicine. As this trend is expected to continue this review contains a description of recent studies to provide an appreciation of the problems associated with implementing neural networks for medical imaging and signal processing.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Alaux, A. andRinck, P. A. (1989) Multispectral analysis of magnetic resonance images: a comparison between supervised and unsupervised classification techniques. In Proc. Int. Symp. on Tissue Characterisation in Magnetic Resonance Imaging, European Soc. for Mag. Res. in Med. & Biol, ISBN 354051532, 19th–21st April, Wiesbaden, Germany, 165–169.

  • Aleksander, I. andMorton, H. (1990)An introduction to neural computing. Chapman & Hall, New York.

    Google Scholar 

  • Alexandre, F., Guyot, F. andHaton, J.-P. (1990) A connectionist network with two complementary visual processing systems for X-ray image interpretation. In Proc Int. Neural Networks Conf., July, Paris, France, Part 1, 496–499.

  • Angel, J. R. P., Wizinowich, P., Lloyd-Hart, M. andSandler, D. (1990) Adaptive optics for array telescopes using neural network techniques.Nature,348, 221–224.

    Article  Google Scholar 

  • Anthony, D. M., Hines, E. L., Taylor, D. andBarham, J. (1989) A study of data compression using neural networks and principal component analysis. Proc. IEE Colloq. Biomed. Appl. of Digital Sig. Proc., IEE Coll. Dig. 1989/144, Nov., London, UK, Paper 2.

  • Anthony, D. M., Hines, E. L., Taylor, D. andBarham, J. (1990) The use of neural networks in classifying lung scintigrams. Proc of Int. Neural Network Soc. Int. Neural Networks Conf., 17th–21st June, San Diego, California, USA, Part 1, 71–74.

  • Arrigo, P., Corana, A., Guiliano, F., Marconi, L., Morando, M., Ridella, S., Rolando, C. andScalia, F. (1989) Neural networks: computer simulation and biomedical applications. Proc. 2nd Italian Workshop on Parallel Architectures and Neural Networks.Caianiello E. R. (Ed.), World Scientific, Societa Italiana Reti Neuroniche, ISBN 981020146X, 26th April, Vietri Sul Mare, Salerno, Italy, 205–212.

  • Baker, B., Curry, S. andBaumrind, S. (1989) A neural network method for solving pattern recognition problems in craniofacial X-ray image analysis. In Proc. 11th Ann. Int. Conf. IEEE Eng. in Med. & Biol. Soc., 9th–12th Nov., Seattle, Washington, USA, Section 5, 1646.

  • Barber, D. C. (1980) The use of principal components in the quantitative analysis of gamma camera dynamic studies.Phys. in Med. & Biol.,25, 283–292.

    Article  Google Scholar 

  • Barschdorff, D., Ester, S., Dorsel, T. andMost, E. (1990) A new phonographic technique for congenital and acquired heart disease using neural networks (in German, abstract in English).Biomed. Technik,35, 271–279.

    Article  Google Scholar 

  • Beale, R. andJackson, T. (1990)Neural computing: an introduction Adam Hilger, UK.

    MATH  Google Scholar 

  • Beard, N. (1990) Having a brainwave.Personal Comput. World, Feb., 186–190.

  • Blada, R. A., Diller, G., Deardorff, E., Doue, J. andHsieh, P. (1977) The HP ECG analysis program. InTrends in computer processed electrocardiograms.van Bemmel, J. H. andWillems, J. L. (Eds.), North-Holland Amsterdam, 197–204.

    Google Scholar 

  • Bortolan, G., Degani, R. andWillems, J. L. (1990) Design of neural networks for classification of electrocardiographic signals. Proc. 12th Ann. Int. Conf. IEEE Eng. in Med. & Biol. Soc., 1st–4th Nov., Philadelphia, Pennsylvania, USA, Section 3, 1467–1468.

  • Brown, D. G. (1989) Neural networks for higher order medical imaging tasks. Proc. Medinfo '89 and 6th Ann. Conf. on Medical Informatics, ISBN 0444881387, 16th–20th Oct. and 11th–15th Dec., Beijing and Singapore, 77–81.

  • Carpenter, G. andGrossberg, S. (1987) A massively parallel architecture for a self-organising neural pattern recognition machine.Computer Vision Graph. & Sig. Proc.,37, 54–115.

    Article  MATH  Google Scholar 

  • Carroll, T. O., Ved, H. andReilly, D. (1989) Neural network ECG analysis. Proc. Int. Joint Conf. on Neural Networks, (abstracts only). 18th–22nd June, Washington DC, USA, Part 2, 575.

  • Cheung, J. Y., Hull, S. S. Jr, Yeo, C. S. Y. andKohli, P. (1990) Recognition of abnormal EKG signals by a neural network approach.Microcomputer Appl.,10, (2), 48–53.

    Google Scholar 

  • Cios, K. J., Chen, K. andLangenderfer, R. A. (1990) Use of neural networks in detecting cardiac diseases from echocardiographic images.IEEE Eng. in Med. & Biol. Mag., Sept., 58–60.

  • Clark, J. W. (1991) Neural network modelling.Phys. in Med. & Biol.,36, 1259–1317.

    Article  Google Scholar 

  • Conrath, B. C., Daft, C. M. W. andO'Brien, W. D. Jr (1989) Applications of neural networks to ultrasound tomography. Proc. IEEE Ultrasonics Symp., Oct., Chicago, Illinois, USA, 1007–1010.

  • DaPonte, J. S. andSherman, P. (1991) Classification of ultrasonic image texture by statistical discrimination analysis of neural networks.Computer Med. Imaging Graph.,15, (1), 3–9.

    Article  Google Scholar 

  • Dassen, W. R., Mullereers, R., Smeets, J., Den Dulk, K., Cruz, F., Brugada, P. andWellens, H. J. J. (1990) Self-learning neural networks in electrocardiography.J. Electrocardiol., (US),23, Suppl., 200–202.

    Article  Google Scholar 

  • Dawant, B. M., Özkan, M., Sprenkels, H. G., Aramata, H., Kawamura, K. andMargolin, R. A. (1990) A neural network approach to magnetic resonance imaging tissue characterisation. InCommunication control and signal processing. Proc. Bilkent Int. Conf. on New Trends in Comm. Control & Sig. Proc.,Arikan, E. (Ed.), 2nd–5th July, Bilkent University, Ankara, Turkey, Elsevier, Amsterdam, Part 2, 1803–1809.

    Google Scholar 

  • Eberhart, R. C., Dobbins, R. E. andWebber, W. R. S. (1989) CASENET: a neural network tool for EEG waveform classification. Proc. IEEE Symp. Computer Based Medical Systems, 25th–27th June, Minneapolis, Minnesota, USA, 60–68.

  • Egbert, D. D., Rhodes, E. E. andGoodman, P. H. (1988) Preprocessing biomedical images for neurocomputer analysis. IEEE Int. Conf. on Neural Networks, July, San Diego, California, USA, Part 1, 561–568.

  • Egbert, D. D., Kaburlasos, V. G. andGoodman, P. H. (1990) Neural network discrimination for subtle image patterns. IEEE Int. Joint Conf. on Neural Networks, 17th–21th June, San Diego, California, USA, Part 1, 517–524.

  • Gage, H. D. andMiller, T. K. (1990) Mapping neural networks for the analysis of the forced expired volume signal. Proc. 3rd Ann. Symp. on Computer-Based Medical Systems, June, Chapel Hill, North Carolina, USA, 367–373.

  • Gevins, A. S., Stone, R. K. andRagsdale, S. D. (1988) Differentiating the effects of three benzodiazapines on non-REM sleep EEG spectra: a neural network pattern classification analysis.Neuropsychobiol.,19, (2), 108–115.

    Article  Google Scholar 

  • Goldbaum, M. H., Katz, N. P. Chaudhuri, S. andNelson, M. (1989) Image understanding for automated retinal diagnosis. Proc. 13th Ann. Symp. Computer Appl. in Medical Care, Nov., Washington DC, USA, Chap. 5–8, 756–760.

  • Graup, D. (1975) Functional separation of EMG signals via ARMA identification methods for prosthesis control purposes.IEEE Trans.,SMC-5, 252–259.

    Google Scholar 

  • Grönqvist, A. andLenz, R. (1989) Detection of blood vessels in 3-D MR-images. Proc. Int. Joint Conf. on Neural Networks, 18th–22nd June, Washington DC, USA, Part 1, 145–149.

  • Gross, G. W., Boone, J. M., Greco-Hunt, V. andGreenberg, B. (1990) Neural networks in radiologic diagnosis: II. Interpretation of neonatal chest radiographs.Invest. Radiol.,25, 1017–1023.

    Google Scholar 

  • Grossberg, S. andMingolla, E. (1987) Neural dynamics of surface perception: boundary webs, illuminants, and shape-from-shading.Computer Vision Graph. & Image Proc.,37, 116–165.

    Article  Google Scholar 

  • Guyot, F., Alexandre, F., Haton, J. P. andBurnod, Y. (1989) A potentially powerful connectionist unit: the cortical column. NATO Advanced Workshop on Neuro Computing, NATO, Bonas, France, 22nd–27th Aug. 1988, 197–206.

  • Hecht-Nielsen, R. (1987) Counter-propagation networks. Proc. 1st Int. Conf. on Neural Networks, June, San Diego, California, USA, Part 2, 19–32.

  • Hinton, G. E. (1989) Connectinist learning procedures.Artif. Intell.,40, 185–234.

    Article  Google Scholar 

  • Hopfield, J. J. andTank, D. W. (1986) Computing with neural circuits: a model.Science,223, 625–633.

    Google Scholar 

  • Huang, J. N. andKung, S. Y. (1989) Parallel algorithms/architectures for neural networks.J. VLSI Sig. Proc.,1, 221–251.

    Google Scholar 

  • Iwata, A., Nagasaka, Y. andSuzumura, N. (1989) A digital Holter monitoring system with dual 3 layer neural networks. Proc. Int. Joint. Conf. on Neural Networks, 18th–22nd June, Washington DC, USA, Part 2, 69–74.

  • Jolliffe, I. T. (1986)Principal component analysis. Springer-Verlag, Berlin.

    Google Scholar 

  • Karkhanis, P. A., Cheung, J. Y. andTeague, S. M. (1990) Using a PC based neural network to estimate the ejection fraction of a human heart.Microcomputer Appl.,9, (3), 99–107.

    Google Scholar 

  • Karnin, E. D. (1990) A simple procedure for pruning back-propagation trained neural networks.IEEE Trans.,NN-1, 239–242.

    Google Scholar 

  • Katz, W. T. andMerickel, M. B. (1989) Translation invariant aorta segmentation from magnetic resonance images. Proc. Int. Joint Conf. on Neural Networks, 18th–22nd June, Washington DC, USA, Part 1, 327–333.

  • Kelly, M. F., Parker, P. A. andScott, R. N. (1990) The application of neural networks to myoelectic signal analysis: a preliminary study.IEEE Trans.,BME-37, 221–230.

    Google Scholar 

  • Khoshaba, T., Badie, K. andHashemi, R. M. (1990) EMG pattern classification based on back propagation neural network for prosthesis control. Proc. 12th Ann. Int. Conf. IEEE Eng. in Med. & Biol. Soc., 1st–4th Nov., Philadelphia, Pennsylvania, USA, Section 3, 1474–1475.

  • Kippenhan, J. S. andNagel, J. H. (1990) Diagnosis and modelling of Alzheimer's disease through cural network analysis of PET studies. Proc. 12th Ann. Conf. IEEE Eng. in Med. & Biol. Soc., 1st–4th Nov., Philadelphia, Pennsylvania, USA, Section 3, 1449–1450.

  • Kohonen, T. (1990) The self-organizing map.IEEE Proc.,78, 1464–1480.

    Article  Google Scholar 

  • Lee, S. C. (1989) Using translation-invariant neural network to diagnose heart arrhythmia. Proc. 11th Ann. Int. Conf. IEEE Eng. in Med. & Biol. Soc., 9th–12th Nov., Seattle, Washington, USA, Section 6, 2025–2026.

  • Lehar, S. M., Worth, A. J. andKennedy, D. N. (1990) Application of the boundary contour/feature system to magnetic resonance brain scan imagery. Proc. Int. Joint Conf. on Neural Networks, 17th–21st June, San Diego, California, USA, Part 1, 435–440.

  • Linnenbank, A. C., SippensGroenewegen, A. andGrimbergen, C. A. (1990) Artificial neural networks applied in multiple lead electrocardiography rapid quantitative classification of ventricular tachycardia QRS internal patterns. Proc. 12th Ann. Int. Conf. IEEE Eng. in Med. & Biol., 1st–4th Nov., Philadelphia, Pennsylvania, USA, Section 3, 1461–1462.

  • Miller, A. S., Blott, B. H. andHames, T. K. (1992) Neural networks for electrical impedance tomography image characterisation.Clin. Phys. Physiol. Meas.,13, Suppl. A, 119–123.

    Google Scholar 

  • Miller, L. F., Smith, G. T., Wu, Y. andUhrig, R. E. (1990) Evaluation of neural networks for parameter identification from positron emission tomography scans.Trans. Am. Nuclear Soc.,62, 5–6.

    Google Scholar 

  • Minsky, M. L. andPapert, S. A. (1988)Perceptrons: an introduction to computational geometry, 2nd edn. MIT Press, Cambridge, Massachusetts, USA.

    MATH  Google Scholar 

  • Navabi, M. J., Watt, R. C., Mylrea, K. C. andHameroff, S. R. (1990) Classification of CO2 waveforms using artificial neural networks. Proc. 12th Ann. Conf. IEEE Eng. in Med. & Biol. Soc., 1st–4th Nov., Philadelphia, Pennsylvania, USA, Section 3, 1455–1456.

  • Nekovei, R. andSun, Y. (1990) An adaptive algorithm for coronary artery identification in cineangiograms. Proc. 12th Ann. Int. Conf. of the IEEE Eng. in Med. & Biol. Soc., 1st–4th Nov., Philadelphia, Pennsylvania, USA, Section 3, 1459–1460.

  • Nikoonahad, M. andLiu, D. C. (1990) Medical ultrasound imaging using neural networks.Electron. Lett.,26, 545–546.

    Google Scholar 

  • Özkan, M., Sprenkles, H. G. andDawant, B. M. (1990) Multispectral magnetic resonance image segmentation using neural networks. Proc. Int. Joint Conf. on Neural Networks, 17th–21st June, San Diego, California, USA Part 1, 429–434.

  • Paul, J. andvon Goldammer, E. (1990) Neural net applications in medicine. InSymbols versus neurons.Stender, J. andAddis, T. (Eds.), IOS Press, Amsterdam, 215–231.

    Google Scholar 

  • Pietka, E. (1989) Neural nets for ECG classification. Proc. 11th Ann. Int. Conf. IEEE Eng. in Med. & Biol., Soc., 9th–12th Nov., Seattle, Washington, USA, Section 6, 2021–2022.

  • Pinho, A. J. andAlmeida, L. B. (1991) Biomedical image compression based on artificial neural networks. Proc. 1st European Conf. on Biomed. Eng., 17th–20th Feb., Nice, France, 90–91.

  • Principe, J. C., Chang, T. G. Gala, S. K. andTome, A. P. (1989a) Information processing models for automatic sleep scoring. Proc. 11th Ann. Int. Conf. IEEE Eng. in Med. & Biol. Soc., 9th–12th Nov., Seattle, Washington, USA Section 6, 1804–1805.

  • Principe, J. C., Gala, S. andChang, T. (1989b) Sleep staging based on the theory of evidence.IEEE Trans.,BME-36, 503–509.

    Google Scholar 

  • Raff, U. andNewman, F. D. (1990) Lesion detection in radiologic images using an autoassociative paradigm: preliminary results.Med. Phys. (US),17, 926–928.

    Article  Google Scholar 

  • Rumelhart, D. E., Hinton, G. E. andMcClelland, J. L. (1986) A general framework for parallel distributed processing. InParallel distributed processing: explorations in the microstructure of cognition Volume 1 Foundations.Rumelhart, D. E., McClelland, J. L. and The PDP Research Group (Eds.), MIT Press, Cambridge, Massachusetts, USA, 45–76.

    Google Scholar 

  • Sander, D. G., Barrett, T. K. andPalmer, D. A. (1991) Use of a neural network to control an adaptive optics system for an astronomical telescope.Nature,351, 300–302.

    Article  Google Scholar 

  • Schellenberg, J. D., Naylor, W. C. andClarke, L. P. (1990) Application of artificial neural networks for tissue classification from multispectral magnetic resonance images of the head. Proc. 3rd Ann. IEEE Symp. on Computer-Based Medical Systems, June, Chapel Hill, North Carolina, USA, 350–357.

  • Schertz, L. D., Vannier, M. W., Gado, M. H. andButterfield, R. L. (1985) Statistical assessment of MR image classification techniques. In Proc. 7th Ann. Conf. IEEE Eng. in Med. & Biol. Soc., Sept., Chicago, Illinois, USA, 585–592.

  • Schizas, C. N., Pattichis, C. S., Schofield, I. S., Fawcett, P. R. andMiddleton, L. T. (1989) Artificial neural net algorithms in classifying electromyographic signals. Proc. 1st IEE Conf. on Artificial Neural Networks, IEE Conf. Publ. 1989/313, 16th–18th Oct., London, UK, 134–138.

  • Sebald, A. V. (1989) Use of neural networks for detection of artifacts in arterial pressure waveforms. Proc. 11th Ann. Int. Conf. IEEE Eng. in Med. & Biol. Soc., 9th–12th Nov., Seattle, Washington, USA, Section 6, 2034–2035.

  • Silverman, R. H. andNoetzel, A. S. (1990) Image processing and pattern recognition in ultrasonograms by backpropagation.Neural Networks,3, 593–603.

    Article  Google Scholar 

  • Strand, E. M. andJones, W. T. (1990) A neural network for tracking the prevailing heart rate of the electrocardiogram. Proc. 3rd Ann. Symp. on Computer-Based Medical Systems, June, Chapel Hill, North Carolina USA, 358–365.

  • Stubbs, D. F. (1990) Multiple neural network approaches to clinical expert systems.SPIE Appl. of Artif. Neural Networks,1294, 433–441.

    Google Scholar 

  • Toulson, D. L. andBoyce, J. F. (1991) Segmentation of MR images using neural nets. IEE Colloq. on Image Proc. in Med., IEE Coll. Dig. 1991/84, 19th April, London, UK, Paper 5.

  • Tsai, Y. S., Hung, B. N. andTung, S. F. (1990) An experiment on ECG classification using back-propagation neural network. Proc. 12th Ann. Int. Conf. IEEE Eng. in Med. of Biol. Soc., 1st–4th Nov., Philadelphia, Pennsylvania, USA, Section 3, 1463–1464.

  • Wasserman, P. D. (1989)Neural computing theory and practice. Van Nostrand Reinhold, New York.

    Google Scholar 

  • Widrow, B. andWinter, R. (1988) Neural nests for adaptive filtering and adaptive pattern recognition.IEEE Computer, March, 25–39.

  • Widrow, S. andLehr, M. A. (1990) 30 years of adaptive neural networks: perceptron, madaline, and backpropagation.Proc. IEEE,78, 1415–1441.

    Article  Google Scholar 

  • Xue, Q., Hu, Y. H. andTompkins, W. J. (1989) A neural network weight pattern study for ECG pattern recognition. Proc. 11th Ann. Int. Conf. IEEE Eng. in Med. & Biol. Soc., 9th–12th Nov., Seattle, Washington, USA, Section 6, 2023–2024.

  • Xue, Q., Hu, Y. H. andTompkins, W. J. (1990) Training of ECG signals in neural network pattern recognition. Proc. 12th Ann. Int. Conf. IEEE Eng. Med. & Biol. Soc., 1st–4th Nov., Philadelphia, Pennsylvania, USA, Section 3, 1465–1466.

  • Yeap, T. H., Johnson, F. andRachniowski, M. (1990) ECG beat classification by a neural network. Proc. 12th Ann. Int. Conf. IEEE Eng. in Med. & Biol. Soc., 1st–4th Nov., Philadelphia, Pennsylvania, USA, Section 3, 1457–1458.

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Miller, A.S., Blott, B.H. & hames, T.K. Review of neural network applications in medical imaging and signal processing. Med. Biol. Eng. Comput. 30, 449–464 (1992). https://doi.org/10.1007/BF02457822

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02457822

Keywords

Navigation