Journal:Informatica
Volume 18, Issue 2 (2007), pp. 267–278
Abstract
A technique to improve an eye cataract early detection and quantitative evaluation of maturity using ultrasound was investigated. A broadband coherent signal, backscattered from an eye lens tissue, was digitized, recorded and processed. A new parameter – lens quality was proposed for the human eye cataract quantitative evaluation. Lens quality reflects two phenomena of ultrasound interaction with lens tissue – attenuation and scattering. Digital technique for echo-signal energy and time frequency analysis was applied, ultrasound waves scattering strength and spectral slope was calculated.
Experimental statistical investigations performed with signals divided into five groups – mature cataract, immature form of cataract, incipience cataract phase, healthy lenses and human eye phantom. Investigations have showed that value of specific quality in the test groups vary in the wide range from 1 to 60. This feature allows theoretically differentiate eye lenses cataract in different classes with defined boundaries. Presented results show that we with high reliability can differentiate lenses into three groups: healthy lenses (QL>50), lenses with incipient or immature cataract (QL=2-20) and lenses with mature cataract (QL<1).
The investigated method can be used for an eye lens classification and for early cataract detection This technique was used at the Department of Ophthalmology, Institute for Biomedical Research, Kaunas University of Medicine.
Journal:Informatica
Volume 16, Issue 4 (2005), pp. 541–556
Abstract
This paper presents a new approach for human cataract automatical detection based on ultrasound signal processing. Two signal decomposition techniques, empirical mode decomposition and discrete wavelet transform are used in the presented method. Performance comparison of these two decomposition methods when applied to this specific ultrasound signal is given. Described method includes ultrasonic signal decomposition to enhance signal specific features and increase signal to noise ratio with the following decision rules based on adaptive thresholding. The resulting detection performance of the proposed method using empirical mode decomposition was better to compare to discrete wavelet transform and resulted in 70% correctly identified “healthy subject” cases and 82%, 97% and 100% correctly identified “cataract cases” in the incipience, immature and mature cataract subject groups, respectively. Discussion is given on the reasons of different results and the differences between the two used signal decomposition techniques.
Journal:Informatica
Volume 14, Issue 4 (2003), pp. 529–540
Abstract
Cataract is very frequent disease of human eye and the diagnosis of this disease is not difficult. However, it is important to describe it quantitatively, but it is difficult using only the slit lamp. Ultrasound examinations are widely used in ophthalmology. Piezoelectric crystals generate ultrasound waves of 5–50 MHz. Short pulses of 2 to 3 cycles are sent from transducer into the eye. These pulses go through the tissues of the eye with the speed that is inversely proportional to the density and elasticity of the eye. Acoustic parameters of biologic tissues are described by velocity and attenuation coefficient. It is known that in soft tissues the attenuation coefficient is approximately proportional to the frequency – high frequency components of echoes are attenuated more than the lower frequency components. Results of ultrasound attenuation characteristics of human nuclear cataract are presented. It was shown that ultrasound attenuation of nuclear cataract could be used as “second opinion” for physicians decision support.