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Handbook of Medical Informatics

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Presentation on theme: "Handbook of Medical Informatics"— Presentation transcript:

1 Handbook of Medical Informatics
Jan van Bemmel & Mark Musen

2 Biosignal Analysis



5 Panel 8.01 Sampling of Signals: How Often?
    Without exception, all biosignals are analog signals. Processing of biosignals by computers therefore requires discretization (i.e., sampling and quantification). This panel explains the sampling process without referring to formulas. The sampling theorem mathematically phrased by Shannon and Nyquist states that a signal must be sampled at a rate at least twice the rate of the highest-frequency component present in the signal. If we use a sampling rate that is too low, the signal is distorted. If we obey the sampling theorem, the complete syntactic information content of the signal is retained. This is illustrated by the following example. An EEG usually contains statistical, more or less sine wave-shaped fluctuations that may occur at a rate of up to 30 times/second. This can also be expressed by saying that the EEG contains frequencies up to 30 Hz. Higher frequencies may also be present (e.g., from other signal sources) but these are generally not of semantic interest. The sampling theorem then prescribes that we should sample the EEG at least at 2 x 30 = 60 Hz to keep all signal properties. Table 8.1 gives the frequency bandwidths of interest and the most commonly used sampling rates for some biosignals. For instance, for ECGs (bandwidth, Hz) a sampling rate above the Shannon frequency (500 Hz) is most often used. If we obey the rule of the sampling theorem it is, in principle, possible to restore the original analog signal by digital-to-analog conversion.


7 Panel 8.02 Sampling of Signals: How Accurate?
    When sampling a signal, we use an analog-to-digital converter (A-D converter or ADC). Samples are taken at a rate at least twice the rate of the highest-frequency component contained in the signal (i.e., the mixture of signal plus noise, unless the noise has been filtered out beforehand), and the samples are quantitated and expressed as numbers. The latter is always done with a limited accuracy and may, in principle, add so-called quantization noise to the sampled signal. This quantization noise should generally not exceed the noise that is already present in the signal, or, as expressed in more general terms, discretization by the ADC should not increase the information entropy (see Chapter 2); syntactic and semantic signal properties should be left intact. The degree of quantization can be expressed as the number of quantization steps for the range of possible amplitude values. If the signal amplitude spans a range of A volts (e.g., from -A/2 to +A/2) and the quantization step is Dq, then the number of quantization steps is m = A/Dq. In practice, let m be a power of 2: m = 2n, so that the quantization of the ADC can be expressed in n bits. For instance, an ADC with an accuracy of 10 bits can discern 210 = 1024 different amplitude levels, resulting in a resolution of about 0.1%, expressed as a percentage of the signal range A. An ADC that delivers samples with 8-bit accuracy (28 = 256 steps) is called an 8-bit ADC. A 1-bit ADC only determines the sign of the signal (or whether it is larger or lower than some threshold). For most biosignals a 6- to 12-bit ADC is sufficient; a 12-bit ADC implies a resolution of 1/4096 (less than 0.025%), related to a signal-to-noise ratio which is far superior to that attainable with most signal transducers.

8 Electroencephalogram 0.2-50 600 µV 4-6 Electrooculogram 0.2-15 10 mV
Table 8.01 Bandwidths, Amplitude Ranges, and Quantization of Some Frequently Used Biosignals     Signal Bandwidth (Hz) Amplitude range Quantization (bits) Electroencephalogram 0.2-50 600 µV 4-6 Electrooculogram 0.2-15 10 mV Electrocardiogram 10-12 Electromyogram 4-8 Blood pressure 0-60 400 mm Hg 8-10 Spirogram 0-40 10 L Phonocardiogram 5-2000 80 dB Table 8.1. Bandwidths, Amplitude Ranges, and Quantization of Some Frequently Used Biosignals.

9 Medical Imaging

10 Panel 9.01 Principle of Echo Scanners
    In echo scanners, sound pulses are generated with frequencies of about a few MHz. These pulses are absorbed, scattered, or reflected in the patient. The reflections give rise to relatively strong echoes. Reflections occur at interfaces between media that are different with respect to density and/or the velocity of sound (sound is reflected at interfaces with different acoustic impedances; the so-called acoustic impedance is equal to the product of sound velocity and density). Soft tissue and water have about equal densities and sound has about equal velocities in the two media. Therefore, most of the sound waves are not reflected at their interface. At an interface between soft tissue on one side and bone or air on the other side, a strong reflection is observed. Scattering takes place if the dimension of the object is small (i.e, about the wavelength of the incident radiation). The beam is then scattered in all directions, and therefore, the amplitude of the signal detected by the transducer is relatively small. The resolution of an echo scan, that is, the degree with which details located close together can still be distinguished, is determined by both the wavelength of the sound waves and the duration of the emitted pulse. The pulse is usually several wavelengths long. In practice, therefore, reflections from two points separated by a few wavelengths can be discriminated. The smaller the wavelength the better the resolution. Since the wavelength is inversely proportional to the frequency, the resolution is proportional to the frequency.

11 cont. The attenuation coefficient (which expresses how much the beam is attenuated per centimeter of tissue because of scatter and absorption) is also proportional to the sound frequency for soft tissue and is even proportional to the square of the frequency for other types of tissues. Therefore, the depth of penetration of the sound waves is inversely proportional to the frequency. The more the beam is attenuated, the more difficult it is to measure the reflections of deeper structures, since the signal-to-noise ratio (see Chapter 25) gradually becomes smaller. Since resolution and penetration depth pose contradictory requirements, a compromise must be made: deeper structures can only be visualized with relatively low frequencies, with a concomitant lower resolution. Also, the type of tissue influences the amount of absorption of the beam. Air and bone, for example, are strong absorbers, whereas muscle tissue and water hardly attenuate the beam. At a frequency of 3 MHz (wavelength of 0.5 mm) depths of up to 10 cm are well visualized, with an axial resolution on the order of 1 mm. For eye examinations a higher resolution is needed. In this case frequencies of between 5 and 13 MHz (wavelengths of between 0.25 and mm, respectively) are used. For brain examinations the sound beam must first pass bone structures (e.g., the tempora). Because of the high absorption of bone, especially for high frequencies, only low frequencies can be used, implying a lower resolution.

12 Ultrasound A-mode – x: depth y: amplitude (1 dim.)
M-mode and B-mode – x: depth y: time brightness: amplitude (1 dim.) C-Scan ÷ Sector Scan → Doppler effect – velocity

13 Radiology

14 DSA – image subtraction

15 Computed tomography

16 Gamma camera

17 Image Processing and Analysis

18 Effect of spatial resolution sampling density

19 Effect of using various quantization levels

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