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What is software-defined radio imaging?

The flexibility of this technology allows the introduction of new techniques and technologies at a low cost and without requiring hardware modifications.

Brandon Malatest, On vices

(Image of Shutterstock provided by Per Vices)

Software-defined radio technology (SDR) offers impressive configuration flexibility and high measurement accuracy, making it ideal for use in medical imaging applications.

SDR-based architectures provide clear image reconstructions and high diagnostic confidence. The use of commercial SDT systems (COTS) reduces the overall cost of developing diagnostic solutions and reduces the execution time required to develop them, which benefits both the medical industry and the patient.

How it works

In medical imaging equipment, the SDR platform is suitable for signal processing, system calibration, multi-radio synchronization and image reconstruction.

Block diagram of an MRI system based on the SDR platform of Per Vices (Courtesy of Per Vices)

A typical image setup includes a computer system and an SDR platform. The computer controls the function of the system, while the SDR platform is typically used for signal processing and signal transmission and reception. The basic architecture of the SDR consists of a radio frequency interface, an analog-to-digital converter (ADC), a digital-to-analog converter (DAC) and a digital signal processor (DSP).

SDR-based systems can operate reliably and accurately over a wide bandwidth and spectrum, making them a good platform for adopting ultra-wideband (UWB) wireless technology, which is becoming increasingly popular in the hospital environment. A medical imaging system is considered a UWB when its operating frequency range is greater than 500 MHz. Higher frequencies solve finer structures, while lower frequencies solve larger structures and provide contrast to the reconstructed image. This means that the entire operating tape is vital to extracting as much information as possible from the images to create an accurate reconstruction.

Efficiency of SDR-based medical imaging systems

In a hospital environment, a large number of medical imaging devices are expected to coexist indoors, but traditional radio devices are highly susceptible to radio frequency interference. Interference reduces the performance of radio systems and limits the number of devices that can coexist in a given space.

The SDR paradigm uses MIMO technology (multiple inputs, multiple outputs) to maximize the number of devices that can coexist in a given space. This technology allows multiple receive / receive channels, allowing the transmission and / or reception of multiple signals, while limiting interference between channels.

The speed of a typical imaging device is largely determined by the speed at which the system takes samples (quadrature sampling frequency or I / Q). The signal-to-noise ratio (SNR) of an imaging system is largely determined by the I / Q sampling frequency, in inverse proportion.

Unlike direct sampling, the I / Q sampling approach – which uses SDR-based systems – helps to simplify the implementation of a signal processing system. In addition, the cost of software-based mixing and filtering components required when using I / Q data is low. The use of I / Q data in medical imaging reduces the cost of developing diagnostic tools and improves their scalability.

In critical applications such as medical imaging, radio signals must be perfectly synchronized. Lack of signal synchronization can lead to distorted images and inaccurate results. SDR-based systems offer better phase coherence than current hardware-only medical imaging systems, producing fewer errors and less distortion of reconstructed images.

Advantages of SDR in medical diagnostics

Sophisticated medical imaging systems based on special hardware components can be difficult to upgrade. The lack of update capabilities and disposable applications on these devices causes relatively rapid obsolescence and requires entirely new systems to replace them.

Compared to traditional devices, SDR-based imaging systems use software-based components to perform basic functions. Unlike hardware components, software components are more flexible, easier to upgrade, and provide better performance.

The software components of the SDR paradigm can be upgraded by reprogramming the software in the DSP subsystem. This subsystem is usually implemented using a field-programmable port array (FPGA) or an application-specific integrated circuit (ASIC). The reprogrammability of SDR systems facilitates upgrading and integration in any system.

In addition, SDRs can have a huge impact on non-contact medical imaging. This is an important technology, especially for vulnerable patients, such as babies and burn victims, as it allows patients to receive vital signals without physical contact. SDR systems are suitable for this application due to the configuration flexibility, repeatability and impressive SNR that these systems possess.

Brandon Malatest is the chief operating officer and co-founder of the Toronto-based software radio company Per Vices. He holds an honorary degree in physics with a specialization in experimental physics from the University of Waterloo in Ontario, Canada.

The views expressed in this blog post are those of the author only and do not necessarily reflect those of Medical Design and Outsourcing or its employees.

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