The University of Florida is seeking companies interested in commercializing a photoacoustic tomography (PAT) imaging algorithm that produces higher-quality quantitative tissue absorption images at lower cost. In 2010, the global imaging market stood at $20.7 billion and was projected to reach $26.6 billion by 2016. Besides diagnosing cancers, including breast cancer, PAT can also be used to identify brain lesions such as seizure focus and to detect atherosclerotic plaques in arteries. By utilizing photon (light) and acoustic (sound) imaging approaches, PAT reduces scattering and achieves accurate pictures of tissues up to 5 centimeters deep. Although PAT is becoming increasingly popular, certain critical areas – image quality, time usage and cost – are ripe for innovation. An important component of any PAT system, the reconstructing algorithm assimilates data captured by the sensors to create a visual representation of examined tissues. With its step-by-step procedures for precise calculations, the algorithm not only determines image accuracy, but also dictates the number of detectors needed for data collection. University of Florida researchers have developed a new algorithm that is significantly more advanced and efficient. The algorithm produces higher-quality quantitative images with fewer sensors and shorter exposure times, making PAT a more attractive option for diagnostic imaging.
PAT algorithm that produces higher quality quantitative tissue absorption images with fewer sensors
- Produces higher quality quantitative images, increasing diagnostic reliability
- Requires fewer sensors, reducing cost and effort
- Acquires data faster, decreasing scanning time and minimizing patient discomfort
A hybrid modality that combines laser optics and traditional ultrasound, photoacoustic tomography (PAT) is a biomedical imaging technique based on thermal expansion. Thermal expansion occurs in an object when a small temperature rise is initiated by externally applied radiation. Through the use of multiple ultrasound sensors, thermal expansion is captured and then processed by a reconstruction algorithm that recodes the information to create an accurate representation of the original object. The algorithm, which dictates image quality, is a critical component in the PAT system. Available algorithms tend to produce flawed images and require a large number of sensors in order to capture sufficient data. University of Florida researchers have developed a new algorithm that overcomes these deficits, to achieve enhanced image quality with even fewer sensors. Also, because the algorithm is much more efficient, less time is needed to capture the required information.