Evaluation of automatic time gain compensated in-vivo ultrasound sequences

Ultrasound imaging is increasingly being used in applications such as surgery, anesthesia and urology, where the users are not trained radiologists. User studies indicate that these users rarely adjust the controls of the ultrasound scanner. This project presents a preliminary evaluation of a new algorithm for automatic time gain compensation (TGC) on in-vivo ultrasound sequences.

Forty ultrasound sequences were recorded from the abdomen of two healthy volunteers. Each sequence of 5 sec was recorded with 40 frames/sec. Post processing each frame, a mask is created wherein anechoic and hyper echoic regions are mapped. Near field hyper intensity and deep areas with low signal strength are also included in the mask.

The algorithm uses this mask to create a parallel image where anechoic and hyper echoic regions are eliminated. From this, the mean power is calculated as a function of depth. The power is then used as an estimate of the attenuation, and from this, the needed compensation is found. The measurements were performed by an experienced sonographer using an ultrasound scanner (2202 ProFocus, BK Medical, Denmark) with a 192 elements concave transducer (8820e BK Medical).

A research interface was used to retrieve unprocessed data from the scanner with no preset TGC, using a standard abdominal setup. Five experts in medical ultrasound evaluated the unprocessed and processed video sequences in a double-blinded randomized trial on image quality and penetration depth. In the evaluation of image quality, the unprocessed and processed sequences were displayed in pairs side-by-side in random order and with random left right placement.

Each pair was displayed and scored twice, with different permutations. The sequences were evaluated on their relative clinical value. P-values on the order of 10-8 - 10-14 indicate that the image quality of the processed sequences are clinically better than the unprocessed. In the evaluation of penetration depth, all the processed and unprocessed sequences were displayed in random order.

Each sequence was evaluated on the basis of; at what depth the image quality had decreased so much that it was of no clinical value. The pooled results show a mean increase in penetration depth of 1.91 cm with a p-value of 1.19 - 10-18. In conclusion a new algorithm has been developed and evaluated.

It is capable of compensating for the depth attenuation on abdominal in-vivo ultrasound images.