Automatic Detection of Acoustic Window During Echocardio-graphic Imaging

Ultrasound remains an attractive option for cardiac imaging due to its real-time imaging capabilities and high temporal resolution. One key challenge in echocardiographic imaging is locating an optimal acoustic window for generating high-quality images. This task is confounded by the presence of anatomical structures such as ribs creating imaging shadows. This study presents an automated algorithm capable of detecting shadows. The algorithm was tested on a tissue-mimicking phantom that incorporated specular objects mimicking the acoustic shadows of ribs. The algorithm successfully detected and visualized the rib-sized objects and their accompanying shadow artifacts with a specificity of 0.73 and sensitivity of 0.76. It's implementation could enhance the accuracy and consistency of echocardiographic measurements, leading to more accurate diagnoses and improved treatment planning.