You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Implement DAS as a separated op: wf.beamforming.delay_and_sum(input, delays_map),
where delays_map is a map of delays created for a specific type of imaging (i.e. STAI and PWI).
Implement sta_delays(us_env) and pwi_delays(us_env). These functions should be called before processing starts and should return tensor delays_map(x,y,t) = approx. no. of sample from transducer t, which contributes to brightness level of a (x,y) point of a final b-mode frame.
wf.beamforming.delay_and_sum(input, delays_map),where
delays_mapis a map of delays created for a specific type of imaging (i.e. STAI and PWI).sta_delays(us_env)andpwi_delays(us_env). These functions should be called before processing starts and should return tensordelays_map(x,y,t)= approx. no. of sample from transducert, which contributes to brightness level of a(x,y)point of a final b-mode frame.