an ultrasonic imaging apparatus and a method of processing ultrasonic images related to embodiment 1 of this invention will now be described . fig2 is a block diagram that shows a skeleton framework of the ultrasonic imaging apparatus related to embodiment 1 of the present invention . the ultrasonic imaging apparatus 1 related to embodiment 1 is operable according to known modes such as a b - mode that displays an ultrasonic cross - sectional image ( b - mode cross - sectional image ), a doppler mode ( pulse doppler ( pw ) or continuous doppler ( cw )) that displays bloodstream information , and a cfm ( color flow mapping ) mode that 2 - dimensionally displays bloodstream information , etc . for an ultrasonic probe 2 , a 1 - dimensional ultrasonic probe with a plurality of ultrasonic transducers aligned in one line in a predetermined direction ( scanning direction ) and a 2 - dimensional ultrasonic probe with ultrasonic transducers arranged in a matrix are used . a transceiving part 3 comprises a transmission part ( not shown ) that supplies electrical signals to the ultrasonic probe 2 to generate ultrasound and a receiving part ( not shown ) that receives signals from the ultrasonic probe 2 . the transmission part of the transceiving part 3 comprises a clock generation circuit , a transmission delay circuit , and a pulsar circuit , which are not shown . the clock generation circuit is a circuit that generates a clock signal that decides the transmission timing and the transmitted frequency of an ultrasonic signal . the transmission delay circuit is a circuit that conducts transmission focus by introducing a delay when ultrasound is transmitted . the pulsar circuit incorporates a pulsar for a few minutes for each individual route that corresponds to each ultrasonic transducer , generates a drive pulse at the transmission timing with the delay , and supplies each ultrasonic transducer of the ultrasonic probe 2 . moreover , the receiving part of the transceiving part 3 comprises a pre - amp circuit , an a / d conversion circuit , and a reception delay / adder circuit , which are not shown . the pre - amp circuit amplifies any echo signal that is output from each ultrasonic transducer of the ultrasonic probe 2 for each receiving channel . the a / d conversion circuit conducts a / d conversion of the amplified echo signals . the reception delay / adder circuit provides the delay time necessary to decide the receiving directionality for the echo signals after a / d conversion and adds it . the addition emphasizes the reflected components from the direction according to the receiving directionality . additionally , signals that have been processed for addition by this transceiving part 3 are called “ rf signals .” the rf signals output from the transceiving part 3 are output to a b - mode processing part 4 or a doppler processing part 5 . furthermore , when the transceiving part 3 receives a repetition frequency ( prf ) from a velocity range setup part 95 , it causes the ultrasonic probe 2 to transmit and receive ultrasound according to the repetition frequency . the b - mode processing part 4 visualizes the amplitude information of the echo and generates b - mode ultrasonic raster data from the echo signals . specifically , a b - mode processing circuit conducts a band pass filter process of the rf signals and then detects the envelope curve of the output signals and conducts a compression process using logarithmic conversion of the detected data . the b - mode ultrasonic raster data generated by the b - mode processing part 4 is output to a dsc 6 . the doppler processing part 5 comprises an orthogonal phase detection part 51 , a range gate ( rg ) processing part 52 , a wall filter 53 , and an fft calculation part 54 . the quadrature detection part 51 incorporates a reference signal from a reference transmitter and a reference signal with a phase difference of 90 degrees with the rf signals output from the transceiving part 3 . the range gate ( rg ) processing part 52 excludes any high - frequency components from the incorporated signals to obtain doppler signals that consist of only doppler shift frequency components and subsequently extracts doppler signals from an intended depth in the body to be examined . the wall filter 53 excludes any unnecessary low - frequency doppler signals that are relatively slow in motion , such as signals from vascular walls and cardiac walls , etc . from the doppler signals in the body to be examined designated by the range gate from the range gate processing part 52 and extracts doppler signals of the blood flow to be detected . the fft calculation part 54 conducts a frequency analysis of the doppler signals extracted by the wall filter 53 , obtains the doppler spectrum signals , which are the analytical results , and outputs to the dsc ( digital scan converter ) 6 . thereby , a doppler spectrum image is displayed on a display part 8 along with a b - mode cross - sectional image , for example . moreover , when the fft calculation part 54 receives a velocity offset ( bls ) from the velocity range setup part 95 , it changes only the read address of the fft process for the displacement and adjusts the offset of the velocity . the dsc 6 converts the ultrasonic raster data into image data that is shown in orthogonal coordinates in order to obtain an image that is shown in an orthogonal coordinate system ( scan conversion process ). the image data is output from the dsc 6 to the display part 8 , and an image based on the image data is displayed on the display part 8 . for example , the dsc 6 generates cross - sectional image data as 2 - dimensional information based on the b - mode ultrasonic raster data and outputs the cross - sectional image data to the display part 8 . the display part 8 displays a cross - sectional image based on the cross - sectional image data . an auto range / auto bls - processing part 9 receives the doppler spectrum signals output from the fft calculation part 54 and calculates the optimum velocity range for the doppler spectrum signals . the auto range / auto bls - processing part 9 comprises a measured waveform calculation part 91 , an ecg waveform acquisition part 92 , a waveform estimation part 93 , an interpolation part 94 , and a velocity range setup part 95 . the auto range / auto bls - processing part 9 is described in detail below . the measured waveform calculation part 91 detects the measured blood velocity waveform of the vp ( hereinafter referred to as “ trace ”) by detecting the maximum velocity vp of the doppler spectrum signals output from the fft calculation part 54 and connecting in the direction of that time ( for example , the detecting phase or pseudo filtering may be used ). thereby , the measured blood velocity waveform of the maximum velocity vp becomes a waveform that has traced the maximum velocity vp of the doppler spectrum image . subsequently , the measured waveform calculation part 91 calculates a function vp ( t ) that indicates the measured blood velocity waveform ( hereinafter referred to as “ measured blood velocity waveform vp ( t )”) from the detected measured blood velocity waveform . furthermore , the measured waveform calculation part 91 transmits the measured blood velocity waveform vp ( t ) to the waveform estimation part 93 and the interpolation part 94 . the ecg waveform acquisition part 92 receives a signal from an electrocardiograph 10 , synchronizes the signal with the measured blood velocity waveform calculated by the measured waveform calculation part 91 , and traces the maximum amplitude in the direction of that time to create an ecg waveform . furthermore , based on the created ecg waveform , the ecg waveform acquisition part 92 creates a function u ( t ) that indicates the ecg waveform ( hereinafter referred to as “ ecg waveform u ( t )”). subsequently , the ecg waveform acquisition part 92 transmits the created ecg waveform u ( t ) to the waveform estimation part 93 . based on pre - collected statistical data of the ecg waveform of an individual patient for each age and disorder and an ideal blood velocity waveform of a corresponding individual patient with no effects of valve signals , a memory part 7 conducts system identification using an arx model ( auto - regressive exogenous model ) in order to model it into a model of a commonly used ideal blood velocity waveform and preliminarily stores a coefficient series of the model . this ideal blood velocity waveform with no effects of valve signals is the “ standard blood velocity waveform ” in the present invention . here , the arx model is a linear time - variant parametric model that is used for system identification and correlates a present output y ( t ) with limited past output data y ( t − k ) and input data u ( t − k ) ( for example , refer to “ system identification by matlab ” by shuichi adachi , tokyo denki university press ). the method of calculating the above mentioned coefficient series will now be described . firstly , ages and disorders are classified into groups , and several hundred cases of ecg ( electrocardiogram ) waveforms and ideal blood velocity waveforms with no effects of valve signals are collected for each group . at this time , as a method of obtaining an ideal blood velocity waveform , a blood velocity waveform with no effects of valve signals is obtained by measuring the blood velocity at a part with no reciprocal valves in the circulatory organ . alternatively , for this purpose , a blood velocity waveform with no effects of valve signals is obtained by a physician with experience by manually eliminating the effects of valve signals from a measured blood velocity waveform based on their experience . next , based on the collected ecg waveform and ideal blood velocity waveform , system identification using the arx model is conducted . this is expressed with the following function , in which u ( t ) indicates an ecg waveform and yi ( t ) indicates a commonly used ideal blood velocity waveform . a ( q )* yi ( t )= b ( q )* u ( t − nk )+ e ( t ) e ( t ): residual difference ( i . e ., the difference between the expected value and the measured value ) nk : time delay from the commonly used ideal blood velocity waveform that corresponds to the ecg waveform a ( q )= 1 + a 1 q − 1 + . . . + a na q − na b ( q )= b 1 + b 2 q − 1 + . . .+ b nb q − nb + 1 ( a ( q ) and b ( q ) are irreducible polynomials of shift operator q ) na , nb , nk : integer arguments therefore , in the memory part 7 , a coefficient in the model of the commonly used ideal blood velocity waveform as shown below is preliminarily stored for each classified group . a i =( a 1 , a 2 , . . . , a na ), b j =( b 1 , b 2 , . . . , b nb ) the waveform estimation part 93 estimates the ideal blood velocity waveform for a patient whose blood velocity is currently being measured . this measurement is based on : the measured blood velocity waveform vp ( t ) ( received from the measured waveform calculation part 91 ); the ecg waveform u ( t ) ( received from the ecg waveform acquisition part 92 ); and the coefficient a i =( a 1 , a 2 , . . . , a na ), b j =( b 1 , b 2 , . . . , b nb ) stored in the memory part 7 . at this time , it is determined which of the above - mentioned groups the patient belongs to , and a coefficient that corresponds to the group is used for the coefficient that is used for the estimation . this estimated waveform is called an estimated waveform ye ( t ) as described below . this estimated waveform ye ( t ) can be expressed as follows . ye ( t )=− σ { a i * v p ( t − i )}+ σ { b j * u ( t − j )} the waveform estimation part 95 transmits the estimated waveform ye ( t ) to the interpolation part 94 . the interpolation part 94 stores the threshold for differences between the measured blood velocity waveform vp ( t ) and the estimated waveform ye ( t ). here , this threshold is a value indicating that the measured blood velocity waveform vp ( t ) is affected by valve signals at that time when the threshold is exceeded by the difference between the measured blood velocity waveform vp ( t ) and the estimated waveform ye ( t ). therefore , the purpose of this threshold is to exclude the effects of high - speed valve signals , and if approximation to the estimated waveform is strongly requested , almost all values are excluded . thus , it is preferable to set this threshold according to any requests on how much range should be left as the range of excluded effects of valve signals and a range of the measured blood velocity waveform vp ( t ) after excluding the effects of valve signals . moreover , the interpolation part 94 calculates the difference between the measured blood velocity waveform vp ( t ) and the estimated waveform ye ( t ) in the patient whose received present blood velocity is being measured and determines parts where the difference exceeds the threshold . in the present embodiment , a threshold is given for both positive and negative sides . however , this threshold may be set using another method . for example , because the value is higher in parts with the effects of valves compared to the estimated waveform , the threshold value may be set only on the positive side when the estimated waveform is subtracted from the measured blood velocity waveform . moreover , when the measured blood velocity waveform is subtracted from the estimated waveform , the threshold value may be set only on the negative side . furthermore , the absolute value of the difference between the measured blood velocity waveform and the estimated waveform may be used to set the threshold for the absolute value . the interpolation part 94 excludes parts exceeding the threshold from the measured blood velocity waveform vp ( t ) of the patient whose blood velocity is currently being measured . furthermore , the interpolation part 94 plugs the estimated waveform ye ( t ) into the excluded parts of the measured blood velocity waveform vp ( t ). moreover , the interpolation part 94 interpolates the gap between the estimated waveform ye ( t ) and the measured blood velocity waveform vp ( t ). the method for this interpolation is not limited to any particular kind , and any methods may be used , including linear interpolation , spline interpolation , or interpolation with a linear prediction using the peak of the measured blood velocity waveform . moreover , in the present embodiment , interpolation is conducted after plugging the estimated waveform ye ( t ) into the excluded parts , but the excluded parts of the measured blood velocity waveform vp ( t ) may be directly interpolated without plugging the estimated waveform ye ( t ). the method for this interpolation is also not limited to any particular kind , and any methods may be used , including linear interpolation , spline interpolation , or interpolation with a linear prediction using the peak of the measured blood velocity waveform . at this time , because the process of linear interpolation is simple , the burden applied to the interpolation part 94 is small . on the other hand , with spline interpolation and a method of interpolating with a linear prediction using the peak of the measured blood velocity waveform , the processes are complicated but interpolation can be conducted with a smooth curve , and thus a waveform that is closer to the actual waveform can be created . furthermore , spline interpolation is effective when the interval for interpolation is short , but with the interpolation method of a linear prediction using the peak of the measured blood velocity waveform , interpolation can be conducted even when the interval for interpolation is long . the blood velocity waveform created by this interpolation part 94 is called the “ waveform for range setup ” as described below . the interpolation part 94 transmits the waveform for range setup to the velocity range setup part 95 . the velocity range setup part 95 conducts statistical computing to calculate the upper limit and the lower limit of the velocity range . here , statistical computing includes a normal distribution model in which : a histogram is created from the waveform for range setup to calculate the velocity distribution ; the mean and the variance are calculated from the distribution of the waveform for range setup that has been weighted based on the velocity distribution ; the mean ± coefficient × σ becomes estimate values for the upper and lower limits of the velocity range ; and a post - smoothing threshold processing model in which values that correspond to the coefficient % of the peak value become the upper and lower limits of the velocity range according to the distribution of the weighted waveform for range setup , etc . the method of calculating this velocity range is described in detail in japanese published unexamined application no . 2005 - 185731 . subsequently , the velocity range setup part 95 calculates the repetition frequency ( prf ) that corresponds to the set velocity range . moreover , the velocity range setup part 95 calculates the maximum velocity range from the maximum value on the upper side ( positive side ) from the current reference position ( baseline ) and the minimum velocity range from the maximum value on the lower side ( negative side ) using the waveform for range setup and compares the maximum velocity range with the minimum velocity range to calculate the displacement of the baseline ( reference position ). for example , if the mean value of the maximum velocity range and the minimum velocity range is placed in the center of the screen , the shift amount is calculated by obtaining the distance between the mean value and the baseline (= 0 ). the velocity offset ( bls ), which is the displacement of the reference position ( baseline ), is calculated . the method of calculating this velocity offset ( bls ) is described in detail in japanese published unexamined application no . 2005 - 185731 . as described above , once the repetition frequency ( prf ) and the velocity offset ( bls ) are decided , the velocity range setup part 95 outputs the repetition frequency ( prf ) to the transceiving part 3 . moreover , the velocity range setup part 95 simultaneously outputs the velocity offset ( bls ) to the fft calculation part 54 of the doppler signal - processing part 5 . additionally , in the present embodiment , the auto range / auto bls - processing part 9 may be constituted as hardware or software . for example , by constituting the auto range / auto bls - processing part 9 using a cpu and executing a program by reading the program from a memory area ( not shown ), the functions of the measured waveform calculation part 91 , the ecg waveform acquisition part 92 , the waveform estimation part 93 , the interpolation part 94 , and the velocity range setup part 95 may be executed . at this time , in the present embodiment , adjustments of the velocity offset and the velocity range are both made , but the ultrasonic imaging apparatus of the present invention is operable only by the adjustment of the velocity range . in that case , the offset is not displaced and always has 0 hz as a reference , but a doppler spectrum image with the velocity range adjusted and the folding reduced can be obtained . a sequence of actions of the ultrasonic imaging apparatus related to embodiment 1 of this invention will now be described with reference to fig3 . fig3 is a diagram of a flow chart illustrating a sequence of actions of the ultrasonic imaging apparatus related to embodiment 1 of this invention . firstly , ultrasound is transmitted to the body to be examined and a b - mode cross - sectional image and a doppler spectrum image are generated based on the reflected waves from the body to be examined . the doppler waveform data generated in the fft calculation part 54 is output from the fft calculation part 54 to the display part 8 via the dsc 6 and displayed on the display part 8 along with the b - mode cross - sectional image . furthermore , the doppler waveform data is output from the fft calculation part 54 to the auto trace part 7 . once the doppler waveform is acquired in step s 001 , the measured waveform calculation part 91 traces a marginal region of the doppler spectrum image ( maximum velocity vp ) in the direction of that time to detect the blood velocity waveform of the maximum velocity vp . furthermore , the measured waveform calculation part 91 calculates the measured blood velocity waveform vp ( t ), which is a function that indicates the blood velocity waveform of the maximum velocity vp . the measured waveform calculation part 91 then outputs the measured blood velocity waveform vp ( t ) to the waveform estimation part 93 and the interpolation part 94 . in step s 003 , the ecg waveform acquisition part 92 traces the maximum amplitude of a signal received from the electrocardiograph 10 and calculates the ecg waveform u ( t ), which is a function that indicates the traced waveform . the ecg waveform acquisition part 92 then outputs the ecg waveform u ( t ) to the waveform estimation part 93 . in step s 004 , the waveform estimation part 93 estimates the ideal blood velocity waveform ( estimated waveform ye ( t )) of a patient whose blood velocity is currently being measured . this estimation is based on the measured blood velocity waveform vp ( t ), ecg waveform u ( t ), and a coefficient of a model of a commonly used ideal blood velocity waveform preliminarily stored in the memory part 7 . the waveform estimation part 93 then outputs the estimated waveform ye ( t ) to the interpolation part 94 . the interpolation part 94 calculates the difference between the measured blood velocity waveform vp ( t ) and the estimated waveform ye ( t ), excludes excess parts of the difference over the stored threshold from the measured blood velocity waveform vp ( t ), and interpolates the excluded parts in order to calculate the waveform for range setup . the velocity range setup part 95 conducts a statistical calculation process based on the waveform for range setup to calculate the repetition frequency ( prf ) and velocity offset ( bls ). as described above , once the repetition frequency ( prf ) and the velocity offset ( bls ) are determined , the velocity range setup part 95 outputs the repetition frequency ( prf ) to the transceiving part 3 . at the same time , the velocity range setup part 95 outputs the velocity offset ( bls ) to the fft calculation part 54 in the doppler signal - processing part 5 . the transceiving part 3 transmits and receives ultrasound to and from the ultrasonic probe 2 according to the repetition frequency ( prf ) calculated by the velocity range setup part 95 . moreover , according to the velocity offset ( bls ) calculated by the velocity range setup part 95 , the fft calculation part 54 changes the read address of the fft process by the shift amount to adjust the velocity offset . thereby , the velocity range and the velocity offset ( bls ) are updated . as described above , according to the ultrasonic imaging apparatus 1 related to this embodiment , the velocity range and the velocity offset of the blood velocity waveform with the effects of valve signals excluded based on the doppler spectrum image acquired by scanning are obtained automatically . moreover , by using the velocity range and the velocity offset , the doppler velocity range , etc . can be changed following shifts in the state of the blood flow . with reference to fig4 a - d , the display of a blood velocity waveform will be described below . for this purpose , an example of a blood velocity waveform with the effects of valve signals excluded by using the ultrasonic imaging apparatus related to the present embodiment is used , along with a comparative example of a blood velocity waveform formed with a conventional method without using the ultrasonic imaging apparatus related to the present embodiment . fig4 a is a diagram of a graph for calculating the blood velocity waveform using the ultrasonic imaging apparatus related to the present invention . fig4 b is a graph in which the velocity range of the blood velocity waveform has been set up manually in a conventional ultrasonic imaging apparatus . fig4 c is a graph that shows an ideal velocity range of the blood velocity waveform in the present example . fig4 d is a graph in which the velocity range of the blood velocity waveform has been set up using the ultrasonic imaging apparatus related to the present embodiment . each graph of fig4 is a graph that shows the velocity range ( khz ) in the vertical axis and time ( sec .) in the horizontal axis . the graph 501 shown in fig4 a is a graph that shows the measured blood velocity waveform vp ( t ) before the effects of valves have been excluded ; the graph 502 is a graph that shows the estimated waveform ye ( t ); the graph 503 is a graph that shows the ecg waveform ecg ( t ) that corresponds to the blood velocity waveform of the graph 501 ; and the graph 504 is a graph that shows the blood velocity waveform with the effects of valves excluded using the ultrasonic imaging apparatus related to the present embodiment . in the example , firstly , the measured blood velocity waveform vp ( t ) shown in the graph 501 is created by conducting a doppler automatic trace for a measured doppler signal . then , the estimated waveform ye ( t ) shown in the graph 502 is created using the ecg waveform ecg ( t ) shown in the graph 503 and the ideal blood velocity waveform that has been statistically calculated . subsequently , excess parts of the difference between this estimated waveform ye ( t ) and the measured blood velocity waveform vp ( t ) over the threshold , are excluded and interpolated , thus creating the blood velocity waveform with the effects of valves excluded shown in the graph 504 . at this time , if the blood velocity waveform is displayed without excluding the effects of valves from the measured waveform vp ( t ), the velocity range is required to be 5 . 6 ( khz ). on the other hand , if the effects of valves is excluded by manual operation from the measured waveform vp ( t ) according to the relevant art , it is possible to have a velocity range of 3 . 9 ( khz ) as shown in fig4 b . however , if the velocity range is calculated based on an ideal waveform statistically calculated considering minimization of the effects of valves , it is ideal to have a velocity range of 3 . 2 ( khz ) for the blood velocity waveform in the present example . therefore , if the blood velocity waveform with the effects of valves excluded shown in the graph 504 is used using the ultrasonic imaging apparatus related to the present embodiment , it is possible to have the velocity range of 3 . 2 ( khz ) as shown in fig4 d . as described above , while it is difficult to obtain an ideal velocity range using manual operation , it is possible to obtain a velocity range near the ideal velocity range by excluding the effects of valves using the ultrasonic imaging apparatus of the present embodiment . here in the present embodiment , the arx model is used for system identification , but other mathematical models may be used if they are parametric models for system identification ( for example , refer to “ advanced system identification for control ” by shuichi adachi , tokyo denki university ). this parametric model includes an fir ( finite impulse response ) model , an armax ( auto regressive moving average exogenous ) model , an oe ( output error ) model , and a bj ( box and jenkins ) model , as well as the arx model and other models . the parametric model for system identification is expressed as shown in fig5 . fig5 is a diagram showing the parametric model for system identification . in fig5 , a ( z )* y ( k )={ b ( z )/ f ( z )}* u ( k )+{ c ( z )/ d ( z )}* w ( k ). a ( z )= 1 + a 1 * z − 1 + . . .+ a n * z − n b ( z )= b 1 * z − 1 + b 2 * z − 2 + . . .+ b m * z − m c ( z )= c 1 * z − 1 + c 2 * z − 2 + . . .+ c p * z − p d ( z )= 1 + d 1 * z − 1 + d 2 * z − 2 + . . . + d q * z − q f ( z )= 1 + f 1 * z − 1 + f 2 * z − 2 + . . . + f r * z − r moreover , the parametric model for system identification is expressed as follows . e ( k )+ d 1 * e ( k − 1 )+ . . .+ d q * e ( k − q )= c 1 * w ( k − 1 )+ c 2 * w ( k − 2 )+ c p * w ( k − p ) x ( k )+ f 1 * x ( k − 1 )+ . . .+ f q * x ( k − q )= b 1 * u ( k − 1 )+ b 2 * u ( k − 2 )+ b m * w ( k − m ) y ( k )+ a 1 * y ( k − 1 )+ . . .+ a q * y ( k − q )= e ( k )+ x ( k ) moreover , in the present embodiment , the velocity range is adjusted after the interpolation , but only the interpolated blood velocity waveform with the effects of valves excluded may be created . with this configuration , the blood velocity waveform with the effects of valves excluded can be acquired , facilitating the measurement of blood flow amount and improving the accuracy of measurement . furthermore , the velocity range may be adjusted by using the blood velocity waveform with the effects of valves excluded without interpolation . in this case , the velocity range setup part 95 stores the threshold . the velocity range setup part 95 then compares the estimated waveform with the measured blood velocity waveform to calculate parts that exceed the threshold . with this configuration , the accuracy of the velocity range adjustment decreases by a few %, but because the calculation becomes simple , the speed of calculating the velocity range can be improved . next , an ultrasonic imaging apparatus related to embodiment 2 of this invention will be described . the ultrasonic imaging apparatus 1 a related to embodiment 2 further comprises an abnormality determination part 11 in addition to the ultrasonic imaging apparatus 1 related to embodiment 1 . fig6 is a block diagram illustrating the functions of the ultrasonic imaging apparatus related to embodiment 2 . the determination of an abnormality in the ultrasonic imaging apparatus 1 a is described below . an abnormality determination part 11 creates a state space based on individual ideal blood velocity waveforms with no effects of valve signals for each age and disorder stored in the memory part 7 as statistical data . at this time , the state space is a space that includes blood velocity waveforms that can be considered as being in a normal state . the abnormality determination part 11 acquires a measured blood velocity waveform vp ( t ) from the measured waveform calculation part 91 . the abnormality determination part 11 selects a corresponding state space based on the age and disorder of the patient with the blood velocity waveform vp ( t ) and calculates the mahalanobis &# 39 ; generalized distance between the state space and the blood velocity waveform vp ( t ). at this time , the mahalanobis &# 39 ; generalized distance is an index using the correlation between variables and is a distance scale that indicates the distance from the target reference space . the abnormality determination part 11 determines that the blood velocity is abnormal when the calculated mahalanobis &# 39 ; generalized distance exceeds the pre - stored threshold for the mahalanobis &# 39 ; generalized distance . the abnormality determination part 11 then notifies the operator that the blood velocity is abnormal using the display part 8 , etc . thereby , any abnormality in blood velocity that exceeds the threshold is automatically reported to the operator , and thus oversights of abnormalities in blood velocity can be reduced and a faster and more accurate diagnosis can be provided for a patient .
transmitting and receiving ultrasound with repetition frequency that corresponds to velocity range indicating the measurable velocity to and from a diagnostic site that contains moving fluid within a body to be examined . generating doppler spectrum image showing velocity of moving fluid based on signals obtained from transmission and reception of ultrasound . storing modeled value based on model correlating standard blood velocity waveform with an ecg waveform . calculating measured blood velocity waveform based on spectrum image of a specified patient . acquiring ecg waveform at timing corresponding to measured blood velocity waveform . estimating blood velocity waveform excluding effects of valve signals of patient based on measured blood velocity waveform , ecg waveform , and modeled value . comparing measured blood velocity waveform with estimated blood velocity waveform , to exclude excess parts of the difference over a threshold from measured blood velocity waveform , and to interpolate excluded parts of measured blood velocity waveform .