Patent Application
20130035594
1. Field of the Invention
The present invention relates to an ultrasonic observation apparatus that allows an observation of tissues of a subject by using ultrasonic waves, an operation method of the same, and a computer readable recording medium.
2. Description of the Related Art
Conventionally, a technique known as an ultrasound elastography has been known as a technique using ultrasonic waves for an examination of a breast cancer and the like (see International Publication No. 2005/122906, for example). The ultrasound elastography is a technique of utilizing a diagnostic that tissues developing a cancer or a tumor in an organism vary in hardness depending on a development status of a disease or on an individual. In this technique, an amount of strain and a modulus of elasticity of biological tissues in an examination site are measured by using ultrasonic waves under a condition where a compression is applied externally on the examination site and a result of the measurement is displayed as a cross-sectional image.
According to an aspect of the present invention, an ultrasonic observation apparatus that transmits an ultrasonic wave to a subject and receives an ultrasonic wave reflected by the subject includes: a reference spectrum storage unit that stores a first reference spectrum in a first reception depth range and a second reference spectrum in a second reception depth range obtained based on a frequency of an ultrasonic wave received from a reference reflector; a frequency analyzer that calculates a frequency spectrum by analyzing a frequency of the received ultrasonic wave; and a corrected frequency spectrum calculator that calculates a corrected frequency spectrum by determining whether a reception depth of the frequency spectrum calculated by the frequency analyzer is the first reception depth range or the second reception depth range, and obtaining a difference, in a case of the first reception depth range, between the first reference spectrum and the frequency spectrum and a difference, in a case of the second reception depth range, between the second reference spectrum and the frequency spectrum.
According to another aspect of the present invention, an operation method of an ultrasonic observation apparatus that transmits an ultrasonic wave to a subject and receives an ultrasonic wave reflected by the subject includes: calculating a frequency spectrum by a frequency analyzer by analyzing a frequency of a received ultrasonic wave; storing a first reference spectrum in a first reception depth range and a second reference spectrum in a second reception depth range obtained based on a frequency of an ultrasonic wave received from a reference reflector; and calculating a corrected frequency spectrum by determining whether a reception depth of the frequency spectrum calculated at the calculating is the first reception depth range or the second reception depth range and by obtaining a difference, in a case of the first reception depth range, between the first reference spectrum and the frequency spectrum and a difference, in a case of the second reception depth range, between the second reference spectrum and the frequency spectrum.
According to still another aspect of the present invention, in a non-transitory computer readable recording medium with an executable program stored thereon, the program instructs a processor to execute: calculating a frequency spectrum by a frequency analyzer by analyzing a frequency of a received ultrasonic wave; storing a first reference spectrum in a first reception depth range and a second reference spectrum in a second reception depth range obtained based on a frequency of an ultrasonic wave received from a reference reflector; and calculating a corrected frequency spectrum by determining whether a reception depth of the frequency spectrum calculated at the calculating is the first reception depth range or the second reception depth range and by obtaining a difference, in a case of the first reception depth range, between the first reference spectrum and the frequency spectrum and a difference, in a case of the second reception depth range, between the second reference spectrum and the frequency spectrum.
The above and other features, advantages, and technical and industrial significance of this invention will be better understood by reading the following detailed description of presently preferred embodiments of the invention, when considered in connection with the accompanying drawings.
Exemplary embodiments of the present invention (hereinafter referred to as “embodiments”) will be explained below with reference to the accompanying drawings.
The ultrasonic observation apparatus 1 is provided with an ultrasonic probe 2 that outputs an ultrasonic pulse to an outside and also receives an ultrasonic echo reflected at the outside, a transceiver 3 that transmits and receives an electrical signal to and from the ultrasonic probe 2, an operation unit 4 that performs a predetermined operation with respect to an electrical echo signal obtained by converting the ultrasonic echo, an image processor 5 that generates image data corresponding to the electrical echo signal obtained by converting the ultrasonic echo, an input unit 6 that is realized by using an interface such as a keyset, a mouse, and a touchscreen and accepts an input of information of various kinds, a display unit 7 that is realized by using a display panel formed by a crystal liquid or an organic EL and displays information of various kinds including images generated by the image processor 5, a storage unit 8 that stores information of various kinds including information concerning a tissue property of a known subject, and a control unit 9 that performs an operation control of the ultrasonic observation apparatus 1.
The ultrasonic probe 2 is provided with a signal converter 21 that converts the electrical pulse signal received from the transceiver 3 into an ultrasonic pulse (acoustic pulse signal) and converts the ultrasonic echo reflected by the subject outside into an electrical echo signal. The ultrasonic probe 2 may be configured such that an ultrasonic transducer mechanically scans or a plurality of ultrasonic transducers electronically scan.
The transceiver 3 is electrically connected to the ultrasonic probe 2, transmits a pulse signal to the ultrasonic probe 2, and receives an echo signal from the ultrasonic probe 2. Specifically, the transceiver 3 generates a pulse signal based on a preset waveform and transmission time and transmits the generated pulse signal to the ultrasonic probe 2. Besides, the transceiver 3 performs an A/D conversion after performing processes including amplification, filtering, and the like on the received echo signal to generate and output a digital RF signal. In the case where the ultrasonic probe 2 is configured to make a plurality of ultrasonic transducers electronically scan, the transceiver 3 includes a multichannel circuit for a beam synthesis to deal with the plurality of ultrasonic transducers.
The operation unit 4 is provided with a frequency analyzer 41 that calculates a frequency spectrum (power spectrum) of an echo signal by performing a fast Fourier transform (FFT) on the digital RF signal output from the transceiver 3, a frequency band setting unit 42 that sets a frequency band used in approximating the frequency spectrum calculated by the frequency analyzer 41, a corrected frequency spectrum calculator 43 that calculates a corrected frequency spectrum by correcting the frequency spectrum calculated by the frequency analyzer 41 based on a predetermined reference spectrum stored in the storage unit 8, a feature data extracting unit 44 that extracts feature data of a subject by performing an approximating process and an attenuation correcting process of reducing a contribution of an attenuation generated depending on a reception depth and a frequency of ultrasonic waves in the transmission of ultrasonic waves, and a tissue property determining unit 45 that determines a tissue property in a predetermined area of the subject by using the feature data extracted by the feature data extracting unit 44.
The frequency analyzer 41 calculates a frequency spectrum by performing, with respect to each sound ray (line data), the fast Fourier conversion on an FFT data group including a predetermined volume of data. A frequency spectrum shows a tendency specific to a tissue property of a subject. This is because a frequency spectrum has a correlation with size, density, acoustic impedance, and the like of a subject which is a scattering substance that scatters ultrasonic waves.
The frequency band setting unit 42 performs a frequency band setting by reading out from the storage unit 8 and referring to a frequency band table, which will be explained later, stored by the storage unit 8. The reason why the frequency band setting is changed for each reception depth in this manner is that there is a possibility in ultrasonic waves that efficient information of high frequency component is lost and inefficient information remains in an echo signal received from a site whose reception depth is large since a higher frequency component attenuates more quickly. By taking this aspect into consideration, a frequency band is set in the first embodiment so that a band width becomes narrower and a maximum frequency becomes smaller as a reception depth is larger.
The corrected frequency spectrum calculator 43 reads out from the storage unit 8 and refers to reference spectrum information, which will be explained later, stored in the storage unit 8, calculates a difference between the reference spectrum and a frequency spectrum for each reception depth, and calculate a corrected frequency spectrum. The reason why the correction of the frequency spectrum is performed for each reception depth is the same as the reason for the setting of the frequency band explained above.
The feature data extracting unit 44 is provided with an approximating unit 441 that calculates, by performing an approximating process on the corrected frequency spectrum calculated by the corrected frequency spectrum calculator 43, before-correction feature data before an attenuation correcting process is performed, and an attenuation corrector 442 that performs the attenuation correcting process on the before-correction feature data approximated by the approximating unit 441 to extract feature data.
The approximating unit 441 approximates a frequency spectrum by a primary expression via a regression analysis to extract the before-correction feature data which defines the approximate primary expression. Specifically, the feature data extracting unit 44 calculates a slope a0 and an intercept b0 of the primary expression via the regression analysis and also calculates intensity at a specific frequency within a frequency band in the frequency spectrum as the before-correction feature data. While the approximating unit 441 is configured to calculate an intensity (Mid-band fit) “c0=a0fMID+b0” in a middle frequency “fMID=(fLOW+fHIGH)/2” in the first embodiment, this is just one example. The “intensity” here indicates any one of parameters such as a voltage, an electric power, a sound pressure, and an acoustic energy.
Among the feature data of three kinds, the slope a0 has a correlation with a size of a scattering substance that scatters ultrasonic waves and it is considered that the slope has a smaller value as the scattering substance is larger in size in general. Besides, the intercept b0 has a correlation with a size of the scattering substance, a difference in acoustic impedance, density (consistency) of the scattering substance, and the like. Specifically, the intercept b0 is considered to have a larger value as the scattering substance is larger in size, to have a larger value as a value for the acoustic impedance is larger, and to have a larger value as a value for the density (consistency) of the scattering substance is larger. The intensity c0 in the middle frequency fMID (hereinafter simply referred to as “intensity”) is an indirect parameter obtained from the slope a0 and the intercept b0 and provides spectrum intensity in the middle within an efficient frequency band. Therefore, the intensity c0 is considered to have a certain level of correlation with a brightness of the B-mode image in addition to the size of the scattering substance, the difference in acoustic impedance, and the density of the scattering substance. Here, an approximating polynomial calculated by the feature data extracting unit 44 is not limited to the primary expression and an approximating polynomial of quadratic or higher expression may be used.
A correction performed by the attenuation corrector 442 will be explained. An attenuation amount A of ultrasonic waves can be expressed as follows:
A=2αzf (1)
Here, a symbol “α” indicates an attenuation rate, a symbol “z” indicates a reception depth of ultrasonic waves, and a symbol “f” indicates a frequency. As evidenced by expression (1), the attenuation amount A is proportional to the frequency f. A specific value for the attenuation rate α is 0 to 1.0 (dB/cm/MHz), more preferably 0.3 to 0.7 (dB/cm/MHz) in a case of a biological body, and the value is determined depending on the kind of an organ as an observation target. For example, in a case where an organ as an observation target is a pancreas, “α=0.6 (dB/cm/MHz)” is determined. Here in the first embodiment, it is also possible to make a configuration such that the value for the attenuation rate a can be changed by an input from the input unit 6.
The attenuation corrector 442 corrects the before-correction feature data (the slope a0, the intercept b0, and the intensity c0) extracted by the approximating unit 441 as follows.
a=a
0+2αz (2)
b=b
0 (3)
c=c
0+2αzfMID (=afMID+b) (4)
As evidenced by expressions (2) and (4), the attenuation corrector 422 performs a correction whose correction amount is larger as the reception depth z of ultrasonic waves is larger. Besides, according to expression (3), a correction concerning to the intercept is an identical transformation. This is because the intercept is a frequency component corresponding to the frequency 0 (Hz) and is not subject to the attenuation.
The tissue property determining unit 45 calculates an average and a standard deviation of feature data of the frequency spectrum extracted by the feature data extracting unit 44 for each feature data. The tissue property determining unit 45 determines a tissue property of a predetermined area of the subject by using the calculated average and the standard deviation and an average and a standard deviation of feature data, stored in the storage unit 8, of a frequency spectrum of a known subject. The “predetermined area” here means an area in an image specified, via the input unit 6, by an operator of the ultrasonic observation apparatus 1 who watches images generated by the image processor 5 (hereinafter referred to as “area of interest”). Besides, the “the tissue property” here means any one of a cancer, an endocrine tumor, a mucinous tumor, normal tissues, and a vascular channel, for example. In the case where the subject is a pancreas, a chronic pancreatitis, an autoimmune pancreatitis, and the like are included as the tissue property.
The average and the standard deviation of the feature data calculated by the tissue property determining unit 45 reflect changes at a cellular level such as an enlargement of a nucleus and a heteromorphy and changes in tissues such as a fibrous growth in interstitium and a fibrosis substituted with parenchymal tissues, and indicate a value specific to each tissue property. Therefore, it becomes possible to accurately determine a tissue property in a predetermined area of the subject by using the average and the standard deviation of the feature data.
The image processor 5 is provided with a B-mode image data generator 51 that generates B-mode image data for performing a display by converting an amplitude of an echo signal into a brightness and a determination result displaying image data generator 52 that generates a determination result displaying image data for performing a display of a determination result of the tissue property in the area of interest and information related to the determination result by using the data output by the B-mode image data generator 51 and the operation unit 4.
The B-mode image data generator 51 generates B-mode image data by performing a signal process using known techniques such as a band-pass filter, a logarithmic transformation, a gain process, and a contrast process on the digital signal, and also culling data depending on a data step width which is determined in accordance with a display range of an image in the display unit 7.
The determination result displaying image data generator 52 generates determination result displaying image data including the determination result of the tissue property in the area of interest and a tissue property emphasized image in which the tissue property is emphasized by using the B-mode image data generated by the B-mode image data generator 51, the feature data extracted by the feature data extracting unit 44, and the determination result determined by the tissue property determining unit 45.
The storage unit 8 is provided with a known subject information storage unit 81 that stores information of a known subject, a frequency band information storage unit 82 that stores frequency band information determined depending on a reception depth of ultrasonic waves, a reference spectrum information storage unit 83 that stores reference spectrum information depending on a reception depth of ultrasonic waves, a window function storage unit 84 that stores a window function which is used in a frequency analyzing process performed by the frequency analyzer 41, and a correction information storage unit 85 that stores correction information which is referred to when an attenuation corrector 442 performs the process.
The known subject information storage unit 81 stores, by associating with a tissue property of a known subject, feature data of a frequency spectrum extracted with respect to the known subject. Besides, the known subject information storage unit 81 stores, with respect to the feature data of the frequency spectrum related to the known subject, an average and a standard deviation calculated for each of groups classified based on tissue properties of known subjects, together with the data of all kinds of the feature data of the known subjects. Here, the feature data of the known subjects is extracted in the same process as the first embodiment. It should be noted that it is not necessary to perform the process of extracting feature data of the known subjects in the ultrasonic observation apparatus 1. It is preferable that information of the known subjects stored in the known subject information storage unit 81 has a high degree of reliability on tissue property.
The reference spectrum information storage unit 83 stores, as frequency information depending on each reception depth of ultrasonic waves on a predetermined reference reflector, a frequency spectrum calculated based on an echo signal obtained by being reflected by the reference reflector (hereinafter referred to as “reference spectrum”). The reference reflector is an ideal reflector on which ultrasonic waves do not scatter, through which ultrasonic waves do not pass, and by which ultrasonic waves are not absorbed, for example. The reference spectrum is calculated for each kind of the ultrasonic probe 2 and for each reception depth of ultrasonic waves. Here, the reason why the reference spectrum is calculated for each of different ultrasonic probes 2 is that a transducer differs depending on the kind of the ultrasonic probes 2 and therefore there is a difference in a waveform of pulse to be transmitted. Here, it is not necessary that the reference reflector is the ideal reflector in a sense explained above.
The window function storage unit 84 stores at least one of window functions such as Hamming window, Hanning window, and Blackman window.
The correction information storage unit 85 stores information concerning conversion of expressions (2) to (4).
The storage unit 8 is realized by using a ROM that stores in advance an operation program of the ultrasonic observation apparatus according to the first embodiment, a program for starting the operation system, and the like, and a RAM that stores operation parameters of various processes, data, and the like.
Components other than the ultrasonic probe 2 of the ultrasonic observation apparatus 1 having functional configuration explained above are realized by using a computer provided with a CPU having an operating function and a controlling function. The CPU provided in the ultrasonic observation apparatus 1 executes an operating process related to an operating method of the ultrasonic observation apparatus according to the first embodiment by reading out, from the storage unit 8, information memorized and stored in the storage unit 8 and programs of various kinds including the operation program of the ultrasonic observation apparatus explained above.
Here, it is possible to widely distribute the operation program of the ultrasonic observation apparatus according to the first embodiment by recording it in a computer-readable recording medium such as a hard disk, a flash memory, a CD-ROM, a DVD-ROM, and a flexible disk.
The control unit 9 then performs a control of making the display unit 7 display a B-mode image corresponding to the B-mode image data generated by the B-mode image data generator 51 (step S3).
After that, when an area of interest is set via the input unit 6 (“Yes” at step S4), the frequency analyzer 41 calculates a frequency spectrum by performing a frequency analysis through the FFT operation (step S5). At this step S5, it is possible to set all area of the image as the area of interest. On the other hand, when an area of interest is not set (“No” at step S4) and an instruction to end the process is input via the input unit 6 (“Yes” at step S6), the ultrasonic observation apparatus 1 ends the process. In contrast, when an area of interest is not set (“No” at step S4) and the instruction to end the process is not input (“No” at step S6), the ultrasonic observation apparatus 1 returns to step S4.
Here, the process (step S5) performed by the frequency analyzer 41 will be explained in detail with reference to the flowchart shown in
The frequency analyzer 41 then calculates all frequency spectra for a plurality of data positions set on one sound ray. The frequency analyzer 41 first sets an initial value Z0 for a data position Z (corresponding to a reception depth) which represents a series of data group (FFT data group) obtained for the FFT operation (step S22).
After that, the frequency analyzer 41 obtains FFT data group of the data position Z (step S23) and makes the window function stored in the window function storage unit 84 work on the obtained FFT data group (step S24). By making the window function work on the FFT data group, it is possible to avoid a discontinuity of the FFT data group at a border and prevent an occurrence of an artifact.
The frequency analyzer 41 then determines whether or not the FFT data group of the data position Z is a normal data group (step S25). Here, it is necessary that the FFT data group has data pieces whose number is a power of two. The number of data pieces of the FFT data group will be expressed as 2n (“n” being a positive integer) below. The description “the FFT data group is normal” means that the data position Z locates at a 2n-1th position from the front in the FFT data group. In other words, the description “the FFT data group is normal” means that there is 2n-1−1 (=N) pieces of data before the data position Z and there is 2n-1 (=M) pieces of data after the data position Z. In the case shown in
As a result of the determination at step S25, when the FFT data group of the data position Z is normal (“Yes” at step S25), the frequency analyzer 41 moves to step S27, which will be explained later.
As a result of the determination at step S25, when the FFT data group of the data position Z is not normal (“No” at step S25), the frequency analyzer 41 generates a normal FFT data group by inserting zero for the deficiency (step S26). The FFT data group determined not to be normal at step S25 is worked on by the window function before the insertion of zero. Therefore, no discontinuity of data occurs even by inserting zero to the FFT data group. After step S26, the frequency analyzer 41 moves to step S27, which will be explained later.
At step S27, the frequency analyzer 41 obtains a frequency spectrum by performing the FFT operation by using the FFT data group (step S27).
The frequency analyzer 41 then adds a predetermined data step width D to the data position Z and calculates a data position Z of an FFT data group as a next analysis target (step S28). While it is preferable that the data step width D here is made to accord with the data step width used when the B-mode image data generator 51 generates the B-mode image data, a value larger than the data step width used by the B-mode image data generator may be set if it is requested to reduce an operation amount in the frequency analyzer 41.
After that, the frequency analyzer 41 determines whether or not the data position Z is larger than a last data position Zmax (step S29). Here, the last data position Zmax may be configured to be a data length of the sound ray LD or to be a data position corresponding to a lower end of the area of interest. When the data position Z is larger than the last data position Zmax as a result of the determination (“Yes” at step S29), the frequency analyzer 41 increases the sound ray number L by one (step S30). On the other hand, when the data position Z is not larger than the last data position Zmax (“No” at step S29), the frequency analyzer 41 returns to step S23. In this manner, the frequency analyzer 41 performs the FFT operation on FFT data groups whose number is [{(Zmax−Z0)/D}+1] (=K) with respect to one sound ray LD. Here, an integer [X]indicates a maximum integer not exceeding X.
When the sound ray number L after the increase at step S30 is larger than a last sound ray number Lmax (“Yes” at step S31), the frequency analyzer 41 returns to the main routine shown in
In this manner, the frequency analyzer 41 performs the FFT operation K times with respect to each of (Lmax−L0+1) sound rays. Here, the last sound ray number Lmax may be provided to the last sound ray that the transceiver 3 receives, or to a sound ray corresponding to a border at one of the left and the right of the area of interest, for example. A total number (Lmax−L0+1)×K of the FFT operations performed by the frequency analyzer 41 with respect to all the sound rays will be treated as “P” below.
After the frequency analyzing process at step S5 explained above, the frequency band setting unit 42 performs a frequency band setting for each reception depth of ultrasonic waves with reference to the frequency band table Tb stored in the frequency band information storage unit 82 (step S7). Here, the process of the frequency band setting unit 42 may be performed in parallel with the process of the frequency analyzer 41 or may be performed prior to the process of the frequency analyzer 41.
The reception depth corresponding to the spectrum curve C1 and the reception depth corresponding to the spectrum curve C3 are the same. Besides, the reception depth corresponding to the spectrum curve C2 and the reception depth corresponding to the spectrum curve C4 are the same. Frequency band is defined depending on the kind of the ultrasonic probe 2. As explained above, the reception depth in the case shown in
The corrected frequency spectrum calculator 43 then reads out from the reference spectrum information storage unit 83 and refers to a reference spectrum depending on the reception depth and the kind of the ultrasonic probe 2, and calculates a difference between the reference spectrum and the frequency spectrum calculated by the frequency analyzer 41 to calculate a corrected frequency spectrum (step S8.)
After step S8, the approximating unit 441 extracts before-correction feature data via the regression analysis on the frequency spectra whose number is P calculated by the frequency analyzer 41 as an approximating process (step S9). Specifically, the approximating unit 441 extracts, by calculating a primary expression that approximates a frequency spectrum of a frequency band fLow<f<f<fHIGH via the regression analysis, the slope a0, the intercept b0, and the intensity c0 which define the primary expression as before-correction feature data. Straight lines L1 to L4 respectively shown in
After this, the attenuation corrector 442 performs the attenuation correcting process on the before-correction feature dada extracted by the approximating unit 441 (step S10). In a case where a data sampling frequency is 50 MHz, for example, a time interval of the data sampling is 20 (nsec). Here, assuming that a sound velocity is 1530 (m/sec), an interval in distance of the data sampling is “1530 (m/sec)×20 (nsec)/2=0.0153 (mm)”. Assuming that the number of data steps from the first data piece in the sound ray LD to a data position in an FFT data group as a processing target is k, the data position Z becomes 0.0153 k (mm). The attenuation corrector 442 calculates the slop a, the intercept b, and the intensity c, which are the feature data of the frequency spectrum, by substituting the value for the data position Z obtained in this manner in the reception depth z in expressions (2) to (4) explained above.
I=af+b=(a0+2αZ)f+b0 (5)
As evidenced by expression (5), the straight line L1′ has a slop whose inclination is large and has the same value in intercept, compared to the straight line L1.
After this, the tissue property determining unit 45 determines a tissue property in the area of interest of the subject based on the feature data extracted by the feature data extracting unit 44 and the known subject information stored in the known subject information storage unit 81 (step S11).
Here, the process (step S11) performed by the tissue property determining unit 45 will be explained in detail with reference to the flowchart shown in
Since the classification and the determination of tissue properties also in obtaining feature data of a known subject are performed by using, as an indicator, feature data obtained via the attenuation correction on before-correction feature data of frequency spectrum obtained by the frequency analysis in the first embodiment, it is possible to clearly distinguish tissue properties which differ from each other. Especially, since feature data on which the attenuation correction is performed is used in the first embodiment, it is possible to obtain an area of each group in the feature data space in a condition where groups are separated more clearly, compared to the case of using feature data extracted without performing the attenuation correction.
After step S41, the tissue property determining unit 45 calculates distances dμ, dν, and dρ, on the feature data space, between the subject point Sp and respective points μ0, ν0, and ρ0 each of which has, as a coordinate in the feature data space, an average of intercepts b and an average of intensities c of frequency spectra in FFT data groups included in each of the groups Gμ, Gν, and Gρ, the points being hereinafter referred to as “known subject average point” (step S42). Here, when b-axis component and c-axis component in the feature data space differ significantly in scale, it is preferable to arbitrarily perform a weighting so that contributions of respective distances become nearly uniform.
The tissue property determining unit 45 then determines a tissue property of all the subject points including the subject point Sp based on the distances calculated at step S42 (step S43). For example, since the distance dμ is the smallest in the case shown in
After this, the tissue property determining unit 45 outputs the result of the distance calculation at step S42 and the result of the determination at step S43 (step S44). Thus, the tissue property determining process at step S11 is ended.
After step S11 explained above, the determination result displaying image data generator 52 generates determination result displaying image data by using the B-mode image data generated by the B-mode image data generator 51, the feature data calculated by the feature data extracting unit 44, and the determination result determined by the tissue property determining unit 45 (step S12).
The display unit 7 then displays the determination result displaying image generated by the determination result displaying image data generator 52 (step S13).
In the information displaying part 201, identifying information (ID number, name, sex, and the like) of the subject for example, the tissue property determination result obtained by the tissue property determining unit 45, information concerning the feature data in performing the tissue property determination, and information of ultrasonic image quality such as a gain and a contrast are displayed. Here, for the information concerning the feature data, it is possible to make a display utilizing an average and a standard deviation of feature data of frequency spectra of FFT data groups, the number of which is Q, present in an inside of the area of interest.
Specifically, it is possible to display “Slope=1.5±0.3 (dB/MHz), Intercept=−60±2 (dB), and Intensity=−50±1.5 (dB)”, for example in the information displaying part 201.
A tissue property emphasized image 300 displayed in the image displaying part 202 is a gray-scale image in which the intercept b is uniformly allotted to R (red), G (green), and B (blue) with respect to the B-mode image 100 shown in
Due to the display of the determination result displaying image 200 having the configuration explained above by the display unit 7, it becomes possible for the operator to grasp the tissue property in the area of interest more accurately. Here, the determination result displaying image is not limited to the configuration explained above. For example, the tissue property emphasized image and the B-mode image may be displayed side by side for the determination result displaying image. Thus, it is possible to recognize the difference between the two images on one frame.
The tissue property emphasized image 300 shown in
According to the first embodiment explained so far, it is possible to clearly determine the difference in tissues without using an amount of strain and a modulus of elasticity of biological tissues since a frequency spectrum is calculated by analyzing a frequency of received ultrasonic waves, a frequency band used in approximating the frequency spectrum is set, the frequency spectrum is corrected based on a reference spectrum read out from the storage unit that stores the reference spectrum obtained based on a frequency of ultrasonic waves received from the reference reflector, before-correction feature data is extracted by performing the approximating process on the corrected frequency spectrum, and then feature data of the subject is extracted by performing the attenuation correcting process in which the contribution of ultrasonic attenuation which depends on the reception depth and the frequency of ultrasonic waves is reduced. Hence, it is possible to enable distinguishing a tissue property accurately and to enhance the reliability for the observation result.
According to the first embodiment, it is possible to remove an influence of the attenuation associated with the transmission of ultrasonic waves and to perform a tissue property determination with higher accuracy since the attenuation correction is performed on the extracted feature data.
According to the first embodiment, it is possible to remove an influence of the attenuation associated with the transmission of ultrasonic waves and to perform a tissue property determination with even higher accuracy since the frequency band is determined so that the band width becomes narrower and the maximum frequency becomes smaller as the reception depth is larger.
A second embodiment of the present invention differs from the first embodiment in the feature data extracting process performed by the feature data extracting unit. A configuration of an ultrasonic observation apparatus according to the second embodiment is the same as that of the ultrasonic observation apparatus 1 explained in the first embodiment. Therefore, an identical component corresponding to a component of the ultrasonic observation apparatus 1 will be assigned with the same reference symbol in the explanation below.
In a feature data extracting process according to the second embodiment, the attenuation corrector 442 first performs the attenuation correcting process on the corrected frequency spectrum calculated by the corrected frequency spectrum calculator 43. After that, the approximating unit 441 extracts feature data of the frequency spectrum by performing the approximating process on the corrected frequency spectrum on which the attenuation correction is performed by the attenuation corrector 442.
At step S59, the attenuation corrector 442 performs the attenuation correction on the corrected frequency spectrum calculated by the corrected frequency spectrum calculator 43 (step S59).
After this, the approximating unit 441 extracts feature data of frequency spectrum via the regression analysis on all the frequency spectra on which the attenuation correction is performed by the attenuation corrector 442 (step S60). Specifically, the approximating unit 441 calculates the slope a, the intercept b, and the intensity c in the middle frequency fMID of the primary expression via the regression analysis. A straight line L5′ shown in
Processes of steps S61 to S63 sequentially correspond to the processes of steps S11 to S13 in
According to the second embodiment of the present invention explained so far, it is possible to clearly determine the difference in tissues without using an amount of strain and a modulus of elasticity of biological tissues since a frequency spectrum is calculated by analyzing a frequency of received ultrasonic waves, a frequency band used in approximating the frequency spectrum is set, the frequency spectrum is corrected based on a reference spectrum read out from the storage unit that stores the reference spectrum obtained based on a frequency of ultrasonic waves received from the reference reflector, the attenuation correcting process in which the contribution of ultrasonic attenuation which depends on the reception depth and the frequency of ultrasonic waves is reduced is performed on the corrected frequency spectrum, and then feature data of the subject is extracted by performing the approximating process. Hence, it is possible to enable distinguishing a tissue property accurately and to enhance the reliability for the observation result.
According to the second embodiment, it is possible to remove an influence of the attenuation associated with the transmission of ultrasonic waves and to perform a tissue property determination with higher accuracy since the attenuation correction is performed on the corrected frequency spectrum.
According to the second embodiment, it is possible to remove an influence of the attenuation associated with the transmission of ultrasonic waves and to perform a tissue property determination with even higher accuracy since the frequency band is determined so that the band width becomes narrower and the maximum frequency becomes smaller as the reception depth is larger.
A third embodiment of the present invention differs from the first embodiment in the tissue property determining process by the tissue property determining unit. A configuration of an ultrasonic observation apparatus according to the third embodiment is the same as that of the ultrasonic observation apparatus 1 explained in the first embodiment. Therefore, an identical component corresponding to a component of the ultrasonic observation apparatus 1 will be assigned with the same reference symbol in the explanation below.
The tissue property determining unit 45, after making up new populations by adding feature data (a, b, c) to each of the groups Gμ, Gν, and Gρ (see
After that, the tissue property determining unit 45 calculates a difference (hereinafter referred to simply as “difference in standard deviation”) between a standard deviation of each kind of the feature data of the groups Gμ, Gν, and Gρ in original populations constituted only by known subjects and a standard deviation of each kind of the feature data of the groups Gμ, Gν, and Gρ in the new populations in which the new subject is added each, and determines that a tissue property corresponding to a group including feature data whose difference in standard deviation is the smallest should be the tissue property of the subject.
Here, the tissue property determining unit 45 may calculate the difference in standard deviation only with respect to the difference in standard deviation of given pieces of feature data selected in advance among plural pieces of feature data. The selection of the feature data in this case may be arbitrarily performed by the operator or may be automatically performed by the ultrasonic observation apparatus 1.
Besides, the tissue property determining unit 45 may calculate a value in which a weight is arbitrarily added to the difference in standard deviation of all the feature data in each group and determine that a tissue property corresponding to a group the calculated value of which is the smallest should be the tissue property of the subject. In this case, when the feature data is “slope a, intercept b, and intensity c”, for example, the tissue property determining unit 45 performs, by setting weights for the slop a, the intercept b, and the intensity c, respectively to wa, wb and wc, a calculation of wa·(difference in standard deviation of a)+wb·(difference in standard deviation of b)+wc·(difference in standard deviation of c), and determines the tissue property of the subject based on the calculated value. Here, the values for the weights wa, wb and wc may be arbitrarily set by the operator or may be automatically set by the ultrasonic observation apparatus 1.
Besides, the tissue property determining unit 45 may calculate the square root of a value in which a weight is arbitrarily added to the square of the difference in standard deviation of all the feature data for each group, and determine that a tissue property corresponding to a group the square root of which is the smallest should be the tissue property of the subject. In this case, when the feature data is “slop a, intercept b, and intensity c”, for example, the tissue property determining unit 45 performs, by setting weights for the slop a, the intercept b, and the intensity c, respectively to w′a, w′b and w′c, a calculation of {w'a·(difference in standard deviation of a)2+w′b·(difference in standard deviation of b)2+ w′c·(difference in standard deviation of c)2}1/2, and makes the tissue property determination based on the calculated value. Here in this case, too, the values for the weights w′a, w′b and w′c may be arbitrarily set by the operator or may be automatically set by the ultrasonic observation apparatus 1.
According to the third embodiment of the present invention explained so far, it is possible to enable distinguishing a tissue property accurately, to enhance the reliability for the observation result, and to perform a tissue property determination with higher accuracy by removing an influence of the attenuation associated with the transmission of ultrasonic waves, similarly to the first embodiment explained above.
While the tissue property determining unit 45 determines the tissue property based on the change in standard deviation of each kind of feature data between an original population and another population in which a new subject is added in the third embodiment, this configuration is just one example. The tissue property determining unit 45 may determine the tissue property based on a change in average of each kind of the feature data between the original population and another population in which a new subject is added, for example.
While the embodiments of the present invention are explained so far, the present invention is not limited only to the first to the third embodiments explained above. In other words, the present invention may cover various embodiments within a scope not departing from the technical ideas as defined by the appended claims.
Additional advantages and modifications will readily occur to those skilled in the art. Therefore, the invention in its broader aspects is not limited to the specific details and representative embodiments shown and described herein. Accordingly, various modifications may be made without departing from the spirit or scope of the general inventive concept as defined by the appended claims and their equivalents.
| Number | Date | Country | Kind |
|---|---|---|---|
| 2010-253286 | Nov 2010 | JP | national |
This application is a continuation of International Application No. PCT/JP2011/76026, designating the United States and filed on Nov. 11, 2011 which claims the benefit of priority of the prior Japanese Patent Application No. 2010-253286, filed on Nov. 11, 2010, and the entire contents of the International application and the Japanese Application are incorporated herein by reference.
| Number | Date | Country | |
|---|---|---|---|
| Parent | PCT/JP2011/076026 | Nov 2011 | US |
| Child | 13561235 | US |
