WO2022040878A1 - 超声成像系统和超声图像分析方法 - Google Patents

超声成像系统和超声图像分析方法 Download PDF

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Publication number
WO2022040878A1
WO2022040878A1 PCT/CN2020/110875 CN2020110875W WO2022040878A1 WO 2022040878 A1 WO2022040878 A1 WO 2022040878A1 CN 2020110875 W CN2020110875 W CN 2020110875W WO 2022040878 A1 WO2022040878 A1 WO 2022040878A1
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Prior art keywords
lesion
target
features
display
preset
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PCT/CN2020/110875
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English (en)
French (fr)
Inventor
刘羽西
刘彦伯
安兴
丛龙飞
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深圳迈瑞生物医疗电子股份有限公司
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Priority to PCT/CN2020/110875 priority Critical patent/WO2022040878A1/zh
Priority to CN202080104345.5A priority patent/CN116157074A/zh
Publication of WO2022040878A1 publication Critical patent/WO2022040878A1/zh

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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/08—Detecting organic movements or changes, e.g. tumours, cysts, swellings

Definitions

  • the present application relates to the technical field of ultrasound imaging, and more particularly, to an ultrasound imaging system and an ultrasound image analysis method.
  • Breast cancer is a malignant tumor that occurs in the glandular epithelium of the breast.
  • the incidence and mortality of breast cancer have continued to increase year by year.
  • Common tumors that threaten women's physical and mental health have continued to increase year by year.
  • the incidence of thyroid diseases in the population is increasing year by year, and ultrasound imaging has become the first choice for the clinical diagnosis of breast and thyroid diseases due to its non-invasive, simple, inexpensive, and repeatable features.
  • BI-RADS Breast Imaging Reporting and Data System
  • TI-RADS thyroid Imaging-Reporting And Data System
  • a first aspect of the embodiments of the present application provides an ultrasonic imaging system, including a probe, a transmitting circuit, a receiving circuit, a processor and a display, wherein:
  • the transmitting circuit is used to excite the probe to transmit ultrasonic waves to the measured object;
  • the receiving circuit is used to control the probe to receive ultrasonic echoes returned from the measured object to obtain ultrasonic echo signals;
  • the processor is configured to process the ultrasound echo signal to obtain an ultrasound image
  • the processor is further configured to: acquire an ultrasound image of a target area of the measured object, where the target area includes a thyroid area or a breast area;
  • the display is controlled to display characters corresponding to at least two preset lesion features in the preset graphics, and the characters corresponding to the lesion feature matching the target lesion feature among the at least two preset lesion features are marked with the first character.
  • the preset graphic includes at least two areas, and one of the areas is used to display a character corresponding to the preset lesion feature;
  • a second aspect of the embodiments of the present application provides an ultrasonic imaging system, including a probe, a transmitting circuit, a receiving circuit, a processor, and a display, wherein:
  • the transmitting circuit is used to excite the probe to transmit ultrasonic waves to the measured object;
  • the receiving circuit is used to control the probe to receive ultrasonic echoes returned from the measured object to obtain ultrasonic echo signals;
  • the processor is configured to process the ultrasound echo signal to obtain an ultrasound image
  • the processor is further configured to: acquire an ultrasound image of a target area of the measured object, where the target area includes a thyroid area or a breast area;
  • Controlling the display to display the characters corresponding to the target lesion features of the lesions in a preset graphic, and to differentiate and display the characters corresponding to the lesion features representing a specific lesion state in the target lesion features of the lesion;
  • the target lesion feature includes at least one of BI-RADS lesion features, and when the target region is a thyroid region, the target lesion feature includes TI-RADS lesion features. at least one.
  • the transmitting circuit is used to excite the probe to transmit ultrasonic waves to the measured object;
  • the receiving circuit is used to control the probe to receive ultrasonic echoes returned from the measured object to obtain ultrasonic echo signals;
  • the processor is configured to process the ultrasound echo signal to obtain an ultrasound image
  • the processor is further configured to: acquire an ultrasound image of a target area of the measured object, where the target area includes a thyroid area or a breast area;
  • controlling the display to display, in a preset graphic, an identifier corresponding to the target lesion feature of the lesion;
  • the target lesion features include BI-RADS lesion features
  • the target lesion features include TI-RADS lesion features
  • a fourth aspect of the embodiments of the present application provides an ultrasonic imaging system, including a probe, a transmitting circuit, a receiving circuit, a processor, and a display, wherein:
  • the receiving circuit is used to control the probe to receive ultrasonic echoes returned from the measured object to obtain ultrasonic echo signals;
  • the processor is configured to process the ultrasound echo signal to obtain an ultrasound image
  • the processor is also used for: acquiring an ultrasound image of the target area of the measured object;
  • a fifth aspect of the embodiments of the present application provides an ultrasonic imaging system, including a probe, a transmitting circuit, a receiving circuit, a processor, and a display, wherein:
  • the transmitting circuit is used to excite the probe to transmit ultrasonic waves to the measured object;
  • the receiving circuit is used to control the probe to receive ultrasonic echoes returned from the measured object to obtain ultrasonic echo signals;
  • the processor is configured to process the ultrasound echo signal to obtain an ultrasound image
  • the processor is also used for: acquiring an ultrasound image of the target area of the measured object;
  • the display is controlled to display the characters corresponding to the target lesion features of the lesions in a preset graphic, and differentiatedly display the characters corresponding to the lesion features representing a specific lesion state among the target lesion features of the lesions.
  • a sixth aspect of the embodiments of the present application provides an ultrasonic imaging system, including a probe, a transmitting circuit, a receiving circuit, a processor, and a display, wherein:
  • the transmitting circuit is used to excite the probe to transmit ultrasonic waves to the measured object;
  • the receiving circuit is used to control the probe to receive ultrasonic echoes returned from the measured object to obtain ultrasonic echo signals;
  • the processor is configured to process the ultrasound echo signal to obtain an ultrasound image
  • the processor is also used for: acquiring an ultrasound image of the target area of the measured object;
  • the display is controlled to display, in a preset graphic, an identifier corresponding to the target lesion feature of the lesion.
  • Characters corresponding to at least two preset lesion features are displayed in a preset graphic, and characters corresponding to the lesion feature matching the target lesion feature among the at least two preset lesion features are displayed in a first manner in a differentiated manner ; wherein, the preset graphic includes at least two areas, one of which is used to display a character corresponding to the preset lesion feature.
  • An eighth aspect of the embodiments of the present application provides an ultrasonic image analysis method, the method comprising:
  • Characters corresponding to the target lesion features of the lesions are displayed in the preset graph, and characters corresponding to the lesion features representing a specific lesion state in the target lesion features of the lesions are displayed in a differentiated manner.
  • a ninth aspect of the embodiments of the present application provides an ultrasonic image analysis method, the method comprising:
  • Characters corresponding to the target lesion features of the lesions are displayed in the preset graphics.
  • the ultrasound imaging system and the ultrasound image analysis method of the embodiments of the present application can display the identified features of the target lesion in a graphical manner, thereby intuitively presenting the analysis result of the ultrasound image and improving the analysis efficiency of the ultrasound image.
  • FIG. 1 shows a schematic block diagram of an ultrasound imaging system according to an embodiment of the present invention
  • FIG. 2 is a table showing characters corresponding to all TI-RADS lesion features according to an embodiment of the present application
  • FIG. 4 is a pie chart showing characters corresponding to all TI-RADS lesion features according to an embodiment of the present application.
  • FIG. 7 is a pie chart showing characters corresponding to BI-RADS lesion features representing a specific lesion state according to an embodiment of the present application.
  • FIG. 8 is a ring diagram showing characters corresponding to TI-RADS lesion characteristics representing different lesion states by sub-blocks according to an embodiment of the present application
  • FIG. 10 is a schematic diagram of a display interface for displaying characters corresponding to a target lesion feature in a TI-RADS lesion feature according to an embodiment of the present application;
  • FIG. 11 is a schematic diagram of a display interface for displaying characters corresponding to a target lesion feature in a BI-RADS lesion feature according to an embodiment of the present application;
  • FIG. 12 shows a schematic flowchart of an ultrasonic image analysis method according to another embodiment of the present invention.
  • FIG. 13 shows a schematic flowchart of an ultrasound image analysis method according to yet another embodiment of the present invention.
  • FIG. 1 shows a schematic structural block diagram of an ultrasound imaging system 100 according to an embodiment of the present application.
  • the ultrasound imaging system 100 includes a probe 110 , a transmit circuit 112 , a receive circuit 114 , a processor 116 and a display 118 . Further, the ultrasound imaging system may further include a transmit/receive selection switch 120 and a beam forming circuit 122 , and the transmit circuit 112 and the reception circuit 114 may be connected to the probe 110 through the transmit/receive selection switch 120 .
  • the probe 110 includes a plurality of transducer array elements.
  • the plurality of transducer array elements can be arranged in a row to form a linear array, or arranged in a two-dimensional matrix to form an area array.
  • the plurality of transducer array elements can also form a convex array.
  • the transducer array element is used to transmit ultrasonic waves according to the excitation electrical signal, or convert the received ultrasonic waves into electrical signals, so each transducer array element can be used to realize the mutual conversion of electrical pulse signals and ultrasonic waves, so as to realize the transmission to the measured object.
  • the tissue in the target area transmits ultrasonic waves, and can also be used to receive ultrasonic echoes reflected by the tissue.
  • transducer array elements are used to transmit ultrasonic waves and which transducer array elements are used to receive ultrasonic waves can be controlled through the transmitting sequence and receiving sequence, or the transducer array elements can be controlled to divide time slots for transmitting ultrasonic waves Or receive echoes of ultrasonic waves.
  • the transducer elements participating in ultrasonic emission can be excited by electrical signals at the same time, so as to emit ultrasonic waves at the same time; Ultrasound at certain time intervals.
  • the transmit circuit 112 transmits the delayed focused transmit pulse to the probe 110 through the transmit/receive selection switch 120 .
  • the probe 110 is excited by the transmission pulse to transmit an ultrasonic beam to the tissue in the target area of the object to be measured, and after a certain delay, receives the ultrasonic echo with tissue information reflected from the tissue in the target area, and transmits the ultrasonic echo. Converted back to electrical signals.
  • the receiving circuit 114 receives the electrical signals converted and generated by the probe 110, obtains ultrasonic echo signals, and sends these ultrasonic echo signals to the beam forming circuit 122, and the beam forming circuit 122 performs focus delay, weighting and channel calculation on the ultrasonic echo data.
  • the processor 116 performs signal detection, signal enhancement, data conversion, logarithmic compression, etc. on the ultrasonic echo signal to form an ultrasonic image.
  • the ultrasound images obtained by the processor 116 may be displayed on the display 118 or stored in the memory 124 .
  • the processor 116 is also used to obtain the ultrasonic image of the target area of the measured object in other ways.
  • the processor 116 may also control to receive ultrasound images of the target area transmitted from other ultrasound systems or networks.
  • the target area is the body area for ultrasound imaging. For example, in real-time scanning, the target area refers to the body area scanned by the doctor through the probe. In one embodiment, the target area of the subject includes a thyroid area or a breast area.
  • the processor 116 is further configured to detect lesions in the ultrasound image and identify target lesion characteristics of the lesions.
  • the target lesion characteristics of the lesion include the BI-RADS lesion characteristics, that is, the lesion characteristics summarized for breast lesions in the BI-RADS evaluation criteria;
  • the target lesion characteristics of the lesion include TI-RADS lesion characteristics, that is, the lesion characteristics summarized for thyroid lesions in the TI-RADS assessment criteria.
  • This application does not limit the versions of the BI-RADS evaluation standards and TI-RADS evaluation standards, no matter which country or organization formulates the BI-RADS evaluation standards and TI-RADS evaluation standards, no matter the existing BI-RADS evaluation standards Both the criteria and the TI-RADS assessment criteria or future updated BI-RADS assessment criteria and TI-RADS assessment criteria should be included within the scope of this application.
  • the preset lesion features include multiple categories, wherein the preset lesion features of the same category are a set of preset lesion features representing the same clinical index of the lesion, and the clinical index of the lesion includes, for example, the shape, edge, and direction of the lesion. Wait.
  • the preset lesion features of the same category include a category of lesion features used to characterize the edge of the lesion, a category of lesion features used to characterize the direction of the lesion, and a category of lesion features used to characterize the direction of the lesion in the BI-RADS lesion features.
  • a type of lesion feature characterizing lesion shape a type of lesion signature characterizing lesion blood flow, a type of lesion signature characterizing lesion calcification, a type of lesion signature characterizing lesion posterior echo, and a type of lesion signature characterizing lesion interior echo a type of lesion characteristic.
  • the lesion features that characterize the shape of the lesion include irregular, round and oval; the lesion features that characterize the direction of the lesion include parallel and non-parallel; the lesion features that characterize the edge of the lesion include burrs, differential lobes, angulation, blurring and clarity; Lesion features that characterize echoes within the lesion include anechoic, hyperechoic, cystic-solid echoes, hypoechoic, isoechoic, and inhomogeneous echoes; lesion features that characterize echoes behind the lesion include no change, enhancement, shadowing, and mixed changes; The focal features of calcification include extratumor calcification, intratumor calcification, and intraductal calcification.
  • the preset lesion features of the same category include a type of lesion feature used to characterize the echo of the lesion, a type of lesion feature used to characterize the shape of the lesion, and a type of lesion feature used to characterize the edge of the lesion among the TI-RADS lesion features.
  • the lesion features that characterize the composition of the lesion include solid, cystic, mixed cystic and solid, and spongy;
  • the lesion features that characterize the lesion echo include extremely hypoechoic, hypoechoic, isoechoic or hyperechoic, and anechoic;
  • lesions that characterize the shape of the lesion Features include width greater than height and height greater than width;
  • lesion features characterizing lesion margins include smooth, irregular, extrathyroidal invasion, and indeterminate;
  • lesion features characterizing focal hyperechoic lesions include peripheral calcifications, microcalcifications, no calcifications, and coarse lesions calcification.
  • the target lesion feature is the lesion feature obtained by identifying the lesion, that is, the lesion actually possessed by the lesion feature.
  • the processor 116 respectively identifies the lesion feature that the lesion actually has in the plurality of preset lesion features of the category, that is, the lesion is in the category under the target lesion characteristics.
  • the preset lesion features include three lesion features of irregular shape, circle and ellipse.
  • the feature is the shape feature that the breast lesion of the target object actually has, such as an oval shape.
  • the preset lesion characteristics may include solid, cystic, cystic-solid mixed, and spongy.
  • the target lesion feature is the component feature actually possessed by the thyroid lesion of the target object, such as solidity.
  • the processor 116 may first detect the lesion in the ultrasound image based on a relevant machine recognition algorithm. For example, the processor 116 may detect the lesion in the ultrasound image based on a deep learning neural network model, a machine learning model or traditional image processing methods, etc. where, for example, the specific boundaries of the lesion are segmented from the ultrasound image.
  • the machine learning model can be trained based on the collected ultrasound images with the lesion labeling results in advance, and then the trained machine learning model can be used to detect the grayscale of the pixels in the ultrasound images.
  • the degree value or texture value is used for binary classification to determine whether each pixel belongs to the lesion area, so as to realize the automatic detection of the lesion.
  • the processor 116 can extract image features such as gradient and texture of the ultrasound image, and determine the region where the lesion is located in the ultrasound image based on the extracted image features.
  • the user can manually mark the lesion area in the ultrasound image, for example, display the ultrasound image on the display 118, and perform manual marking operations according to the user. Determine where the lesions are located.
  • the location of the lesion can also be determined by semi-automatic detection. For example, the location of the lesion on the ultrasound image is automatically detected based on a machine recognition algorithm, and then further modified or corrected by the user to obtain a more precise location.
  • the processor 116 may also detect lesions in the ultrasound image using any other suitable method.
  • the processor 116 identifies target lesion characteristics of the detected lesions.
  • the processor 116 may identify the target lesion characteristics of the lesion based on a trained deep learning neural network. For example, when the target area is the thyroid area, a classification model can be trained for each category of TI-RADS lesion features, and the ultrasound images of the lesion area are input into each classification model to obtain the target lesion features of the corresponding category; or , and a multi-task neural network can also be used to input the ultrasound images of the lesions into the multi-task neural network, and output the target lesion features of multiple categories at the same time.
  • the processor 116 may use a traditional image feature extraction algorithm combined with a machine learning method to identify the target lesion feature of the lesion.
  • the target area is the thyroid area
  • feature value extraction is performed for each TI-RADS category, and the extracted feature values are compared with a preset threshold to determine the target lesion characteristics of the lesion.
  • the processor 116 may also use any other suitable algorithm to extract the target lesion feature of the lesion.
  • the processor 116 may not identify the target lesion feature according to the lesion category, but identify each preset lesion feature separately. For example, the processor 116 may separately train a second feature for each preset lesion feature. The classifier for classification is used to determine whether the lesion has corresponding lesion characteristics.
  • the processor 116 controls the display 118 to display the target lesion feature in a graphical manner. Specifically, the processor 116 controls the display 118 to display characters corresponding to at least two preset lesion features in the preset graphics, and displays the characters corresponding to the lesion feature matching the target lesion feature among the at least two preset lesion features Differentiated display is performed in a first manner; wherein, the preset graphic includes at least two regions, and one region is used to display a character corresponding to a preset lesion feature.
  • the user can intuitively know the target lesion feature of the lesion by distinguishing and displaying the characters corresponding to the lesion feature matching the target lesion feature in the first manner.
  • the differentiated display in the first manner includes, but is not limited to, the following: highlighting or flashing a character corresponding to a lesion feature matching the target lesion feature or an area where the character is displayed; adding a symbol to the character Display, for example, displaying preset symbols around the characters; differentiated shading color display for the area where the characters corresponding to the lesion features matching the target lesion features are displayed, or the characters themselves are differentiated font color display.
  • the first manner of differentiated display may also include other differentiated display manners capable of distinguishing the characters corresponding to the target lesion features from the characters corresponding to other preset lesion features, for example, it may also include a pair of characters corresponding to other preset lesion features. characters for shadow masking, etc.
  • the TI-RADS lesion features displayed in the preset graph include all the lesion features in the TI-RADS lesion features.
  • the BI-RADS lesion features displayed in the preset graph may also include all the lesion features in the BI-RADS lesion features.
  • the embodiments of the present application do not limit the specific characters representing the preset lesion characteristics, as long as the characters can represent the corresponding preset lesion characteristics.
  • the characters displayed in the preset graph can be "anechoic” or "echo is anechoic”; when the calcification type of the thyroid lesion is microcalcification, the preset graphic The characters displayed in the graph can be "microcalcification” or "dotted hyperechoic”.
  • the target lesion characteristics of the lesions may be displayed in a table format, which is concise, clear, and easy to view.
  • the preset graphic is a table
  • the region in the preset graphic displaying the characters corresponding to each preset lesion feature is a cell in the table.
  • FIG. 2 shows the target lesion characteristics of a thyroid lesion displayed in a tabular manner.
  • one TI-RADS lesion feature is displayed in each cell of the table, and all 18 TI-RADS lesion features in the TI-RADS assessment criteria are displayed throughout the table.
  • the characteristics of the target lesions identified by the processor 116 for the lesions in the ultrasound image are hypoechoic, mixed with cysts and solids, no calcification, wider than high, and extrathyroidal invasion.
  • the shading of the cell where the characters corresponding to the above five target lesion features are located is displayed in a differentiated manner. According to the table shown in Figure 2, the user can know not only the characteristics of all TI-RADS lesions, but also the characteristics of TI-RADS lesions actually possessed by the thyroid lesions of the tested object.
  • Figure 3 shows the target lesion characteristics of breast lesions displayed in a tabular fashion, where one BI-RADS lesion signature is displayed in each cell of the table and the BI-RADS assessment is displayed throughout the table All 26 BI-RADS lesion characteristics in the criteria.
  • the processor 116 has identified six target lesion features, namely irregular shape, parallelism, differential lobes, hypoechoic, acoustic shadow and no blood flow. Therefore, in the table of FIG. 3 , the above characteristics identified by the processor 116 are The shading of the cell where the characters corresponding to the six target lesion features are displayed is differentiated.
  • the target lesion characteristics of the lesions may be displayed in the form of a pie chart.
  • the preset graphic for displaying characters corresponding to the preset lesion features is a pie chart, and the area for displaying the characters corresponding to each preset lesion feature in the pie chart is a sector divided in the pie chart .
  • At least two of the areas in the preset graphic form a block, and each area in the same block is used to display characters corresponding to preset lesion features of the same category, so that the user can locate the target lesion according to the characteristics of the target lesion.
  • the block to know the category to which the target lesion feature belongs.
  • BI-RADS lesion features are divided into seven categories: shape, direction, edge, internal echo, posterior echo, calcification, and blood flow.
  • Each category includes at least two BI-RADS lesion features.
  • the preset graphics can be divided into 7 blocks, and each area of each block displays the characters corresponding to the BI-RADS lesion features belonging to the same category.
  • the features of TI-RADS lesions are divided into five categories: composition, echo, shape, edge, and focal hyperechoic.
  • the preset graph can be divided into 5 areas. Blocks, each area of each block displays the characters corresponding to the TI-RADS lesion features belonging to the same category.
  • the preset graph is a table
  • at least two cells in the same row or column of the table form a block, that is, the same row or column of the table displays the BI-RADS lesion characteristics of the same category or the TI of the same category - RADS lesion characteristics.
  • characters corresponding to preset lesion features belonging to the same category can be displayed in adjacent cells in different rows or columns of the table in a compact manner to save layout area.
  • FIG. 4 shows the target lesion characteristics of a thyroid lesion displayed in a pie chart.
  • a TI-RADS lesion feature is displayed in each sector of the pie chart, the whole pie chart is divided into 5 blocks, and at least two sectors in each block display the corresponding TI-RADS lesion features of the same category Characters, the entire pie chart shows five blocks corresponding to five categories of composition, echo, shape, edge, and focal hyperechoic, and 18 sectors corresponding to all 18 TI-RADS lesion features of the five categories .
  • the four sectors in the upper right corner of the pie chart are displayed with characters: extremely low, low, equal or high, none.
  • the characters displayed in these four sectors all correspond to the preset lesion characteristics of the echo category, so these four Sectors can form a block that characterizes the type of echo.
  • the five categories of target lesion features identified by the processor 116 are hypoechoic, cystic, no calcification, wider than high, and extrathyroidal invasion.
  • the fan-shaped shading where the character corresponding to the target lesion feature is located is displayed in a differentiated manner.
  • Figure 5 shows the target lesion characteristics of breast lesions displayed in a pie chart, wherein one BI-RADS lesion characteristic is displayed in each sector of the pie chart, and the entire pie chart is divided into 7 regions Blocks, at least two sectors in each block show characters corresponding to the same category of BI-RADS lesion features, and the entire pie chart shows the seven categories of shape, orientation, edge, internal echo, posterior echo, calcification, and blood flow. , and the 26 sectors corresponding to all 26 BI-RADS lesion features in seven categories. Exemplarily, the two fan-shaped areas in the upper right corner of the pie chart display characters: parallel and non-parallel.
  • the characters displayed in the two fan-shaped areas are the preset lesion characteristics of the corresponding direction category, so the two fan-shaped areas can form a A block representing the type of direction.
  • the features of the target lesions identified by the processor 116 are irregular shape, parallelism, differential lobes, hypoechoic, acoustic shadow, and internal blood flow. Therefore, in the pie chart of FIG. 5, the processor 116 identifies The fan-shaped shading where the characters corresponding to the above seven target lesion features are located is displayed in a differentiated manner.
  • the processor 116 may control the display 118 to display each block differently to facilitate distinguishing the blocks.
  • the processor 116 may control the display 118 to display each area of the same block as the same color or pattern, or the processor 116 may control the display 118 to display the characters corresponding to the preset lesion features in each area of the same block as same color.
  • the processor 116 can also control the display 118 to display different blocks in a differentiated manner by other means, such as displaying a bold dividing line or a dividing line of different colors among the blocks.
  • characters corresponding to the category to which the preset lesion feature in the block belongs may also be displayed near each block to more clearly mark the lesion category corresponding to the block.
  • the pre-set lesion characteristics that characterize the component namely solid, cystic, mixed cyst-solid, and spongy, are displayed in each sector of the block in the upper left corner; therefore, the block is displayed near the block.
  • the character “component” to indicate that the preset lesion features in the block represent the components of the lesion.
  • the characters “echo”, “shape”, “edge” and “focal hyperechoic” are displayed near the other four blocks of the pie chart in Fig. 4, respectively, to indicate the preset lesions displayed in each block The category to which the feature belongs.
  • the processor 116 is further configured to: when the target area is the breast area, control the display 118 to distinguish in a second manner
  • the characters corresponding to the lesion features representing the specific lesion state in the BI-RADS lesion features are displayed in a second manner; when the target area is the thyroid region, the control display 118 differentiates and displays the lesion features representing the specific lesion status among the TI-RADS lesion features in a second manner.
  • the differentiated display in the second manner may be all the characters corresponding to the lesion features representing the specific lesion state in the preset lesion features, or may be the characters corresponding to the lesion features representing the specific lesion state in the target lesion features.
  • the differentiated display in the second manner includes, but is not limited to, at least one of the following: highlight display, blinking display, additional symbol display, differentiated shading color display or differentiated font color display.
  • highlight display blinking display
  • additional symbol display differentiated shading color display or differentiated font color display.
  • differentiated display in the second manner may be blinking display.
  • the characters corresponding to the above 8 TI-RADS lesion features are shown in the pie chart; in the example of Figure 6, the regions corresponding to the two lesion features of hypoechoic and extrathyroidal invasion are compared with other regions A differentiated display is performed, indicating that hypoechoic and extrathyroidal invasion are the characteristics of the target lesion, that is, the processor 116 recognizes that the lesion actually has these two characteristics of the lesion.
  • FIGS. 6 and 7 show the characters corresponding to the lesion features representing the specific lesion state in the form of a pie chart
  • other preset graphics may also be used to display the characters corresponding to the above-mentioned lesion features representing the specific lesion state. , including but not limited to tables.
  • the characters corresponding to the lesion features representing the specific lesion state are displayed in the preset graph
  • the characters corresponding to the preset lesion features belonging to the same category may also be displayed in the same block for easy viewing.
  • FIG. 6 Hypoechoic and very low echoes belonging to the echo category are shown in the same block, and glitches, differential lobes, angulation and edge blur, which belong to the edge category in Figure 7, are shown in the same block.
  • At least two areas in the preset graphic form a block, and each area in the same block is used to display characters corresponding to preset lesion features representing the state of the same lesion, so that the user can determine the target lesion characteristics according to the target lesion characteristics.
  • the division methods of the above two blocks can be combined with each other, for example, the same row of the table displays the preset lesion features of the same category, and the same column displays the preset lesion features representing the same lesion state.
  • the lesion status can indicate the benign and malignant lesions.
  • the TI-RADS assessment standard scores 18 features of thyroid lesions on a scale of 0 to 3, with the higher the score, the more likely the feature of the lesion is present in a malignant lesion, and thus can be included in the same block of the preset graph. TI-RADS lesion characteristics with the same score are shown.
  • the preset lesion features that characterize the same lesion state include TI-RADS lesion features: 1) No calcification, no echo, spongy, wider than high, uncertain, smooth, cystic
  • the pre-set lesion features that characterize the state of the first lesion namely, the TI-RADS lesion feature with a score of 0; 2) the pre-determined lesions that characterize the state of the second lesion composed of coarse calcification, hyperechoic or isoechoic, and mixed cysts and solids Lesion features, that is, TI-RADS lesion features with a score of 1; 3) Pre-set lesion features that characterize the state of the third lesion, consisting of hypoechoic, lobulated or irregular, peripheral calcification, and solidity, that is, a score of 2 4)
  • the pre-set lesion features that characterize the fourth lesion state which is composed of height greater than width, extrathyroidal invasion, punctate hyperechoic, and extremely
  • the preset graphic may be a ring diagram, the ring diagram includes at least one ring, and one ring includes at least two fan-shaped rings; characters corresponding to each preset lesion feature are displayed
  • the area of is the sector ring in the annular diagram, and the block formed by at least two sector rings is the annular diagram in the annular diagram.
  • the characters corresponding to the features of TI-RADS lesions with a score of 0 to 3 are displayed in turn from the fan diagram in the middle to the outer ring, and the actual TI-RADS lesion features of the lesions are displayed.
  • the sector or sector ring where the corresponding character is located is differentiated and displayed in the first manner.
  • the fan-shaped graph in the middle of the ring graph of FIG. 8 and each ring are also marked with the score of the preset lesion feature displayed by the ring, for the user's reference.
  • BI-RADS lesions can be classified according to their benign and malignant characteristics based on clinical experience, and displayed in the ring diagram.
  • the processor 116 may be implemented as software, hardware, firmware, or any combination thereof, and may use single or multiple application specific integrated circuits (ASICs), single or multiple general-purpose integrated circuits, single or multiple microprocessors, single or multiple programmable logic devices, or any combination of the foregoing circuits and/or devices, or other suitable circuits or devices. Also, the processor 116 may control other components in the ultrasound imaging system 100 to perform corresponding steps of the methods in the various embodiments in this specification.
  • ASICs application specific integrated circuits
  • the processor 116 may control other components in the ultrasound imaging system 100 to perform corresponding steps of the methods in the various embodiments in this specification.
  • the display 118 is connected to the processor 116, and the display 118 may be a touch display screen, a liquid crystal display screen, etc.; or, the display 118 may be an independent display such as a liquid crystal display, a TV set, etc. independent of the ultrasound imaging system 100; or, the display 118 may It is the display screen of electronic devices such as smartphones, tablets, etc.
  • the number of displays 118 may be one or more.
  • the display 118 may include a main screen and a touch screen, where the main screen is mainly used for displaying ultrasound images, and the touch screen is mainly used for human-computer interaction.
  • Display 118 may display ultrasound images obtained by processor 116 .
  • the display 118 can also provide the user with a graphical interface for human-computer interaction while displaying the ultrasound image, set one or more controlled objects on the graphical interface, and provide the user with the human-computer interaction device to input operating instructions to control these objects.
  • the controlled object so as to perform the corresponding control operation.
  • an icon is displayed on the graphical interface, and the icon can be operated by using a human-computer interaction device to perform a specific function, such as drawing a region of interest frame on the ultrasound image.
  • the ultrasound imaging system 100 may also include other human-computer interaction devices other than the display 118, which are connected to the processor 116.
  • the processor 116 may be connected to the human-computer interaction device through an external input/output port.
  • the output port can be a wireless communication module, a wired communication module, or a combination of the two.
  • External input/output ports may also be implemented based on USB, bus protocols such as CAN, and/or wired network protocols, and the like.
  • the human-computer interaction device may include an input device for detecting the user's input information, for example, the input information may be a control instruction for the ultrasonic transmission/reception sequence, or a point, line or frame drawn on the ultrasonic image. Manipulate input instructions, or may also include other instruction types.
  • the input device may include one or a combination of a keyboard, a mouse, a scroll wheel, a trackball, a mobile input device (eg, a mobile device with a touch display screen, a cell phone, etc.), a multi-function knob, and the like.
  • the human-computer interaction apparatus may also include an output device such as a printer.
  • the components included in the ultrasound imaging system 100 shown in FIG. 1 are only schematic, and it may include more or less components, which is not limited in the present application.
  • the embodiment of the present application further provides an ultrasonic imaging system, and with continued reference to FIG. 1 , the ultrasonic imaging system includes a probe, a transmitting circuit, a receiving circuit, a processor, and a display.
  • the ultrasonic imaging system includes a probe, a transmitting circuit, a receiving circuit, a processor, and a display.
  • the ultrasonic imaging system 100 For the relevant description, reference may be made to the ultrasonic imaging system 100 above. For the relevant description, the following only describes the main functions of the ultrasound imaging system, and omits the details that have been described above.
  • the transmitting circuit is used to excite the probe to transmit ultrasonic waves to the measured object;
  • the receiving circuit is used to control the probe to receive ultrasonic echoes returned from the measured object to obtain ultrasonic echo signals;
  • the processor is used to process the ultrasonic waves echo signals to obtain an ultrasound image;
  • the processor is further configured to: obtain an ultrasound image of the target area of the measured object; detect a lesion in the ultrasound image, and identify the target lesion feature of the lesion; control the display to display Characters corresponding to at least two preset lesion features are displayed in the preset graphics, and characters corresponding to the lesion feature matching the target lesion feature among the at least two preset lesion features are displayed in a differentiated manner; wherein, the The preset graphic includes at least two areas, and one of the areas is used to display a character corresponding to the preset lesion feature.
  • the ultrasonic imaging system of this embodiment is generally similar to the ultrasonic imaging system 100 described above, the main difference between the two is that the target area of the measured object is not limited to the breast area and the thyroid area, but also includes the liver area or other target areas.
  • different target areas correspond to different evaluation criteria
  • the preset lesion features and target lesion features are the lesion features under the corresponding evaluation criteria.
  • the processor accordingly analyzes the ultrasound image using the evaluation criteria for the liver.
  • FIG. 9 is a schematic flowchart of an ultrasound image analysis method 900 according to an embodiment of the present application.
  • the ultrasonic image analysis method 900 includes the following steps:
  • Step S910 acquiring an ultrasound image of the target area of the measured object
  • Step S920 detecting the lesion in the ultrasound image, and identifying the target lesion feature of the lesion
  • Step S930 displaying characters corresponding to at least two preset lesion features in a preset graphic, and displaying the characters corresponding to the lesion feature matching the target lesion feature among the at least two preset lesion features in a first manner Differentiated display; wherein, the preset graphic includes at least two regions, and one of the regions is used to display a character corresponding to the preset lesion feature.
  • the target area includes a thyroid area or a breast area
  • the preset lesion characteristics include BI-RADS lesion characteristics
  • the Prespecified lesion characteristics include TI-RADS lesion characteristics
  • the ultrasound imaging system and the ultrasound image analysis method of the embodiments of the present application display the preset lesion features in the preset graph, and differentiate and display the target lesion features identified therein, so as to intuitively present the preset lesion features and the actual lesion characteristics of the lesion. It can improve the analysis efficiency of ultrasound images.
  • the transmitting circuit is used to excite the probe to transmit ultrasonic waves to the measured object;
  • the receiving circuit is used to control the probe to receive ultrasonic echoes returned from the measured object to obtain ultrasonic echo signals;
  • the processing The processor is used to process the ultrasonic echo signal to obtain an ultrasonic image;
  • the processor is further used to: acquire an ultrasonic image of a target area of the measured object, the target area includes a thyroid area or a breast area; detect the ultrasonic image in the ultrasonic image and identify the target lesion feature of the lesion; determine the lesion feature representing a specific lesion state among the lesion features of the lesion; control the display to display the character corresponding to the target lesion feature of the lesion in a preset graphic, and Distinguishly display the character corresponding to the lesion feature representing the specific lesion state in the target lesion feature of the lesion; when the target area is a breast region, the target lesion feature includes at least one of the BI-RADS lesion features, when When
  • the difference between the ultrasonic imaging system of this embodiment and the ultrasonic imaging system 100 described above is mainly that: in the ultrasonic imaging system of this embodiment, the characters corresponding to the target lesion characteristics of the lesions are displayed in the preset graphics, instead of Shows features of the lesion that the lesion does not have.
  • the display interface shown in FIG. 10 shows the ultrasound image 1010 of the thyroid region and the TI-RADS lesion characteristics of the thyroid lesion identified based on the ultrasound image 1010
  • the display interface shown in FIG. 11 The ultrasound image 1020 of the breast region and the BI-RADS lesion features of the breast region identified based on the ultrasound image 1010 are shown in FIG.
  • the preset graphics are boxes, and the characters of each target lesion feature are displayed in a box.
  • the target lesion features are displayed according to the category to which they belong, that is, the target lesions under the category are respectively identified for the BI-RADS lesion features or TI-RADS lesion features of each category.
  • the feature is displayed in the corresponding box, and the category to which the current target lesion feature belongs is displayed above the box.
  • the TI-RADS lesion features displayed in the box represent the actual target lesion features of the lesion, including the height greater than the width representing the shape of the lesion, the cystic solidity representing the lesion component, and the echo representing the lesion.
  • the preset graphics for displaying the characters corresponding to the target features of the lesion are not limited to the forms shown in FIG. 10 and FIG. 11 , for example, the preset graphics may also be a table, a pie chart, a ring chart or other suitable forms.
  • a target lesion feature can be displayed in each cell of the table, and the characters corresponding to the malignant signs in the table can be displayed in a differentiated manner, or the different lesion states can be displayed in a differentiated manner.
  • the characters corresponding to the target lesion feature of , or the area where the character is located are displayed in different colors; for example, the category to which the target lesion feature belongs may also be displayed in the table at the same time.
  • the ultrasonic imaging system of this embodiment is generally similar to the above-mentioned ultrasonic imaging system, and the difference between the two is that the target area of the measured object is not limited to the breast area and the thyroid area, but also includes the liver area or other target areas.
  • the target area of the measured object is not limited to the breast area and the thyroid area, but also includes the liver area or other target areas.
  • different target regions correspond to different evaluation criteria
  • the target lesion features are the lesion features under the corresponding evaluation criteria.
  • FIG. 12 is a schematic flowchart of an ultrasound image analysis method 1200 according to an embodiment of the present application.
  • the ultrasonic image analysis method 1200 includes the following steps:
  • Step S1210 acquiring an ultrasound image of the target area of the measured object
  • the ultrasound imaging system and the ultrasound image analysis method of the embodiments of the present application display characters corresponding to the features of the target lesions in a preset graph, and differentiate and display the features of the target lesions that represent the state of a specific lesion, thereby intuitively presenting the features of the target lesions and The user is prompted with the target lesion feature that represents the specific lesion state, thereby improving the analysis efficiency of the ultrasound image.
  • Embodiments of the present application further provide an ultrasonic imaging system, including a probe, a transmitting circuit, a receiving circuit, a processor, and a display, wherein: the transmitting circuit is used to excite the probe to transmit ultrasonic waves to the measured object; is used to control the probe to receive the ultrasonic echoes returned from the measured object to obtain ultrasonic echo signals; the processor is used for processing the ultrasonic echo signals to obtain ultrasonic images; the processor is further used for: obtaining the measured ultrasonic echoes Ultrasound image of the target area of the object; detecting the lesion in the ultrasound image, and identifying the target lesion feature of the lesion; controlling the display to display the identifier corresponding to the target lesion feature of the lesion in a preset graphic.
  • the transmitting circuit is used to excite the probe to transmit ultrasonic waves to the measured object; is used to control the probe to receive the ultrasonic echoes returned from the measured object to obtain ultrasonic echo signals
  • the processor is used for processing the ultra
  • the ultrasonic imaging system of this embodiment is generally similar to the ultrasonic imaging system described above, and the difference between the two is mainly that the target area of the measured object is not limited to the breast area and the thyroid area, but also includes other target areas.
  • the target area of the measured object is not limited to the breast area and the thyroid area, but also includes other target areas.
  • different target regions correspond to different evaluation criteria
  • the target lesion features are the lesion features under the corresponding evaluation criteria.
  • FIG. 13 is a schematic flowchart of an ultrasound image analysis method 1300 according to an embodiment of the present application.
  • the ultrasonic image analysis method 1300 includes the following steps:
  • step S1310 acquire the ultrasound image of the target area of the measured object
  • step S1320 detect the lesion in the ultrasound image, and identify the target lesion feature of the lesion
  • step S1330 the character corresponding to the target lesion feature of the lesion is displayed in the preset graphic.
  • the target area includes a thyroid area or a breast area
  • the target lesion features include BI-RADS lesion characteristics
  • the target lesion features Lesion characteristics include TI-RADS lesion characteristics
  • the ultrasound imaging system and the ultrasound image analysis method of the embodiments of the present application display the identifier corresponding to the feature of the target lesion in the preset graph, thereby visually presenting the feature of the target lesion and improving the analysis efficiency of the ultrasound image.
  • the disclosed apparatus and method may be implemented in other manners.
  • the device embodiments described above are only illustrative.
  • the division of the units is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components may be combined or May be integrated into another device, or some features may be omitted, or not implemented.
  • Various component embodiments of the present application may be implemented in hardware, or in software modules running on one or more processors, or in a combination thereof.
  • a microprocessor or a digital signal processor (DSP) may be used in practice to implement some or all functions of some modules according to the embodiments of the present application.
  • DSP digital signal processor
  • the present application can also be implemented as a program of apparatus (eg, computer programs and computer program products) for performing part or all of the methods described herein.
  • Such a program implementing the present application may be stored on a computer-readable medium, or may be in the form of one or more signals. Such signals may be downloaded from Internet sites, or provided on carrier signals, or in any other form.

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Abstract

一种超声成像系统和超声图像分析方法，该超声成像系统包括探头、发射电路、接收电路、处理器和显示器，其中处理器用于：获取被测对象目标区域的超声图像，目标区域包括甲状腺区域或乳腺区域；检测超声图像中的病灶，并识别病灶的目标病灶特征；控制显示器在预设图形中显示至少两个预设病灶特征对应的字符，并将其中与目标病灶特征相匹配的病灶特征对应的字符以第一方式区别化显示；其中，预设图形包括至少两个区域，一个区域用于显示一个预设病灶特征对应的字符；预设病灶特征包括BI-RADS病灶特征或TI-RADS病灶特征。本申请将识别到的目标病灶特征以图形化的方式进行显示，从而直观地呈现超声图像的分析结果，提高超声图像的分析效率。

Description

超声成像系统和超声图像分析方法 技术领域
本申请涉及超声成像技术领域，更具体地涉及一种超声成像系统和超声图像分析方法。
背景技术
乳腺癌是发生在乳腺腺上皮组织的恶性肿瘤，近年来乳腺癌的发病率和死亡率逐年持续上升，发病人群日趋年轻化，发病地域从以城市为主扩展至广大农村，目前乳腺癌已成为威胁女性身心健康的常见肿瘤。同样的，甲状腺疾病在人群中的发病率逐年升高，而超声影像检查因具有无创、操作简单、价格低廉、可重复操作等特点，已成为乳腺、甲状腺疾病临床诊断的首选方案。
美国放射协会于2013提出了最新版的乳腺BI-RADS(Breast Imaging Reporting and Data System，乳腺影像报告和数据系统)评估标准，对乳腺病灶的超声表现进行了总结。此外，美国放射协会于2017年提出的甲状腺TI-RADS(Thyroid Imaging-Reporting And Data System，甲状腺影像报告和数据系统)评估标准中对甲状腺病灶的超声表现进行了总结。作为国际权威的乳腺评估标准和甲状腺评估标准，BI-RADS评估标准和TI-RADS评估标准在国内外临床上被广泛认可与使用。然而，由于这两种评估标准中涉及的特征种类多，医生在对超声图像进行分析时需要一一确认病灶是否有该特征，使得诊断效率较低，对医生的记忆是个极大的挑战，并且也无法清晰直观地将评估结果呈现给用户。
发明内容
在发明内容部分中引入了一系列简化形式的概念，这将在具体实施方式部分中进一步详细说明。本发明的发明内容部分并不意味着要试图限定出所要求保护的技术方案的关键特征和必要技术特征，更不意味着试图确定所要求保护的技术方案的保护范围。
针对现有技术的不足，本申请实施例第一方面提供了一种超声成像系统， 包括探头、发射电路、接收电路、处理器和显示器，其中：
所述发射电路用于激励所述探头向被测对象发射超声波；
所述接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；
所述处理器用于处理所述超声回波信号以获得超声图像；
所述处理器还用于：获取被测对象目标区域的超声图像，所述目标区域包括甲状腺区域或乳腺区域；
检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
控制所述显示器在预设图形中显示至少两个预设病灶特征对应的字符，并将所述至少两个预设病灶特征中与所述目标病灶特征相匹配的病灶特征对应的字符以第一方式区别化显示；其中，所述预设图形包括至少两个区域，一个所述区域用于显示一个所述预设病灶特征对应的字符；
当所述目标区域为乳腺区域时，所述预设病灶特征包括BI-RADS病灶特征，当所述目标区域为甲状腺区域时，所述预设病灶特征包括TI-RADS病灶特征。
本申请实施例第二方面提供了一种超声成像系统，包括探头、发射电路、接收电路、处理器和显示器，其中：
所述发射电路用于激励所述探头向被测对象发射超声波；
所述接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；
所述处理器用于处理所述超声回波信号以获得超声图像；
所述处理器还用于：获取被测对象目标区域的超声图像，所述目标区域包括甲状腺区域或乳腺区域；
检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
确定所述病灶的病灶特征中表征特定病灶状态的病灶特征；
控制所述显示器在预设图形中显示所述病灶的目标病灶特征对应的字符，并区别化显示所述病灶的目标病灶特征中表征特定病灶状态的病灶特征对应 的字符；
当所述目标区域为乳腺区域时，所述目标病灶特征包括BI-RADS病灶特征中的至少一种，当所述目标区域为甲状腺区域时，所述目标病灶特征包括TI-RADS病灶特征中的至少一种。
本申请实施例第三方面提供了一种超声成像系统，包括探头、发射电路、接收电路、处理器和显示器，其中：
所述发射电路用于激励所述探头向被测对象发射超声波；
所述接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；
所述处理器用于处理所述超声回波信号以获得超声图像；
所述处理器还用于：获取被测对象目标区域的超声图像，所述目标区域包括甲状腺区域或乳腺区域；
检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
控制所述显示器在预设图形中显示所述病灶的目标病灶特征对应的标识；
当所述目标区域为乳腺区域时，所述目标病灶特征包括BI-RADS病灶特征，当所述目标区域为甲状腺区域时，所述目标病灶特征包括TI-RADS病灶特征。
本申请实施例第四方面提供了一种超声成像系统，包括探头、发射电路、接收电路、处理器和显示器，其中：
所述发射电路用于激励所述探头向被测对象发射超声波；
所述接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；
所述处理器用于处理所述超声回波信号以获得超声图像；
所述处理器还用于：获取被测对象目标区域的超声图像；
检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
控制所述显示器在预设图形中显示至少两个预设病灶特征对应的字符，并将所述至少两个预设病灶特征中与所述目标病灶特征相匹配的病灶特征对 应的字符区别化显示；其中，所述预设图形包括至少两个区域，一个所述区域用于显示一个所述预设病灶特征对应的字符。
本申请实施例第五方面提供了一种超声成像系统，包括探头、发射电路、接收电路、处理器和显示器，其中：
所述发射电路用于激励所述探头向被测对象发射超声波；
所述接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；
所述处理器用于处理所述超声回波信号以获得超声图像；
所述处理器还用于：获取被测对象目标区域的超声图像；
检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
确定所述病灶的病灶特征中表征特定病灶状态的病灶特征；
控制所述显示器在预设图形中显示所述病灶的目标病灶特征对应的字符，并区别化显示所述病灶的目标病灶特征中表征特定病灶状态的病灶特征对应的字符。
本申请实施例第六方面提供了一种超声成像系统，包括探头、发射电路、接收电路、处理器和显示器，其中：
所述发射电路用于激励所述探头向被测对象发射超声波；
所述接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；
所述处理器用于处理所述超声回波信号以获得超声图像；
所述处理器还用于：获取被测对象目标区域的超声图像；
检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
控制所述显示器在预设图形中显示所述病灶的目标病灶特征对应的标识。
本申请实施例第七方面提供了一种超声图像分析方法，所述方法包括：
获取被测对象目标区域的超声图像；
检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
在预设图形中显示至少两个预设病灶特征对应的字符，并将所述至少两个预设病灶特征中与所述目标病灶特征相匹配的病灶特征对应的字符以第一方式区别化显示；其中，所述预设图形包括至少两个区域，一个所述区域用于显示一个所述预设病灶特征对应的字符。
本申请实施例第八方面提供了一种超声图像分析方法，所述方法包括：
获取被测对象目标区域的超声图像；
检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
在预设图形中显示所述病灶的目标病灶特征对应的字符，并区别化显示所述病灶的目标病灶特征中表征特定病灶状态的病灶特征对应的字符。
本申请实施例第九方面提供了一种超声图像分析方法，所述方法包括：
获取被测对象目标区域的超声图像；
检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
在预设图形中显示所述病灶的目标病灶特征对应的字符。
本申请实施例的超声成像系统和超声图像分析方法能够将识别到的目标病灶特征以图形化的方式进行显示，从而直观地呈现超声图像的分析结果，提高超声图像的分析效率。
附图说明
为了更清楚地说明本发明实施例中的技术方案，下面将对实施例描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动性的前提下，还可以根据这些附图获得其他的附图。
在附图中：
图1示出根据本发明一实施例的超声成像系统的示意性框图；
图2为根据本申请一实施例的显示全部TI-RADS病灶特征对应字符的表格；
图3为根据本申请一实施例的显示全部BI-RADS病灶特征对应字符的表格；
图4为根据本申请一实施例的显示全部TI-RADS病灶特征对应字符的饼 图；
图5为根据本申请一实施例的显示全部BI-RADS病灶特征对应字符的饼图；
图6为根据本申请一实施例的显示表征特定病灶状态的TI-RADS病灶特征对应字符的饼图；
图7为根据本申请一实施例的显示表征特定病灶状态的BI-RADS病灶特征对应字符的饼图；
图8为根据本申请一实施例的分区块显示表示不同病灶状态的TI-RADS病灶特征对应字符的环形图；
图9示出根据本发明一实施例的超声图像分析方法的示意性流程图；
图10为根据本申请一实施例的显示TI-RADS病灶特征中的目标病灶特征对应的字符的显示界面的示意图；
图11为根据本申请一实施例的显示BI-RADS病灶特征中的目标病灶特征对应的字符的显示界面的示意图；
图12示出根据本发明另一实施例的超声图像分析方法的示意性流程图；
图13示出根据本发明又一实施例的超声图像分析方法的示意性流程图。
具体实施方式
为了使得本申请的目的、技术方案和优点更为明显，下面将参照附图详细描述根据本申请的示例实施例。显然，所描述的实施例仅仅是本申请的一部分实施例，而不是本申请的全部实施例，应理解，本申请不受这里描述的示例实施例的限制。基于本申请中描述的本申请实施例，本领域技术人员在没有付出创造性劳动的情况下所得到的所有其它实施例都应落入本申请的保护范围之内。
在下文的描述中，给出了大量具体的细节以便提供对本申请更为彻底的理解。然而，对于本领域技术人员而言显而易见的是，本申请可以无需一个或多个这些细节而得以实施。在其他的例子中，为了避免与本申请发生混淆，对于本领域公知的一些技术特征未进行描述。
应当理解的是，本申请能够以不同形式实施，而不应当解释为局限于这里提出的实施例。相反地，提供这些实施例将使公开彻底和完全，并且将本申请的范围完全地传递给本领域技术人员。
在此使用的术语的目的仅在于描述具体实施例并且不作为本申请的限制。在此使用时，单数形式的“一”、“一个”和“所述/该”也意图包括复数形式，除非上下文清楚指出另外的方式。还应明白术语“组成”和/或“包括”，当在该说明书中使用时，确定所述特征、整数、步骤、操作、元件和/或部件的存在，但不排除一个或更多其它的特征、整数、步骤、操作、元件、部件和/或组的存在或添加。在此使用时，术语“和/或”包括相关所列项目的任何及所有组合。
为了彻底理解本申请，将在下列的描述中提出详细的结构，以便阐释本申请提出的技术方案。本申请的可选实施例详细描述如下，然而除了这些详细描述外，本申请还可以具有其他实施方式。
下面，首先参考图1描述根据本申请一个实施例的超声成像系统，图1示出了根据本申请实施例的超声成像系统100的示意性结构框图。
如图1所示，超声成像系统100包括探头110、发射电路112、接收电路114、处理器116和显示器118。进一步地，超声成像系统还可以包括发射/接收选择开关120和波束合成电路122，发射电路112和接收电路114可以通过发射/接收选择开关120与探头110连接。
探头110包括多个换能器阵元，多个换能器阵元可以排列成一排构成线阵，或排布成二维矩阵构成面阵，多个换能器阵元也可以构成凸阵列。换能器阵元用于根据激励电信号发射超声波，或将接收的超声波转换为电信号，因此每个换能器阵元可用于实现电脉冲信号和超声波的相互转换，从而实现向被测对象的目标区域的组织发射超声波、也可用于接收经组织反射回的超声波回波。在进行超声检测时，可通过发射序列和接收序列控制哪些换能器阵元用于发射超声波，哪些换能器阵元用于接收超声波，或者控制换能器阵元分时隙用于发射超声波或接收超声波的回波。参与超声波发射的换能器阵元可以同时被电信号激励，从而同时发射超声波；或者，参与超声波束发射的换能器阵元也可以被具有一定时间间隔的若干电信号激励，从而持续发射具有一定时间间隔的超声波。
在超声成像过程中，发射电路112用于激励探头110向被测对象发射超声波；接收电路114用于控制探头110接收从被测对象返回的超声回波，以获得超声回波信号。
具体地，在超声成像过程中，发射电路112将经过延迟聚焦的发射脉冲通过发射/接收选择开关120发送到探头110。探头110受发射脉冲的激励而向被测对象的目标区域的组织发射超声波束，经一定延时后接收从目标区域的组织反射回来的带有组织信息的超声回波，并将此超声回波重新转换为电信号。接收电路114接收探头110转换生成的电信号，获得超声回波信号，并将这些超声回波信号送入波束合成电路122，波束合成电路122对超声回波数据进行聚焦延时、加权和通道求和等处理，然后送入处理器116。处理器116对超声回波信号进行信号检测、信号增强、数据转换、对数压缩等处理以形成超声图像。处理器116得到的超声图像可以在显示器118上显示，也可以存储于存储器124中。除了对超声回波信号进行处理以实时生成目标区域的超声图像以外，处理器116还用于通过其他方式获取被测对象目标区域的超声图像，例如，处理器116可以从存储器124中提取预先存储的目标区域的超声图像，处理器116也可以控制接收从其他超声系统或网络中传输而来的目标区域的超声图像。其中，目标区域为进行超声成像的身体区域，例如，在实时扫查中，目标区域指医生通过探头扫查的身体区域。在一个实施例中，被测对象的目标区域包括甲状腺区域或乳腺区域。
在生成或获取到目标区域的超声图像之后，处理器116还用于检测超声图像中的病灶，并识别所述病灶的目标病灶特征。其中，当目标区域为乳腺区域时，病灶的目标病灶特征包括BI-RADS病灶特征，即BI-RADS评估标准中针对乳腺病灶总结的病灶特征；当目标区域为甲状腺区域时，病灶的目标病灶特征包括TI-RADS病灶特征，即TI-RADS评估标准中针对甲状腺病灶总结的病灶特征。本申请对BI-RADS评估标准和TI-RADS评估标准的版本不做限制，无论是哪个国家或组织制定的BI-RADS评估标准和TI-RADS评估标准，无论是目前已有的BI-RADS评估标准和TI-RADS评估标准或未来更新的BI-RADS评估标准和TI-RADS评估标准都应包括在本申请的范围之内。
在一个实施例中，预设病灶特征包括多个类别，其中同一类别的预设病灶特征为表征病灶相同临床指标的预设病灶特征的集合，病灶的临床指标例如包括病灶的形状、边缘、方向等。示例性地，当目标区域为乳腺区域时，同一类别的预设病灶特征包括BI-RADS病灶特征中用于表征病灶边缘的一类病灶特征、用于表征病灶方向的一类病灶特征、用于表征病灶形状的一类 病灶特征、用于表征病灶血流的一类病灶特征、用于表征病灶钙化的一类病灶特征、用于表征病灶后方回声的一类病灶特征和用于表征病灶内部回声的一类病灶特征。
其中，表征病灶形状的病灶特征包括不规则形、圆形和椭圆形；表征病灶方向的病灶特征包括平行和不平行；表征病灶边缘的病灶特征包括毛刺、微分叶、成角、模糊和清晰；表征病灶内部回声的病灶特征包括无回声、高回声、囊实性回声、低回声、等回声和不均回声；表征病灶后方回声的病灶特征包括无改变、增强、声影和混合改变；表征病灶钙化的病灶特征包括肿块外钙化、肿块内钙化和导管内钙化。
当目标区域为甲状腺区域时，同一类别的预设病灶特征包括TI-RADS病灶特征中用于表征病灶回声的一类病灶特征、用于表征病灶形状的一类病灶特征、用于表征病灶边缘的一类病灶特征、用于表征病灶局部强回声的一类病灶特征和用于表征病灶成分的一类病灶特征。其中，表征病灶成分的病灶特征包括实性、囊性、囊实混合和海绵状；表征病灶回声的病灶特征包括极低回声、低回声、等回声或高回声和无回声；表征病灶形状的病灶特征包括宽大于高和高大于宽；表征病灶边缘的病灶特征包括光滑、不规则、甲状腺外侵犯和不确定；表征病灶局灶性强回声的病灶特征包括周边钙化、微钙化、无钙化和粗钙化。
在本申请实施例中，当预设病灶特征为TI-RADS或BI-RADS评估标准中规定的病灶特征时，目标病灶特征为其中对病灶进行识别所得到的病灶特征，即病灶实际具有的病灶特征。在一个示例中，针对BI-RADS病灶特征或TI-RADS病灶特征的每个类别，处理器116分别识别病灶在该类别的多个预设病灶特征中实际具有的病灶特征，即病灶在该类别下的目标病灶特征。
例如，当所述目标区域为乳腺区域、预设病灶特征为BI-RADS病灶特征时，针对乳腺病灶的形状，预设病灶特征包括不规则形、圆形和椭圆形三个病灶特征，目标病灶特征为目标对象的乳腺病灶实际具有的形状特征，例如椭圆形。类似地，当所述目标区域为甲状腺区域、预设病灶特征为TI-RADS病灶特征时，针对甲状腺病灶的成分，预设病灶特征可以包括实性、囊性、囊实混合和海绵状四个病灶特征，目标病灶特征为目标对象的甲状腺病灶实际具有的成分特征，例如实性。
在一个示例中，处理器116可以首先基于相关的机器识别算法检测超声 图像中的病灶，例如，处理器116可以基于深度学习神经网络模型、机器学习模型或传统图像处理方法等检测超声图像中病灶所在的位置，例如，从超声图像中分割出病灶的具体边界。
示例性地，当处理器116采用深度学习神经网络模型检测超声图像中的病灶时，可以预先基于已收集的具有病灶标注结果的超声图像数据对神经网络进行训练，在网络训练阶段计算迭代过程中病灶的检测结果和标注结果之间的误差，并以误差最小化为目的不断更新网络中的权值，直到使检测结果逐渐逼近病灶的标注结果，最终得到训练好的深度学习神经网络模型。
当处理器116采用基于机器学习的病灶自动检测方法时，可以预先基于已收集的具有病灶标注结果的超声图像训练机器学习模型，之后采用训练完成的机器学习模型对超声图像中的像素点的灰度值或纹理值进行二分类，判断每个像素点是否属于病灶区域，从而实现病灶的自动检测。
当采用传统图像处理方式进行病灶的自动检测时，处理器116可以提取超声图像的梯度、纹理等图像特征，并基于提取到的图像特征确定超声图像中病灶所在的区域。
以上示出了几种示例性的病灶自动检测方式，在其他实现方式中，也可以由用户手动在超声图像中标注病灶区域，例如在显示器118上显示超声图像，并根据用户执行的手动标注操作确定其中病灶所在位置。或者，还可以通过半自动检测的方式来确定病灶所在位置，例如，首先基于机器识别算法自动检测超声图像上的病灶的位置，再由用户进一步修改或校正，以获取更为精确的位置。处理器116也可以采用任何其他合适的方法检测超声图像中的病灶。
接着，处理器116识别检测到的病灶的目标病灶特征。在一个实施例中，处理器116可以基于训练好的深度学习神经网络识别病灶的目标病灶特征。例如，当目标区域为甲状腺区域时，可以针对每一类别的TI-RADS病灶特征分别训练一个分类模型，将病灶区域的超声图像分别输入每个分类模型中，得到对应类别的目标病灶特征；或者，也可以采用多任务神经网络，将病灶的超声图像输入到多任务神经网络中，并同时输出多个类别的目标病灶特征。在另一个实施例中，处理器116可以采用传统图像特征提取算法结合机器学习的方法识别病灶的目标病灶特征。例如，当目标区域为甲状腺区域时，分别针对每一个TI-RADS类别进行特征值提取，并将提取到的特征值与根据预 先设定的阈值进行比较，以确定病灶的目标病灶特征。处理器116还可以采用其他任何合适的算法提取病灶的目标病灶特征。
在其他实施例中，处理器116也可以不按照病灶类别识别目标病灶特征，而是分别对每个预设病灶特征进行识别，例如，处理器116可以针对每个预设病灶特征分别训练一个二分类的分类器，用于判断病灶是否具有相应的病灶特征。
获取病灶的目标病灶特征之后，处理器116控制显示器118以图形化的方式显示目标病灶特征。具体地，处理器116控制显示器118在预设图形中显示至少两个预设病灶特征对应的字符，并将所述至少两个预设病灶特征中与目标病灶特征相匹配的病灶特征对应的字符以第一方式区别化显示；其中，所述预设图形包括至少两个区域，一个区域用于显示一个预设病灶特征对应的字符。由此，通过图形化的显示方式，用户可以根据对与目标病灶特征相匹配的病灶特征对应的字符进行的第一方式区别化显示直观地获知病灶的目标病灶特征。
示例性地，第一方式区别化显示包括但不限于以下几种：将与目标病灶特征相匹配的病灶特征对应的字符或显示该字符的区域进行高亮显示或闪烁显示；对字符进行附加符号显示，例如在字符周围显示预设符号；对显示与目标病灶特征相匹配的病灶特征对应的字符的区域进行区别化的底纹颜色显示，或对字符本身进行区别化的字体颜色显示。第一方式区别化显示也可以包括能够将与目标病灶特征对应的字符和与其他预设病灶特征对应的字符区别开来的其他区别化显示方式，例如还可以包括对与其他预设病灶特征对应的字符进行阴影遮蔽等。
在一个实施例中，当目标区域为甲状腺区域时，在预设图形中显示的TI-RADS病灶特征包括TI-RADS病灶特征中所有的病灶特征。类似地，当目标区域为乳腺区域时，在预设图形中显示的BI-RADS病灶特征也可以包括BI-RADS病灶特征中所有的病灶特征。由此，用户既可以了解到TI-RADS评估标准或BI-RADS评估标准中总结的全部的预设病灶特征，从而解决由于病灶特征过多而难以记忆的问题，也可以直观地了解到病灶实际具有的目标病灶特征。
需要注意的是，本申请实施例对表示预设病灶特征的具体字符不做限制，只要字符能够表征相应的预设病灶特征即可。例如，表示甲状腺病灶的回声 类型为无回声时，预设图形中显示的字符可以为“无回声”，也可以为“回声为无回声”；表示甲状腺病灶的钙化类型为微钙化时，预设图形中显示的字符可以为“微钙化”，也可以为“点状强回声”。
在一个实施例中，可以以表格的形式显示病灶的目标病灶特征，表格的形式较为简洁明了、便于查看。在该实施例中，预设图形为表格、预设图形中显示每个预设病灶特征对应的字符的区域为表格中的单元格。
首先参见图2，图2示出了以表格的方式显示的甲状腺病灶的目标病灶特征。其中，在表格的每个单元格中显示了一种TI-RADS病灶特征，整个表格中显示了TI-RADS评估标准中的全部18种TI-RADS病灶特征。其中，处理器116针对超声图像中的病灶识别到的目标病灶特征为低回声、囊实混合、无钙化、宽大于高和甲状腺外侵犯。为了便于图示，在图2所示的表格中，对以上五个目标病灶特征对应的字符所在的单元格的底纹进行了区别化的显示。根据图2所示的表格，用户既可以了解到全部的TI-RADS病灶特征，也可以了解到被测对象的甲状腺病灶实际具有的TI-RADS病灶特征。
类似地，图3示出了以表格的方式显示的乳腺病灶的目标病灶特征，其中，在表格的每个单元格中显示了一种BI-RADS病灶特征，整个表格中显示了BI-RADS评估标准中的全部的26种BI-RADS病灶特征。其中，处理器116识别到了六个目标病灶特征，分别为不规则形、平行、微分叶、低回声、声影和无血流，因而在图3的表格中，对处理器116识别到的以上六个目标病灶特征对应的字符所在的单元格的底纹进行了区别化的显示。
在另一个实施例中，可以以饼图的形式显示病灶的目标病灶特征。在该实施例中，用于显示预设病灶特征对应的字符的预设图形为饼图，饼图中用于显示每个预设病灶特征对应的字符的区域为在饼图中划分出的扇形。
在一些实施例中，预设图形中的至少两个所述区域形成一个区块，同一区块的各个区域用于显示同一类别的预设病灶特征对应的字符，以便于用户根据目标病灶特征所在的区块了解该目标病灶特征所属的类别。例如，BI-RADS病灶特征分为形状、方向、边缘、内部回声、后方回声、钙化和血流七个类别，每个类别包括至少两个BI-RADS病灶特征，当预设图形中显示全部的BI-RADS病灶特征时，可以将预设图形分为7个区块，每个区块的各个区域显示属于同一类别的BI-RADS病灶特征对应的字符。TI-RADS病灶特征分为成分、回声、形状、边缘和局灶性强回声五个类别，则当预设图形中 显示全部的TI-RADS病灶特征时，可以将预设图形分为5个区块，每个区块的各个区域显示属于同一类别的TI-RADS病灶特征对应的字符。
例如，当预设图形为表格时，表格的同一行或同一列的至少两个单元格形成一个区块，即表格的同一行或同一列显示同一类别的BI-RADS病灶特征或同一类别的TI-RADS病灶特征。或者，也可以参照图2和图3，以较为紧凑的方式将属于同一类别的预设病灶特征对应的字符显示在表格不同行或不同列的相邻单元格中，以节省布局面积。
当预设图形为饼图时，饼图中临近的至少两个扇形形成一个区块。例如，首先参照图4，图4示出了以饼图的方式显示的甲状腺病灶的目标病灶特征。其中，在饼图的每个扇形中显示了一种TI-RADS病灶特征，整个饼图分为5个区块，每个区块中的至少两个扇形显示同一类别TI-RADS病灶特征对应的字符，整个饼图中显示了成分、回声、形状、边缘和局灶性强回声五个类别对应的五个区块，以及五个类别的全部18种TI-RADS病灶特征对应的18个扇形区域。示例性的，饼图右上角的四个扇形区域显示有字符：极低、低、等或高、无，这四个扇形内显示的字符均对应回声类别的预设病灶特征，因此这四个扇形区域可以形成一个表征回声类别的区块。其中，处理器116识别到的五个类别的目标病灶特征分别为低回声、囊性、无钙化、宽大于高和甲状腺外侵犯，为了便于显示，在图4的饼图中，对以上五个目标病灶特征对应的字符所在的扇形的底纹进行了区别化的显示。
类似地，图5示出了以饼图的方式显示的乳腺病灶的目标病灶特征，其中，在饼图的每个扇形中显示了一种BI-RADS病灶特征，整个饼图分为7个区块，每个区块中的至少两个扇形显示同一类别BI-RADS病灶特征对应的字符，整个饼图中显示了形状、方向、边缘、内部回声、后方回声、钙化和血流七个类别对应的七个区块，以及七个类别的全部的26种BI-RADS病灶特征对应的26个扇形区域。示例性的，饼图右上角的两个扇形区域显示有字符：平行、不平行，这两个扇形内显示的字符均为对应方向类别的预设病灶特征，因此这两个扇形区域可以形成一个表征方向类型的区块。针对以上七个类别，处理器116识别到的目标病灶特征分别为不规则形、平行、微分叶、低回声、声影和内部血流，因而在图5的饼图中，对处理器116识别到的以上七个目标病灶特征对应的字符所在的扇形的底纹进行了区别化的显示。
在一些实施例中，处理器116可以控制显示器118对每个区块进行区别 化的显示，以便于区分各个区块。例如，处理器116可以控制显示器118将同一区块的各个区域显示为同一颜色或图案，或者，处理器116可以控制显示器118将同一区块的各个区域中的预设病灶特征对应的字符显示为同一颜色。除此之外，处理器116也可以控制显示器118通过其他方式区别化显示不同的区块，例如在区块间显示加粗的分界线或不同颜色的分界线等。在一些实施例中，还可以在每个区块附近显示该区块中的预设病灶特征所属的类别对应的字符，以更清晰地标注区块所对应的病灶类别，例如，参照图4，在图4所示的饼图中，左上角的区块的各个扇形中显示了表征成分的预设病灶特征，即实性、囊性、囊实混合和海绵状；因而在该区块附近显示字符“成分”，以表示该区块中的预设病灶特征表征的是病灶的成分。类似地，图4的饼图的其他四个区块附近分别显示有字符“回声”、“形状”、“边缘”和“局灶性强回声”，以表示各个区块中显示的预设病灶特征所属的类别。
在一些实施例中，当预设图形中显示全部的BI-RADS病灶特征或TI-RADS病灶特征时，处理器116还用于：当目标区域为乳腺区域时，控制显示器118以第二方式区别化显示BI-RADS病灶特征中表征特定病灶状态的病灶特征对应的字符；当目标区域为甲状腺区域时，控制显示器118以第二方式区别化显示TI-RADS病灶特征中表征特定病灶状态的病灶特征对应的字符，其中，第二方式区别化显示不同于上述的第一方式区别化显示。其中，第二方式区别化显示的可以是预设病灶特征中的全部表征特定病灶状态的病灶特征对应的字符，也可以是目标病灶特征中表征特定病灶状态的病灶特征对应的字符。
其中，表征特定病灶状态的病灶特征可以是表征病灶为恶性病灶的可能性较大的病灶特征。BI-RADS评估标准和TI-RADS评估标准中的部分病灶特征在临床上更多的出现于恶性的病灶中，这部分病灶特征被定义为恶性征象，需要用户格外注意，因而可以在预设图形中将这部分病灶特征对应的字符进行第二方式区别化显示。
示例性地，第二方式区别化显示包括但不限于以下至少一种：高亮显示、闪烁显示、附加符号显示、区别化的底纹颜色显示或区别化的字体颜色显示。例如，当第一方式区别化显示为高亮显示时，第二方式区别化显示可以是闪烁显示。结合图2，其中对低回声、囊实混合、无钙化、宽大于高和甲状腺外侵犯几个目标病灶特征对应的字符所在单元格的底纹进行了第一方式区别 化显示；由于其中甲状腺外侵犯为恶性征象，因而可以对甲状腺外侵犯所对应的单元格进行高亮显示；可选地，也可以对预设病灶特征中表征特定病灶状态的病灶特征对应的字符高亮显示，即表格中的全部恶性征象进行高亮显示。
在另一个实施例中，预设图形中可以不显示全部的BI-RADS病灶特征或TI-RADS病灶特征对应的字符，而只显示表征特定病灶状态的病灶特征对应的字符，以向用户提供更有针对性的信息。具体地，当目标区域为乳腺区域时，可以在预设图形中显示表征特定病灶状态的BI-RADS病灶特征对应的字符；当目标区域为甲状腺区域时，可以在预设图形中显示表征特定病灶状态的TI-RADS病灶特征对应的字符。由于用户需要格外注意多出现于恶性病灶中的病灶特征，因而表征特定病灶状态的病灶特征可以是BI-RADS病灶特征或TI-RADS病灶特征中表征恶性征象的病灶特征。
示例性地，当目标区域为甲状腺区域时，TI-RADS病灶特征中更多出现于恶性病灶中的、表征特定病灶状态的病灶特征可以是TI-RADS标准中评分在2分以上的病灶特征，具体包括回声为低回声、回声为极低回声、形状为高大于宽、边缘为分叶状或不规则、边缘为甲状腺外侵犯、钙化为周边钙化、钙化为点状强回声和成分为实性。参见图6，其中在饼图中示出了以上8种TI-RADS病灶特征对应的字符；在图6的示例中，对低回声和甲状腺外侵犯两种病灶特征对应的区域相比于其他区域进行了区别化的显示，表示低回声和甲状腺外侵犯为目标病灶特征，即处理器116识别到病灶实际具有这两种病灶特征。
当目标区域为乳腺区域时，BI-RADS病灶特征中更多出现于恶性病灶中的、表征特定病灶状态的病灶特征包括以下至少一项：边缘为成角、边缘为模糊、边缘为毛刺、边缘为微分叶、方向为不平行、形状为不规则形、血流为内部血流、钙化为导管内钙化、钙化为肿块外钙化、钙化为肿块内钙化、后方回声为混合改变、后方回声为声影、内部回声为不均回声。参加图7，其中在饼图中显示了以上12种BI-RADS病灶特征对应的字符；在图7的示例中，对微分叶、声影、不规则形和内部血流这四种病灶特征对应的区域相比于其他区域进行了区别化的显示，表示这四种病灶特征为目标病灶特征，即处理器116识别到病灶实际具有这四种病灶特征。
虽然图6和图7以饼图的形式显示了表征特定病灶状态的病灶特征对应 的字符，但在其他实施例中，也可以采用其他预设图形显示上述表征特定病灶状态的病灶特征对应的字符，具体包括但不限于表格。并且，当在预设图形中显示表征特定病灶状态的病灶特征对应的字符时，也可以将属于同一类别的预设病灶特征对应的字符显示在同一区块中以便于查看，例如，图6中属于回声类别的低回声和极低回声显示在同一区块中，图7中属于边缘类别的毛刺、微分叶、成角和边缘模糊显示在同一区块中。
在另一实施例中，预设图形中的至少两个区域形成一个区块，同一区块的各个区域用于显示表征同一病灶状态的预设病灶特征对应的字符，以便于用户根据目标病灶特征所在的区块了解病灶的病灶状态。也就是说，在该实施例中，同一区块不再用于显示属于同一类别的预设病灶特征，而是用于显示表征同一病灶状态的预设病灶特征。在一些实施例中，以上两种区块的划分方式可以相互结合，例如表格的同一行显示同一类别的预设病灶特征，同一列显示表征同一病灶状态的预设病灶特征。
其中，病灶状态可以表示病灶的良恶性。例如，TI-RADS评估标准对甲状腺病灶的18个特征进行了0到3的评分，评分越高，恶性病灶中出现该病灶特征的可能性越大，因而可以在预设图形的同一区块中显示具有同一评分的TI-RADS病灶特征。具体地，当目标区域为甲状腺区域时，表征同一病灶状态的预设病灶特征包括TI-RADS病灶特征中：1)由无钙化、无回声、海绵状、宽大于高、不确定、光滑、囊性组成的表征第一病灶状态的预设病灶特征，即评分为0分的TI-RADS病灶特征；2)由粗钙化、高或等回声、囊实混合组成的表征第二病灶状态的预设病灶特征，即评分为1分的TI-RADS病灶特征；3)由低回声、分叶状或不规则、周边钙化、实性组成的表征第三病灶状态的预设病灶特征，即评分为2分的TI-RADS病灶特征；4)由高大于宽、甲状腺外侵犯、点状强回声、极低回声组成的表征第四病灶状态的预设病灶特征，即评分为3分的TI-RADS病灶特征。
在一个实施例中，参照图8，所述预设图形可以是环形图，所述环形图包括至少一个环形，一个所述环形包括至少两个扇形环；显示每个预设病灶特征对应的字符的区域为环形图中的扇形环，至少两个扇形环构成的区块为环形图中的所述环形。可以理解的是，由于环形图最内环围绕圆心设置，因而环形图中心的图形可以为扇形；中心显示有扇形的环形图也在本申请的环形图所涵盖的范围内。在图8的环形图中，由中间的扇形图到外侧的每个环 形依次显示评分为0分-3分的TI-RADS病灶特征对应的字符，并将其中病灶实际具有的TI-RADS病灶特征对应的字符所在的扇形或扇形环进行了第一方式区别化显示。此外，图8的环形图的中间的扇形图和每个环形上还标注有该环形显示的预设病灶特征的评分，以供用户参照。对于乳腺区域来说，由于目前没有BI-RADS病灶特征的评分标准，因而可以根据临床经验对BI-RADS病灶按照其良恶性进行分类，并显示在环形图中。
可选地，处理器116可以实现为软件、硬件、固件或其任意组合，并且可以使用单个或多个专用集成电路(Application Specific Integrated Circuit，ASIC)、单个或多个通用集成电路、单个或多个微处理器、单个或多个可编程逻辑器件、或者前述电路和/或器件的任意组合、或者其他适合的电路或器件。并且，处理器116可以控制所述超声成像系统100中的其它组件以执行本说明书中的各个实施例中的方法的相应步骤。
显示器118与处理器116连接，显示器118可以为触摸显示屏、液晶显示屏等；或者，显示器118可以为独立于超声成像系统100之外的液晶显示器、电视机等独立显示器；或者，显示器118可以是智能手机、平板电脑等电子设备的显示屏，等等。其中，显示器118的数量可以为一个或多个。例如，显示器118可以包括主屏和触摸屏，主屏主要用于显示超声图像，触摸屏主要用于人机交互。
显示器118可以显示处理器116得到的超声图像。此外，显示器118在显示超声图像的同时还可以提供给用户进行人机交互的图形界面，在图形界面上设置一个或多个被控对象，提供给用户利用人机交互装置输入操作指令来控制这些被控对象，从而执行相应的控制操作。例如，在图形界面上显示图标，利用人机交互装置可以对该图标进行操作，用来执行特定的功能，例如在超声图像上绘制出感兴趣区域框等。
可选地，超声成像系统100还可以包括显示器118之外的其他人机交互装置，其与处理器116连接，例如，处理器116可以通过外部输入/输出端口与人机交互装置连接，外部输入/输出端口可以是无线通信模块，也可以是有线通信模块，或者两者的组合。外部输入/输出端口也可基于USB、如CAN等总线协议、和/或有线网络协议等来实现。
其中，人机交互装置可以包括输入设备，用于检测用户的输入信息，该输入信息例如可以是对超声波发射/接收时序的控制指令，可以是在超声图像 上绘制出点、线或框等的操作输入指令，或者还可以包括其他指令类型。输入设备可以包括键盘、鼠标、滚轮、轨迹球、移动式输入设备(比如带触摸显示屏的移动设备、手机等等)、多功能旋钮等等其中之一或者多个的结合。人机交互装置还可以包括诸如打印机之类的输出设备。
超声成像系统100还可以包括存储器124，用于存储处理器执行的指令、存储接收到的超声回波、存储超声图像，等等。存储器可以为闪存卡、固态存储器、硬盘等。其可以为易失性存储器和/或非易失性存储器，为可移除存储器和/或不可移除存储器等。
应理解，图1所示的超声成像系统100所包括的部件只是示意性的，其可以包括更多或更少的部件，本申请对此不限定。
本申请实施例还提供一种超声成像系统，继续参照图1，所述超声成像系统包括探头、发射电路、接收电路、处理器和显示器，各个部件的相关描述可以参照上文对超声成像系统100的相关描述，以下仅对超声成像系统的主要功能进行描述，而省略以上已经描述过的细节内容。
具体地，发射电路用于激励所述探头向被测对象发射超声波；接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；处理器用于处理所述超声回波信号以获得超声图像；所述处理器还用于：获取被测对象目标区域的超声图像；检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；控制所述显示器在预设图形中显示至少两个预设病灶特征对应的字符，并将所述至少两个预设病灶特征中与所述目标病灶特征相匹配的病灶特征对应的字符区别化显示；其中，所述预设图形包括至少两个区域，一个所述区域用于显示一个所述预设病灶特征对应的字符。
本实施例的超声成像系统与上文所述的超声成像系统100大体上类似，二者的区别主要在于被测对象的目标区域不限于乳腺区域和甲状腺区域，也包括肝脏区域或其他目标区域。相应地，不同的目标区域对应不同的评估标准，预设病灶特征和目标病灶特征为相应评估标准下的病灶特征。例如，当目标区域为肝脏区域时，相应地，处理器采用针对肝脏的评估标准对超声图像进行分析。
下面，将参考图9描述根据本申请一实施例的超声图像分析方法。图9是本申请实施例的超声图像分析方法900的一个示意性流程图。
如图9所示，本申请实施例的超声图像分析方法900包括如下步骤：
步骤S910，获取被测对象目标区域的超声图像；
步骤S920，检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
步骤S930，在预设图形中显示至少两个预设病灶特征对应的字符，并将所述至少两个预设病灶特征中与所述目标病灶特征相匹配的病灶特征对应的字符以第一方式区别化显示；其中，所述预设图形包括至少两个区域，一个所述区域用于显示一个所述预设病灶特征对应的字符。
示例性地，所述目标区域包括甲状腺区域或乳腺区域，当所述目标区域为乳腺区域时，所述预设病灶特征包括BI-RADS病灶特征，当所述目标区域为甲状腺区域时，所述预设病灶特征包括TI-RADS病灶特征。
关于本申请实施例的超声图像分析方法900的其他具体细节可以参照上文的相关描述，在此不做赘述。
本申请实施例的超声成像系统和超声图像分析方法在预设图形中显示预设病灶特征，并将其中识别到的目标病灶特征进行区别化显示，从而直观地呈现预设病灶特征和病灶实际具有的目标病灶特征，提高超声图像的分析效率。
本申请实施例第二方面提供一种超声成像系统，继续参照图1，所述超声成像系统包括探头、发射电路、接收电路、处理器和显示器，各个部件的相关描述可以参照上文对超声成像系统100进行的相关描述，以下仅对超声成像系统的主要功能进行描述，而省略以上已经描述过的细节内容。
具体地，所述发射电路用于激励所述探头向被测对象发射超声波；所述接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；所述处理器用于处理所述超声回波信号以获得超声图像；所述处理器还用于：获取被测对象目标区域的超声图像，所述目标区域包括甲状腺区域或乳腺区域；检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；确定所述病灶的病灶特征中表征特定病灶状态的病灶特征；控制所述显示器在预设图形中显示所述病灶的目标病灶特征对应的字符，并区别化显示所述病灶的目标病灶特征中表征特定病灶状态的病灶特征对应的字符；当所述目标区域为乳腺区域时，所述目标病灶特征包括BI-RADS病灶特征中的至少一种，当所述目标区域为甲状腺区域时，所述目标病灶特征包括TI-RADS病灶 特征中的至少一种。
本实施例的超声成像系统与上文所述的超声成像系统100的区别主要在于：在本实施例的超声成像系统中，预设图形中显示的是病灶的目标病灶特征对应的字符，而不必显示病灶不具有的病灶特征。目标病灶特征中表征特定病灶状态的目标病灶特征可以是BI-RADS病灶特征或TI-RADS病灶特征中的恶性征象，即TI-RADS病灶特征中的回声为低回声、回声为极低回声、形状为高大于宽、边缘为分叶状或不规则、边缘为甲状腺外侵犯、钙化为周边钙化、钙化为点状强回声、成分为实性，以及BI-RADS病灶特征中的边缘为成角、边缘为模糊、边缘为毛刺、边缘为微分叶、方向为不平行、形状为不规则形、血流为内部血流、钙化为导管内钙化、钙化为肿块外钙化、钙化为肿块内钙化、后方回声为混合改变、后方回声为声影、内部回声为不均回声。区别化显示包括但不限于高亮显示、闪烁显示、附加符号显示、区别化的底纹颜色显示或区别化的字体颜色显示。
参见图10、图11，其中图10所示的显示界面中示出了甲状腺区域的超声图像1010和基于该超声图像1010识别得到的甲状腺病灶的TI-RADS病灶特征，图11所示的显示界面中示出了乳腺区域的超声图像1020和基于该超声图像1010识别得到的乳腺区域的BI-RADS病灶特征。在图10和图11所示的显示方式中，预设图形为方框，每个目标病灶特征的字符显示在一个方框中。在图10和图11所示的显示方式中，目标病灶特征按照其所属的类别进行显示，即针对每个类别的BI-RADS病灶特征或TI-RADS病灶特征分别识别到该类别下的目标病灶特征并显示在对应的方框中，方框上方显示当前目标病灶特征所属的类别。在图10所示的显示界面中，方框中显示的TI-RADS病灶特征表示病灶所实际具有的目标病灶特征，包括表征病灶形状的高大于宽、表征病灶成分的囊实性、表征病灶回声的低回声和表征病灶边缘的甲状腺外侵犯；病灶无局灶性强回声；其中，低回声和甲状腺外侵犯为TI-RADS评估标准下的恶性征象，因而对这两个病灶特征对应的字符所在的区域进行区别化显示。在图11所示的显示界面中，方框中显示的BI-RADS病灶特征表示病灶所实际具有的目标病灶特征，包括表征病灶形状的不规则形、表征病灶方向的平行、表征病灶边缘的成角、表征病灶回声的低回声、表征病灶后方回声的无改变、表征病灶钙化的肿块内钙化和表征病灶血流的内部血流。其中，不规则形、成角、肿块内钙化和内部血流为BI-RADS评估 标准下的恶性征象，因而对这四个病灶特征对应的字符所在的区域进行区别化显示。
继续参照图10、图11，在一些实施例中，所述方框可以实现为下拉框的形式，并且可以允许用户对目标病灶特征进行修改。具体地，当用户选择下拉框右侧的箭头时，可以显示列举当前类别下的其他病灶特征的下拉菜单，用户可以根据实际情况选择其他的病灶特征，以替换机器自动识别的目标病灶特征。
在一些实施例中，可以将表征不同病灶状态的目标病灶特征对应的字符或字符所在区域显示为不同的颜色。或者，可以将不同类别的目标病灶特征显示为不同的颜色，以便于用户对其进行区分。
需要注意的是，显示病灶目标特征对应字符的预设图形不限于图10和图11所示的形式，例如，预设图形还可以是表格、饼图、环形图或其他合适的形式。例如，当预设图形为预设图形为表格时，可以在表格的每个单元格中显示一个目标病灶特征，并将其中的恶性征象所对应的字符进行区别化显示，或者将其中不同病灶状态的目标病灶特征对应的字符或字符所在区域显示为不同的颜色；示例性地，表格中还可以同时显示目标病灶特征所属的类别。当预设图形为扇形图时，可以在扇形图的每个扇形中显示一个目标病灶特征，并且可以在扇形外围显示目标病灶特征所属的类别。当预设图形为环形图时，可以将目标病灶特征按照其表征的病灶状态进行排列，例如当目标病灶特征为TI-RADS病灶特征时，可以在环形图中由内到外的每个环形中依次显示评分由高到低或由低到高的TI-RADS病灶特征。
本申请实施例还提供一种超声成像系统，包括探头、发射电路、接收电路、处理器和显示器，其中，所述发射电路用于激励所述探头向被测对象发射超声波；所述接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；所述处理器用于处理所述超声回波信号以获得超声图像；所述处理器还用于：获取被测对象目标区域的超声图像；检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；确定所述病灶的病灶特征中表征特定病灶状态的病灶特征；控制所述显示器在预设图形中显示所述病灶的目标病灶特征对应的字符，并区别化显示所述病灶的目标病灶特征中表征特定病灶状态的病灶特征对应的字符。
本实施例的超声成像系统与上文所述的超声成像系统大体上类似，二者 的区别主要在于被测对象的目标区域不限于乳腺区域和甲状腺区域，也包括肝脏区域或其他目标区域。相应地，不同的目标区域对应不同的评估标准，目标病灶特征为相应评估标准下的病灶特征。
下面，将参考图12描述根据本申请一实施例的超声图像分析方法。图12是本申请实施例的超声图像分析方法1200的一个示意性流程图。
如图12所示，本申请实施例的超声图像分析方法1200包括如下步骤：
步骤S1210，获取被测对象目标区域的超声图像；
步骤S1220，检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
步骤S1230，在预设图形中显示所述病灶的目标病灶特征对应的字符，并区别化显示所述病灶的目标病灶特征中表征特定病灶状态的病灶特征对应的字符。
示例性地，所述目标区域包括甲状腺区域或乳腺区域，当所述目标区域为乳腺区域时，所述预设病灶特征包括BI-RADS病灶特征，当所述目标区域为甲状腺区域时，所述预设病灶特征包括TI-RADS病灶特征。
关于本申请实施例的超声图像分析方法1200的其他具体细节可以参照上文的相关描述，在此不做赘述。
本申请实施例的超声成像系统和超声图像分析方法在预设图形中显示目标病灶特征对应的字符，并将其中表征特定病灶状态的目标病灶特征进行区别化显示，从而直观地呈现目标病灶特征并提示用户其中表征特定病灶状态的目标病灶特征，提高超声图像的分析效率。
本申请实施例第三方面提供一种超声成像系统，继续参照图1，所述超声成像系统包括探头、发射电路、接收电路、处理器和显示器，其中：所述发射电路用于激励所述探头向被测对象发射超声波；所述接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；所述处理器用于处理所述超声回波信号以获得超声图像；所述处理器还用于：获取被测对象目标区域的超声图像，所述目标区域包括甲状腺区域或乳腺区域；检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；控制所述显示器在预设图形中显示所述病灶的目标病灶特征对应的标识；当所述目标区域为乳腺区域时，所述目标病灶特征包括BI-RADS病灶特征，当所述目标区域为 甲状腺区域时，所述目标病灶特征包括TI-RADS病灶特征。
本实施例的超声成像系统与本申请实施例第二方面所提供的超声成像系统的区别主要在于：首先，在本实施例的超声成像系统中，不限制预设图形的具体形式，例如预设图形可以不分区，或者，预设图形的每个区域中可以显示多个目标病灶特征；其次，目标病灶特征的标识不限于字符，也可以是图形或文字，只要能够表示对应的目标病灶特征即可；最后，显示器只需要显示目标病灶特征对应的标识、以提示用户病灶实际具有的病灶特征即可，而无需区别化显示表征特定病灶状态的病灶特征。
本申请实施例还提供一种超声成像系统，包括探头、发射电路、接收电路、处理器和显示器，其中：所述发射电路用于激励所述探头向被测对象发射超声波；所述接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；所述处理器用于处理所述超声回波信号以获得超声图像；所述处理器还用于：获取被测对象目标区域的超声图像；检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；控制所述显示器在预设图形中显示所述病灶的目标病灶特征对应的标识。
本实施例的超声成像系统与上文所述的超声成像系统大体上类似，二者的区别主要在于被测对象的目标区域不限于乳腺区域和甲状腺区域，也包括其他目标区域。相应地，不同的目标区域对应不同的评估标准，目标病灶特征为相应评估标准下的病灶特征。
下面，将参考图13描述根据本申请一实施例的超声图像分析方法。图13是本申请实施例的超声图像分析方法1300的一个示意性流程图。
如图13所示，本申请实施例的超声图像分析方法1300包括如下步骤：
在步骤S1310，获取被测对象目标区域的超声图像；
在步骤S1320，检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
在步骤S1330，在预设图形中显示所述病灶的目标病灶特征对应的字符。
示例性地，所述目标区域包括甲状腺区域或乳腺区域，当所述目标区域为乳腺区域时，所述目标病灶特征包括BI-RADS病灶特征，当所述目标区域为甲状腺区域时，所述目标病灶特征包括TI-RADS病灶特征。
关于本申请实施例的超声图像分析方法1300的其他具体细节可以参照上文的相关描述，在此不做赘述。
本申请实施例的超声成像系统和超声图像分析方法在预设图形中显示目标病灶特征对应的标识，从而直观地呈现目标病灶特征，提高超声图像的分析效率。
尽管这里已经参考附图描述了示例实施例，应理解上述示例实施例仅仅是示例性的，并且不意图将本申请的范围限制于此。本领域普通技术人员可以在其中进行各种改变和修改，而不偏离本申请的范围和精神。所有这些改变和修改意在被包括在所附权利要求所要求的本申请的范围之内。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
在本申请所提供的几个实施例中，应该理解到，所揭露的设备和方法，可以通过其它的方式实现。例如，以上所描述的设备实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个设备，或一些特征可以忽略，或不执行。
在此处所提供的说明书中，说明了大量具体细节。然而，能够理解，本申请的实施例可以在没有这些具体细节的情况下实践。在一些实例中，并未详细示出公知的方法、结构和技术，以便不模糊对本说明书的理解。
类似地，应当理解，为了精简本申请并帮助理解各个发明方面中的一个或多个，在对本申请的示例性实施例的描述中，本申请的各个特征有时被一起分组到单个实施例、图、或者对其的描述中。然而，并不应将该本申请的方法解释成反映如下意图：即所要求保护的本申请要求比在每个权利要求中所明确记载的特征更多的特征。更确切地说，如相应的权利要求书所反映的那样，其发明点在于可以用少于某个公开的单个实施例的所有特征的特征来解决相应的技术问题。因此，遵循具体实施方式的权利要求书由此明确地并入该具体实施方式，其中每个权利要求本身都作为本申请的单独实施例。
本领域的技术人员可以理解，除了特征之间相互排斥之外，可以采用任何组合对本说明书(包括伴随的权利要求、摘要和附图)中公开的所有特征以及如此公开的任何方法或者设备的所有过程或单元进行组合。除非另外明 确陈述，本说明书(包括伴随的权利要求、摘要和附图)中公开的每个特征可以由提供相同、等同或相似目的的替代特征来代替。
此外，本领域的技术人员能够理解，尽管在此所述的一些实施例包括其它实施例中所包括的某些特征而不是其它特征，但是不同实施例的特征的组合意味着处于本申请的范围之内并且形成不同的实施例。例如，在权利要求书中，所要求保护的实施例的任意之一都可以以任意的组合方式来使用。
本申请的各个部件实施例可以以硬件实现，或者以在一个或者多个处理器上运行的软件模块实现，或者以它们的组合实现。本领域的技术人员应当理解，可以在实践中使用微处理器或者数字信号处理器(DSP)来实现根据本申请实施例的一些模块的一些或者全部功能。本申请还可以实现为用于执行这里所描述的方法的一部分或者全部的装置程序(例如，计算机程序和计算机程序产品)。这样的实现本申请的程序可以存储在计算机可读介质上，或者可以具有一个或者多个信号的形式。这样的信号可以从因特网网站上下载得到，或者在载体信号上提供，或者以任何其他形式提供。
应该注意的是上述实施例对本申请进行说明而不是对本申请进行限制，并且本领域技术人员在不脱离所附权利要求的范围的情况下可设计出替换实施例。在权利要求中，不应将位于括号之间的任何参考符号构造成对权利要求的限制。本申请可以借助于包括有若干不同元件的硬件以及借助于适当编程的计算机来实现。在列举了若干装置的单元权利要求中，这些装置中的若干个可以是通过同一个硬件项来具体体现。单词第一、第二、以及第三等的使用不表示任何顺序。可将这些单词解释为名称。
以上所述，仅为本申请的具体实施方式或对具体实施方式的说明，本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。本申请的保护范围应以权利要求的保护范围为准。

Claims (24)

  1. 一种超声成像系统，其特征在于，包括探头、发射电路、接收电路、处理器和显示器，其中：
    所述发射电路用于激励所述探头向被测对象发射超声波；
    所述接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；
    所述处理器用于处理所述超声回波信号以获得超声图像；
    所述处理器还用于：获取被测对象目标区域的超声图像，所述目标区域包括甲状腺区域或乳腺区域；
    检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
    控制所述显示器在预设图形中显示至少两个预设病灶特征对应的字符，并将所述至少两个预设病灶特征中与所述目标病灶特征相匹配的病灶特征对应的字符以第一方式区别化显示；其中，所述预设图形包括至少两个区域，一个所述区域用于显示一个所述预设病灶特征对应的字符；
    当所述目标区域为乳腺区域时，所述预设病灶特征包括BI-RADS病灶特征，当所述目标区域为甲状腺区域时，所述预设病灶特征包括TI-RADS病灶特征。
  2. 根据权利要求1所述的超声成像系统，其特征在于，当所述目标区域为乳腺区域时，所述BI-RADS病灶特征包括BI-RADS病灶特征中所有的病灶特征；当所述目标区域为甲状腺区域时，所述TI-RADS病灶特征包括TI-RADS病灶特征中所有的病灶特征。
  3. 根据权利要求1所述的超声成像系统，其特征在于，当所述目标区域为乳腺区域时，所述BI-RADS病灶特征包括BI-RADS病灶特征中表征特定病灶状态的病灶特征；当所述目标区域为甲状腺区域时，所述TI-RADS病灶特征包括TI-RADS病灶特征中表征特定病灶状态的病灶特征。
  4. 根据权利要求3所述的超声成像系统，其特征在于，当所述目标区域为乳腺区域时，所述BI-RADS病灶特征中表征特定病灶状态的病灶特征包括：边缘为成角、边缘为模糊、边缘为毛刺、边缘为微分叶、方向为不平行、形状为不规则形、血流为内部血流、钙化为导管内钙化、钙化为肿块外钙化、钙化为肿块内钙化、后方回声为混合改变、后方回声为声影、内部回声为不均回声中的至少一项；
    当所述目标区域为甲状腺区域时，所述TI-RADS病灶特征中表征特定病灶状态的病灶特征包括：回声为低回声、回声为极低回声、形状为高大于宽、 边缘为分叶状或不规则、边缘为甲状腺外侵犯、钙化为周边钙化、钙化为点状强回声、成分为实性中的至少一项。
  5. 根据权利要求2或3所述的超声成像系统，其特征在于，还包括：至少两个所述区域形成一个区块，同一所述区块的各个所述区域用于显示同一类别的预设病灶特征对应的字符；
    所述同一类别的预设病灶特征包括表征病灶相同临床指标的预设病灶特征的集合。
  6. 根据权利要求5所述的超声成像系统，其特征在于，所述表征病灶相同临床指标的预设病灶特征包括：
    当所述目标区域为乳腺区域时，所述同一类别的预设病灶特征包括
    BI-RADS病灶特征中用于表征病灶边缘的一类病灶特征、用于表征病灶方向的一类病灶特征、用于表征病灶形状的一类病灶特征、用于表征病灶血流的一类病灶特征、用于表征病灶钙化的一类病灶特征、用于表征病灶后方回声的一类病灶特征和用于表征病灶内部回声的一类病灶特征中的至少一个；
    当所述目标区域为甲状腺区域时，所述同一类别的预设病灶特征包括TI-RADS病灶特征中用于表征病灶回声的一类病灶特征、用于表征病灶形状的一类病灶特征、用于表征病灶边缘的一类病灶特征、用于表征病灶局部强回声的一类病灶特征和用于表征病灶成分的一类病灶特征中的至少一个。
  7. 根据权利要求5或6所述的超声成像系统，其特征在于，所述预设图形包括表格，所述区域包括单元格，所述表格的同一行或同一列的至少两个所述单元格形成一个所述区块。
  8. 根据权利要求5或6所述的超声成像系统，其特征在于，所述预设图形包括饼图，所述区域包括扇形，所述饼图中临近的至少两个扇形形成一个所述区块。
  9. 根据权利要求2所述的超声成像系统，其特征在于，还包括：至少两个所述区域形成一个区块，同一区块的各个所述区域用于显示表征同一病灶状态的预设病灶特征对应的字符。
  10. 根据权利要求9所述的超声成像系统，其特征在于，当所述目标区域为甲状腺区域时，所述表征同一病灶状态的预设病灶特征包括TI-RADS病灶特征中：
    无钙化、无回声、海绵状、宽大于高、不确定、光滑、囊性组成的表征第一病灶状态的预设病灶特征；粗钙化、高或等回声、囊实混合组成的表征第二病灶状态的预设病灶特征；低回声、分叶状或不规则、周边钙化、实性 组成的表征第三病灶状态的预设病灶特征；高大于宽、甲状腺外侵犯、点状强回声、极低回声组成的表征第四病灶状态的预设病灶特征。
  11. 根据权利要求9或10所述的超声成像系统，其特征在于，所述预设图形包括环形图，所述环形图包括至少一个环形，一个所述环形包括至少两个扇形环；所述区域包括所述扇形环，所述区块包括所述环形。
  12. 根据权利要求5-11中任一项所述的超声成像系统，其特征在于，所述处理器还用于：控制所述显示器将同一所述区块的各个所述区域显示为同一颜色或图案，或者，将同一所述区块的各个所述区域中的预设病灶特征对应的字符显示为同一颜色。
  13. 根据权利要求1-12中任一项所述的超声成像系统，其特征在于，所述第一方式区别化显示包括：高亮显示、闪烁显示、附加符号显示、区别化的底纹颜色显示或区别化的字体颜色显示。
  14. 根据权利要求2、5-13中任一项所述的超声成像系统，其特征在于，所述处理器还用于：当所述目标区域为乳腺区域时，控制所述显示器以第二方式区别化显示所述BI-RADS病灶特征中表征特定病灶状态的病灶特征对应的字符；当所述目标区域为甲状腺区域时，控制所述显示器以第二方式区别化显示所述TI-RADS病灶特征中表征特定病灶状态的病灶特征对应的字符，所述第一方式区别化显示与第二方式区别化显示不同。
  15. 一种超声成像系统，其特征在于，包括探头、发射电路、接收电路、处理器和显示器，其中：
    所述发射电路用于激励所述探头向被测对象发射超声波；
    所述接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；
    所述处理器用于处理所述超声回波信号以获得超声图像；
    所述处理器还用于：获取被测对象目标区域的超声图像，所述目标区域包括甲状腺区域或乳腺区域；
    检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
    确定所述病灶的病灶特征中表征特定病灶状态的病灶特征；
    控制所述显示器在预设图形中显示所述病灶的目标病灶特征对应的字符，并区别化显示所述病灶的目标病灶特征中表征特定病灶状态的病灶特征对应的字符；
    当所述目标区域为乳腺区域时，所述目标病灶特征包括BI-RADS病灶特征中的至少一种，当所述目标区域为甲状腺区域时，所述目标病灶特征包括 TI-RADS病灶特征中的至少一种。
  16. 一种超声成像系统，其特征在于，包括探头、发射电路、接收电路、处理器和显示器，其中：
    所述发射电路用于激励所述探头向被测对象发射超声波；
    所述接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；
    所述处理器用于处理所述超声回波信号以获得超声图像；
    所述处理器还用于：获取被测对象目标区域的超声图像，所述目标区域包括甲状腺区域或乳腺区域；
    检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
    控制所述显示器在预设图形中显示所述病灶的目标病灶特征对应的标识；
    当所述目标区域为乳腺区域时，所述目标病灶特征包括BI-RADS病灶特征，当所述目标区域为甲状腺区域时，所述目标病灶特征包括TI-RADS病灶特征。
  17. 一种超声成像系统，其特征在于，包括探头、发射电路、接收电路、处理器和显示器，其中：
    所述发射电路用于激励所述探头向被测对象发射超声波；
    所述接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；
    所述处理器用于处理所述超声回波信号以获得超声图像；
    所述处理器还用于：获取被测对象目标区域的超声图像；
    检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
    控制所述显示器在预设图形中显示至少两个预设病灶特征对应的字符，并将所述至少两个预设病灶特征中与所述目标病灶特征相匹配的病灶特征对应的字符区别化显示；其中，所述预设图形包括至少两个区域，一个所述区域用于显示一个所述预设病灶特征对应的字符。
  18. 一种超声成像系统，其特征在于，包括探头、发射电路、接收电路、处理器和显示器，其中：
    所述发射电路用于激励所述探头向被测对象发射超声波；
    所述接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；
    所述处理器用于处理所述超声回波信号以获得超声图像；
    所述处理器还用于：获取被测对象目标区域的超声图像；
    检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
    确定所述病灶的病灶特征中表征特定病灶状态的病灶特征；
    控制所述显示器在预设图形中显示所述病灶的目标病灶特征对应的字符，并区别化显示所述病灶的目标病灶特征中表征特定病灶状态的病灶特征对应的字符。
  19. 一种超声成像系统，其特征在于，包括探头、发射电路、接收电路、处理器和显示器，其中：
    所述发射电路用于激励所述探头向被测对象发射超声波；
    所述接收电路用于控制所述探头接收从被测对象返回的超声回波以获得超声回波信号；
    所述处理器用于处理所述超声回波信号以获得超声图像；
    所述处理器还用于：获取被测对象目标区域的超声图像；
    检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
    控制所述显示器在预设图形中显示所述病灶的目标病灶特征对应的标识。
  20. 一种超声图像分析方法，其特征在于，所述方法包括：
    获取被测对象目标区域的超声图像；
    检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
    在预设图形中显示至少两个预设病灶特征对应的字符，并将所述至少两个预设病灶特征中与所述目标病灶特征相匹配的病灶特征对应的字符以第一方式区别化显示；其中，所述预设图形包括至少两个区域，一个所述区域用于显示一个所述预设病灶特征对应的字符。
  21. 根据权利要求19所述的方法，其特征在于，所述目标区域包括甲状腺区域或乳腺区域，当所述目标区域为乳腺区域时，所述预设病灶特征包括BI-RADS病灶特征，当所述目标区域为甲状腺区域时，所述预设病灶特征包括TI-RADS病灶特征。
  22. 一种超声图像分析方法，其特征在于，所述方法包括：
    获取被测对象目标区域的超声图像；
    检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
    在预设图形中显示所述病灶的目标病灶特征对应的字符，并区别化显示所述病灶的目标病灶特征中表征特定病灶状态的病灶特征对应的字符。
  23. 一种超声图像分析方法，其特征在于，所述方法包括：
    获取被测对象目标区域的超声图像；
    检测所述超声图像中的病灶，并识别所述病灶的目标病灶特征；
    在预设图形中显示所述病灶的目标病灶特征对应的字符。
  24. 根据权利要求22或23所述的方法，其特征在于，所述目标区域包括甲状腺区域或乳腺区域，当所述目标区域为乳腺区域时，所述目标病灶特征包括BI-RADS病灶特征，当所述目标区域为甲状腺区域时，所述目标病灶特征包括TI-RADS病灶特征。
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN103455821A (zh) * 2012-05-29 2013-12-18 北京三星通信技术研究有限公司 基于bi-rads的图像分析装置和方法
US20190142367A1 (en) * 2007-05-04 2019-05-16 Delphinus Medical Technologies, Inc. Patient interface system
CN111324659A (zh) * 2020-02-27 2020-06-23 西安交通大学 一种针对时序医疗数据的可视化推荐方法及系统

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20190142367A1 (en) * 2007-05-04 2019-05-16 Delphinus Medical Technologies, Inc. Patient interface system
CN103455821A (zh) * 2012-05-29 2013-12-18 北京三星通信技术研究有限公司 基于bi-rads的图像分析装置和方法
CN111324659A (zh) * 2020-02-27 2020-06-23 西安交通大学 一种针对时序医疗数据的可视化推荐方法及系统

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
"Master Thesis", 1 April 2017, SOUTHWEST JIAOTONG UNIVERSITY, CN, article ZHANG ZHIHANG: "Feature Extraction and Visualization of Ultrasonic Image Based on TI-RADS", pages: 1 - 74, XP055903350 *

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