CN114581469A

CN114581469A - Method and device for automatically extracting axes of femur and tibia of lower limb and electronic equipment

Info

Publication number: CN114581469A
Application number: CN202210130785.9A
Authority: CN
Inventors: 怀晓晨; 穆红章
Original assignee: Lingyu Yinnuo Beijing Technology Co ltd
Current assignee: Lingyu Yinnuo Beijing Technology Co ltd
Priority date: 2022-02-12
Filing date: 2022-02-12
Publication date: 2022-06-03

Abstract

The application relates to a method, a device and electronic equipment for automatically extracting axes of thighbone and shinbone of lower limb, wherein the method comprises the following steps: acquiring a full-length load original picture of double lower limbs; obtaining a target image according to the double-lower-limb full-length load original image; intercepting a femur area image and a tibia area image from a target image based on a preset interception rule; determining a femoral axis according to the femoral region image based on a preset first determination rule; determining a tibia axis according to the tibia region image based on a preset second determination rule; and marking the femoral axis and the tibial axis in the target image based on a preset reduction rule. This application has the effect of realizing quick accurate definite lower limb thighbone and shin bone axis.

Description

Method and device for automatically extracting axes of femur and tibia of lower limb and electronic equipment

Technical Field

The present application relates to the field of image processing, and in particular, to a method and an apparatus for automatically extracting axes of a femur and a tibia of a lower limb, and an electronic device.

Background

The lower limb force line is an axis passing through the hip joint, the knee joint center and the ankle joint center. The recovery of the lower limb force line basically depends on the accurate positioning of the femoral axis, in order to better match the femoral prosthesis, the anterior-posterior axis of the distal end of the femur can be used as a reliable mark of the opposite side of the rotation of the femoral prosthesis, the tibial plateau osteotomy is further accurately positioned, and the tibial axis is usually marked, so that the determination of the femoral and tibial axes of the lower limb is of great importance in the measurement process of the lower limb force line.

At present, in the X-ray full-length plate, the related measurement of the axes of the femur and the tibia of the lower limb is mainly manual measurement, and the measurement efficiency is lower by adopting a manual method.

Disclosure of Invention

In order to rapidly and accurately determine the axes of the femur and the tibia of the lower limb, the application provides a method, a device and electronic equipment for automatically extracting the axes of the femur and the tibia of the lower limb.

In a first aspect, the present application provides a method for automatically extracting the axes of a femur and a tibia of a lower limb, which adopts the following technical scheme:

a method of automatically extracting femoral and tibial axes of a lower limb, comprising:

acquiring a full-length load original picture of double lower limbs;

obtaining a target image according to the double-lower-limb full-length load original image;

intercepting a femur area image and a tibia area image from a target image based on a preset interception rule;

determining a femoral axis according to the femoral region image based on a preset first determination rule;

determining a tibia axis according to the tibia region image based on a preset second determination rule;

and marking the femoral axis and the tibial axis in the target image based on a preset reduction rule.

By adopting the technical scheme, the lower limb full-length weight bearing X-ray film is obtained, then the lower limb full-length weight bearing X-ray film is preprocessed to obtain a target image, a femur area image and a tibia area image are intercepted from the target image based on a preset intercepting rule, a femur axis is determined according to the femur area image based on a preset first determining rule after the femur area image and the tibia area image are intercepted, a tibia axis is determined according to the tibia area image based on a preset second determining rule, and then the femur axis and the tibia axis are marked in the target image based on a preset restoring rule to complete measurement of the tibia axis and the tibia axis.

Optionally, the method for obtaining the target image according to the double-lower-limb full-length load original image specifically includes:

adjusting the double-lower-limb full-length load original image according to a preset window width and a preset window level and converting the double-lower-limb full-length load original image into a JPG (joint photographic experts group) format image;

and performing image enhancement on the picture, improving the contrast ratio of the femur region and the tibia region, and obtaining a target image.

Optionally, the method for capturing the femur area image and the tibia area image from the target image based on the preset capturing rule specifically includes:

determining a position which is a first preset distance away from the short side of the target image close to the anterior superior iliac spine along the length of the target image as a first clipping position;

determining a position which is a second preset distance away from the first cutting position as a second cutting position along the length direction of the target image, wherein the distance from the first cutting position to the short edge of the target image close to the anterior superior iliac spine is smaller than the distance from the second cutting position to the short edge of the target image close to the anterior superior iliac spine;

cutting the target image from a first cutting position and a second cutting position along the width direction of the target image, wherein the area between the first cutting position and the second cutting position is a femur area image;

determining a position which is a third preset distance away from the short side of the target image close to the anterior superior iliac spine along the length direction of the target image as a third clipping position;

determining a position which is a second preset distance away from a third cutting position along the length direction of the target image as a fourth cutting position, wherein the distance from the third cutting position to the short edge of the target image close to the anterior superior iliac spine is smaller than the distance from the fourth cutting position to the short edge of the target image close to the anterior superior iliac spine;

and cutting the target image from the third cutting position and the fourth cutting position along the width direction of the target image to obtain a region between the third cutting position and the fourth cutting position as a tibia region image.

Optionally, the method for determining the femoral axis according to the femoral region image based on the first determination rule specifically includes:

determining a left femoral region and a right femoral region according to the femoral region image;

determining a femoral axis searching area according to the femoral area image based on a preset first area determination rule;

determining first contour information of the femur in the femur axis searching region based on a preset third determination rule;

determining an edge contour line of the femur according to the first contour information;

and determining the femoral axis according to the edge contour line of the femur and the boundary line of the femoral axis searching area based on a preset femoral axis determining rule, wherein the boundary line of the femoral axis searching area comprises a first boundary line and a second boundary line.

Optionally, the method for determining the edge contour line of the femur according to the first contour information specifically includes:

determining straight lines contained in the first contour information according to Hough straight line detection;

establishing a first rectangular coordinate system in the femur region image;

determining coordinates of target points on all straight lines contained in the first contour information;

and determining the edge contour line of the femur according to the coordinates of the target points on all the straight lines contained in the first contour information and the first rectangular coordinate system.

Optionally, the method for determining the femoral axis according to the edge contour line of the femur and the boundary line of the femoral axis search region based on the preset femoral axis determination rule specifically includes:

determining two intersection points of the edge contour line of the femur and a first boundary line of the femoral axis searching area;

determining a first midpoint of a line segment determined by two intersection points of an edge contour line of the femur and a first boundary line of the femur axis searching region according to a first rectangular coordinate system;

determining two intersection points of the edge contour line of the femur and a second boundary line of the femur axis searching area;

determining a second midpoint of a line segment determined by two intersection points of an edge contour line of the femur and a second boundary line of the femur axis searching area according to a first rectangular coordinate system;

and determining the straight line determined by the first midpoint and the second midpoint, namely the axis of the femur.

Optionally, the method for determining the tibial axis according to the tibial region image based on the preset second determination rule specifically includes:

determining two knee joint contours according to the tibia region image and marking the two knee joint contours to distinguish a left knee joint from a right knee joint;

determining a tibia axis searching region according to the tibia region image based on a preset second region determination rule;

determining a tibia contour of the tibia in the tibia axis searching region based on a preset fourth determination rule;

determining an edge contour line of the tibia according to the tibia contour;

and determining the tibia axis according to the boundary between the edge contour line of the tibia and the tibia axis searching region based on a preset tibia axis determining rule.

In a second aspect, the present application provides a device for automatically extracting the axes of the femur and the tibia of the lower limb, which adopts the following technical scheme:

an apparatus for automatically extracting femoral and tibial axes of a lower limb, comprising:

the acquisition module is used for acquiring a double-lower-limb full-length load original image;

the image processing module is used for obtaining a target image according to the double-lower-limb full-length load original image;

the image intercepting module is used for intercepting a femur region image and a tibia region image from the target image based on a preset intercepting rule;

the femur axis extraction module is used for determining a femur axis according to the femur region image based on a preset first determination rule;

the tibia axis extraction module is used for determining a tibia axis according to the tibia region image based on a preset second determination rule;

and the reduction module is used for marking the femoral axis and the tibial axis in the target image based on a preset reduction rule.

In a third aspect, the present application provides an electronic device, which adopts the following technical solutions:

an electronic device comprising a memory and a processor, the memory having stored thereon a computer program of a method of automatically extracting femoral and tibial axes of a lower limb, which method is loadable and executable by the processor.

In a fourth aspect, the present application provides a computer-readable storage medium, which adopts the following technical solutions:

a computer readable storage medium storing a computer program of a method of automatically extracting femoral and tibial axes of a lower limb, which can be loaded and executed by a processor.

To sum up, the application comprises the following beneficial technical effects:

the method comprises the steps of obtaining a lower limb full-length weight bearing X-ray film, preprocessing the lower limb full-length weight bearing X-ray film to obtain a target image, intercepting a femur area image and a tibia area image from the target image based on a preset intercepting rule, determining a femur axis according to the femur area image based on a preset first determining rule after intercepting the femur area image and the tibia area image, determining a tibia axis according to the tibia area image based on a preset second determining rule, marking the femur axis and the tibia axis in the target image based on a preset reducing rule to complete measurement of the tibia axis and the tibia axis, achieving automatic positioning of the tibia axis and the femur axis by the method, and achieving rapid and accurate determination of the lower limb femur axis and the tibia axis.

Drawings

Fig. 1 is a flowchart of a method for automatically extracting femoral and tibial axes of a lower limb according to the present embodiment.

Fig. 2 is a target image of the present embodiment.

Fig. 3 is a schematic view of the right femoral region of fig. 2.

Fig. 4 is a schematic diagram of fig. 3 after hough line detection and establishment of a first rectangular coordinate system.

Fig. 5 is an image of the right tibial leg area of the present embodiment.

Fig. 6 is a schematic diagram of fig. 5 after hough line detection.

Fig. 7 is a schematic diagram of the target image after adding the third rectangular coordinate system and the fourth rectangular coordinate system.

Fig. 8 is a block diagram of the structure of the device for automatically extracting the femoral and tibial axes of the lower limb provided by the application.

Fig. 9 is a schematic structural diagram of an electronic device provided in the present application.

Description of reference numerals: 1. a femoral region image; 2. a tibial region image; 200. a device for automatically extracting the axes of the femur and the tibia of the lower limb; 201. an acquisition module; 202. an image processing module; 203. an image intercepting module; 204. a femoral axis determination module; 205. a tibial axis determination module; 206. a reduction module; 301. a CPU; 302. a ROM; 303. a RAM; 304. an I/O interface; 305. an input section; 306. an output section; 307. a storage section; 308. a communication section; 309. a driver; 310. a removable media.

Detailed Description

In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.

In addition, the term "and/or" herein is only one kind of association relationship describing an associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.

All terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs unless specifically defined otherwise. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

The embodiment of the application discloses a method for automatically extracting the axes of a femur and a tibia of a lower limb. Referring to fig. 1, the method for automatically extracting femoral and tibial axes of a lower limb comprises:

s101: and obtaining a full-length load original picture of the double lower limbs.

Specifically, the total length of the lower limbs is from the anterior superior iliac spine to the lower medial malleolus, the X-ray film of the total length load of the double lower limbs of the human body is shot by an X-ray machine perspective instrument, the original image of the total length load of the double lower limbs of the human body is transmitted to the server and stored in the database, and the server can call the original image of the total length load of the double lower limbs of the human body from the database when needed.

S102: and obtaining a target image according to the double-lower-limb full-length load original image.

Specifically, the double-lower-limb full-length load original image is a picture in a dcm format, the obtained double-lower-limb full-length sheet load original image is adjusted according to a preset window width and a preset window level, the preset window width is 600 in the embodiment, the window level is 1800, the obtained double-lower-limb full-length sheet load original image is adjusted according to the preset window width and the preset window level, the double-lower-limb full-length sheet load original image is converted into a picture in a JPG format, the picture is processed by an image enhancement technology to improve the contrast of a femur region and a tibia region, and thus a target image is obtained, and pixels of the target image are 1500 pixels in the transverse direction and 4000 pixels in the longitudinal direction.

S103: based on a preset interception rule, the femur region image 1 and the tibia region image 2 are intercepted from the target image.

Specifically, the target image is identified through image identification to determine the anterior superior iliac spine and the lower edge of the medial malleolus in the target image, the target image is rectangular as a whole, the distance from two short sides of the target image to the anterior superior iliac spine is compared, the position which is away from the short side close to the anterior superior iliac spine in the target image by a first preset distance is selected as a first clipping position on the long side of the target image, the position which is away from the first clipping position by a second preset distance is selected as a second clipping position on the long side of the target image, and the distance from the first clipping position to the short side close to the anterior superior iliac spine in the target image is smaller than the distance from the second clipping position to the short side close to the anterior superior iliac spine in the target image.

In this embodiment, the first preset distance is 200 pixels, the second preset distance is the length of the short side of the target image, after the first cropping position and the second cropping position are determined, the target image is cropped along the direction of the short side of the target image from the first cropping position and the second cropping position, respectively, and an area between the first cropping position and the second cropping position is a femur area image 1; and determining a boundary where the first cutting position is located in the femur region image 1 and is parallel to the short side of the target image as a first boundary line, and determining a boundary where the second cutting position is located in the femur region image 1 and is parallel to the short side of the target image as a second boundary line.

Selecting one half of the long edge of the target image as a third clipping position on the long edge of the target image, selecting a position which is a second preset distance away from the third clipping position as a fourth clipping position on the long edge of the target image, wherein the distance from the fourth clipping position to the short edge of the target image close to the anterior superior iliac spine is smaller than the distance from the third clipping position to the short edge of the target image close to the anterior superior iliac spine, clipping the target image along the direction of the short edge of the target image from the third clipping position and the fourth clipping position respectively after the third clipping position and the fourth clipping position are determined, and the region between the third clipping position and the fourth clipping position is a tibia region image 2; and determining the boundary where the third cropping position is located in the tibial region image 2 and is parallel to the short side of the target image as a third boundary line, and determining the boundary where the fourth cropping position is located in the tibial region image 2 and is parallel to the short side of the target image as a fourth boundary line.

Fig. 2 shows the process of cropping the femur area image 1 and the tibia area image.

S104: determining a femoral axis according to the femoral region image 1 based on a preset first determination rule.

Specifically, a femur region image 1 is detected through a YOLO detection model to determine a left femur region and a right femur region, YOLO is an end-to-end target detection algorithm, an RCNN target detection series does not need to be extracted in advance, category, confidence and coordinate positions can be output through a network, the detection speed is high, the left femur region and the right femur region can be determined through detecting the femur region image 1 through the YOLO detection model, and after the left femur region and the right femur region are determined, the left femur region and the right femur region are respectively marked to distinguish the left femur region and the right femur region.

Determining a femoral axis searching region in the femoral region image 1 based on a preset first region determination rule, in this embodiment, the first region determination rule is: the cut femur region image 1 is subjected to binarization processing, the contour of the femur in the femur region image 1 after binarization processing is more obvious, the femur region image 1 after binarization processing is trisected along the vertical direction, and labeling a first boundary line and a second boundary line, the first boundary line and the second boundary line having equal lengths and equal to the length of the short side of the target image, the region between the first boundary line and the second boundary line being a femoral axis search region, and performing contour extraction on the determined femoral axis searching area through a preset contour extraction algorithm, determining the contour of the left femoral area and the contour of the right femoral area, and determining that intersection contour lines exist between the first boundary line and the second boundary line in the plurality of contour lines of the left femoral area and the plurality of contour lines of the right femoral area, so as to determine first contour information of the left femur and first contour information of the right femur.

Determining the edge contour line of the femur according to the first contour information, firstly establishing a first rectangular coordinate system by taking an end point of a second boundary line of the femur region image 1 close to the left femur as an origin, wherein the direction pointing to the first boundary line is the positive direction of a Y axis, the direction pointing to the left femur is the positive direction of an X axis, determining a plurality of straight lines contained in the first contour information of the right femur through Hough line detection, determining coordinates of each straight line, the first boundary line and the second boundary line in the first rectangular coordinate system, and determining two straight lines at the outermost side in the first contour information of the right femur, namely the edge contour line of the right femur.

It can be understood that the method for determining the two outermost straight lines in the first contour information of the right femur is as follows: randomly selecting one straight line in the first contour information as a reference line, comparing all the other straight lines contained in the first contour information of the right femur with the reference line, judging that the straight line is positioned on the left side of the reference line when the abscissa of the intersection point of the certain straight line with the first boundary line and the second boundary line is smaller than the abscissa of any intersection point of the reference line with the first boundary line and the second boundary line, putting the straight line into a set, repeating the process on the straight lines in the set, putting the selected straight line into a set again until the set is an empty set, and determining that the reference line at the moment is the leftmost edge contour line; when the rightmost edge contour line is determined, one straight line in the first contour information is arbitrarily selected as a reference line, all the other straight lines contained in the first contour information of the right femur are compared with the reference line, when the intersection abscissa of a certain straight line and the first boundary line and the intersection abscissa of a certain straight line and the second boundary line are both larger than the intersection abscissa of the reference line and the first boundary line and the intersection abscissa of the certain straight line and the second boundary line, the straight line is judged to be positioned on the right side of the reference line, the straight lines are put into a set, the process is repeated for the straight lines in the set, the selected straight lines are put into a set again, and the reference line at the moment is determined as the rightmost edge contour line until the set is empty.

After determining the leftmost edge contour line and the rightmost edge contour line of the right femur, determining the intersection point of the leftmost edge contour line and the first boundary line and the intersection point of the rightmost edge contour line and the first boundary line, and determining a first midpoint of a line segment determined by the two intersection points; determining the intersection point of the leftmost edge contour line and the second boundary line, the intersection point of the rightmost edge contour line and the second boundary line, and determining the second midpoint of the line segment determined by the two intersection points; the straight line defined by the first midpoint and the second midpoint is the femoral axis. Fig. 3 and 4 show the process of determining the axis of the right femur, and the determination of the axis of the left femur and the axis of the right femur are the same, which will not be described in detail herein.

S105: the tibial axis is determined from the tibial region image 2 based on a preset second determination rule.

Specifically, the tibia region image 2 is processed by OpenCV to determine a contour of the left knee joint and a contour of the right knee joint, the contour of the left knee joint and the contour of the right knee joint are determined according to the contours of the left knee joint, and the left knee joint region and the right knee joint region are respectively marked to distinguish the left leg from the right leg.

The tibia axis extraction region is determined by a preset second region determination rule, specifically, in this embodiment, the second region determination rule is: setting a global threshold value as 200 to carry out binarization processing on the tibia region image 2, wherein the contour of the tibia in the tibia region image 2 after binarization is more obvious, trisecting the tibia region image 2 after binarization processing along the vertical direction, and labeling a third boundary line and a fourth boundary line, wherein the third boundary line, the fourth boundary line, the third boundary line and the fourth boundary line are parallel to each other, the distance between the third boundary line and the third boundary line is equal to the distance between the fourth boundary line and the fourth boundary line, and the area between the third boundary line and the fourth boundary line is a tibia axis searching area, and performing contour extraction on the determined tibial axis searching area through a preset contour extraction algorithm, determining the contour line of the left leg and the contour line of the right leg in the tibial axis searching area, and determining contour lines which are intersected with the third boundary line and the fourth boundary line in the plurality of contour lines of the left leg and the plurality of contour lines of the right leg.

Establishing a second rectangular coordinate system by taking the end point of the fourth boundary line close to the right leg as an origin, calculating the horizontal distance between two end points of the fourth boundary line and the right leg, wherein the end point close to the horizontal distance of the right leg is the end point close to the right leg, the direction pointing to the third boundary line is the positive direction of the Y axis, the direction pointing to the left leg is the positive direction of the X axis, and determining straight lines existing in contour lines of which a plurality of contour lines of the left leg are intersected with the third boundary line and the fourth boundary line through Hough straight line detection so as to determine second contour information of the left leg; and determining straight lines existing in contour lines intersecting both the third boundary line and the fourth boundary line in the plurality of contour lines of the right leg through Hough straight line detection, thereby determining second contour information of the right leg.

In a second rectangular coordinate system, the horizontal coordinate of any point in the fibula area of the left leg is larger than the horizontal coordinate of any point in the tibia area; in the second rectangular coordinate system, the abscissa of any point in the fibula region of the right leg is smaller than the abscissa of any point in the tibia region, whether the detected leg is the right leg or the left leg can be judged according to the mark of the left knee joint region and the mark of the right knee joint region, then the coordinates of each point in each contour included in the second contour information are determined, when the detected leg is the left leg, the region surrounded by the two contours with the smallest abscissas in the second contour information of the left leg is determined to be the tibia region of the left leg, so that the tibia contour of the left leg is determined, when the detected leg is the right leg, the region surrounded by the two contours with the largest abscissas in the second contour information of the right leg is determined to be the tibia region of the right leg, and therefore the tibia contour of the right leg is determined.

After the tibia contour is determined, the contour edge line of the tibia is determined according to the tibia contour, the determination method of the contour edge line of the tibia is the same as the determination method of the contour edge line of the femur, which is not described in detail herein,

after the leftmost edge contour line and the rightmost edge contour line of the tibia are determined, determining the intersection point of the leftmost edge contour line and the third boundary line, the intersection point of the rightmost edge contour line and the third boundary line, and determining the third midpoint of a line segment determined by the two intersection points; determining the intersection point of the leftmost edge contour line and the fourth boundary line, the intersection point of the rightmost edge contour line and the fourth boundary line, and determining the fourth midpoint of the line segment determined by the two intersection points; and the straight line defined by the third midpoint and the fourth midpoint is the tibial axis. Fig. 5 and 6 show the determination of the right leg tibial axis.

S106: marking the femoral axis and the tibial axis in the target image based on a preset reduction rule.

Specifically, after the femoral axis and the tibial axis are determined, a raw target image is obtained, a first boundary line, a second boundary line, a third boundary line and a fourth boundary line are determined on the target image according to the process, a third rectangular coordinate system is established in the raw target image according to the establishing method of the first rectangular coordinate system, a fourth rectangular coordinate system is established in the target image according to the establishing method of the second rectangular coordinate system, when the femoral region image 1 in the target image is replaced by the femoral region image 1 marked with the femoral axis, the first rectangular coordinate system and the third rectangular coordinate system are overlapped to realize the determination of the position, and then the replacement is completed through image processing; when the tibia region image 2 marked with the tibia axis is used for replacing the femur region image 1 in the target image, the second rectangular coordinate system and the fourth rectangular coordinate system are overlapped to determine the position, and then the replacement is completed through image processing; the image processing is a routine measure for those skilled in the art and will not be described in too much detail herein. Fig. 7 shows a process of establishing a third rectangular coordinate system and a fourth rectangular coordinate system in the original target image.

The embodiment of the application discloses a device for automatically extracting the axes of thighbone and shinbone of lower limb. Referring to fig. 8, the apparatus 200 for automatically extracting femoral and tibial axes of a lower limb includes:

an acquisition module 201, configured to acquire a full-length load original diagram of the double lower limbs;

the image processing module 202 is used for obtaining a target image according to the double-lower-limb full-length load original image;

the image intercepting module 203 is used for intercepting a femur region image 1 and a tibia region image 2 from a target image based on a preset intercepting rule;

a femoral axis determining module 204, configured to determine a femoral axis according to the femoral region image 1 based on a preset first determination rule;

a tibial axis determining module 205, configured to determine a tibial axis according to the tibial region image 2 based on a preset second determination rule;

and the reduction module 206 is used for marking the femoral axis and the tibial axis in the target image based on a preset reduction rule.

It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the described module may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.

The embodiment of the application discloses an electronic device. Referring to fig. 9, the electronic apparatus includes a Central Processing Unit (CPU)301 that can perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)302 or a program loaded from a storage section 307 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data necessary for system operation are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other via a bus. An input/output (I/O) interface 304 is also connected to the bus.

The following components are connected to the I/O interface 304: an input section 305 including a keyboard, a mouse, and the like; an output section 306 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage portion 307 including a hard disk and the like; and a communication section 308 including a network interface card such as a LAN card, a modem, or the like. The communication section 308 performs communication processing via a network such as the internet. Drivers 309 are also connected to the I/O interface 304 as needed. A removable medium 310 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 309 as necessary, so that a computer program read out therefrom is mounted into the storage section 307 as necessary.

In particular, according to embodiments of the present application, the process described above with reference to the flowchart of fig. 1 may be implemented as a computer software program. For example, embodiments of the present application include a computer program product comprising a computer program embodied on a machine-readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 308 and/or installed from the removable medium 310. The above-described functions defined in the apparatus of the present application are executed when the computer program is executed by the Central Processing Unit (CPU) 301.

It should be noted that the computer readable medium shown in the present application may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.

The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The foregoing description is only exemplary of the preferred embodiments of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the application referred to in the present application is not limited to the embodiments with a particular combination of the above-mentioned features, but also encompasses other embodiments with any combination of the above-mentioned features or their equivalents without departing from the spirit of the application. For example, the above features may be replaced with (but not limited to) features having similar functions as those described in this application.

Claims

1. A method, a device and electronic equipment for automatically extracting the axes of a femur and a tibia of a lower limb are characterized in that: the method comprises the following steps:

acquiring a full-length load original picture of the double lower limbs;

intercepting a femur area image and a tibia area image from a target image based on a preset intercepting rule;

determining a femur axis according to the femur region image based on a preset first determination rule;

2. The method for automatic extraction of femoral and tibial axes of a lower extremity of claim 1, wherein: the method for obtaining the target image according to the double-lower-limb full-length load original image specifically comprises the following steps:

3. The method for automatic extraction of femoral and tibial axes of a lower extremity of claim 1, wherein: the method for capturing the femur area image and the tibia area image from the target image based on the preset capturing rule specifically comprises the following steps:

cutting the target image from the first cutting position and the second cutting position along the width direction of the target image, wherein the area between the first cutting position and the second cutting position is a femur area image;

determining a position which is a second preset distance away from a third cutting position to be a fourth cutting position along the length direction of the target image, wherein the distance from the third cutting position to the short side of the target image close to the anterior superior iliac spine is smaller than the distance from the fourth cutting position to the short side of the target image close to the anterior superior iliac spine;

and cutting the target image from the third cutting position and the fourth cutting position along the width direction of the target image to obtain a region between the third cutting position and the fourth cutting position, namely a tibia region image.

4. The method for automatic extraction of femoral and tibial axes of a lower extremity of claim 1, wherein: the method for determining the femoral axis according to the femoral region image based on the first determination rule specifically comprises the following steps:

5. The method of automatically extracting femoral and tibial axes of a lower limb of claim 4, wherein: the method for determining the edge contour line of the femur according to the first contour information specifically comprises the following steps:

determining a straight line contained in the first contour information according to Hough straight line detection;

establishing a first rectangular coordinate system in the femur region image;

6. The method of automatically extracting femoral and tibial axes of a lower limb of claim 4, wherein: the method for determining the femoral axis according to the edge contour line of the femur and the boundary line of the femoral axis searching area based on the preset femoral axis determining rule specifically comprises the following steps:

and determining a straight line determined by the first midpoint and the second midpoint, namely the femoral axis.

7. The method for automatic extraction of femoral and tibial axes of a lower extremity of claim 1, wherein: the method for determining the tibia axis according to the tibia region image based on the preset second determination rule specifically includes:

determining two knee joint contours according to the tibia region image and marking the two knee joint contours so as to distinguish a left knee joint from a right knee joint;

determining an edge contour line of the tibia according to the tibia contour;

and determining the tibial axis according to the boundary between the edge contour line of the tibia and the tibial axis searching region based on a preset tibial axis determining rule.

8. The utility model provides an automatic draw device of low limbs thighbone and shin bone axis which characterized in that: the method comprises the following steps:

the acquisition module (201) is used for acquiring a double-lower limb full-length load original graph;

the image processing module (202) is used for obtaining a target image according to the double-lower-limb full-length load original image;

the image intercepting module (203) is used for intercepting a femur region image and a tibia region image from the target image based on a preset intercepting rule;

a femoral axis determination module (204) for determining a femoral axis from the femoral region image based on a preset first determination rule;

a tibial axis determining module (205) for determining a tibial axis from the tibial region image based on a preset second determination rule;

and the reduction module (206) is used for marking the femoral axis and the tibial axis in the target image based on a preset reduction rule.

9. An electronic device, characterized in that: comprising a memory and a processor, said memory having stored thereon a computer program which can be loaded by the processor and which performs the method of any of claims 1 to 7.

10. A computer-readable storage medium, in which a computer program is stored which can be loaded by a processor and which executes the method of any one of claims 1 to 7.