CN220961250U - Analysis system for automatic detection and identification of biological smear - Google Patents

Abstract

The utility model discloses an analysis system for automatic detection and identification of biological smears, which is used for microscopic, photographing, identification and analysis of stained biological smears and provides the quantity or content of cells, proteins or other components. The analysis system comprises a first module, a second module and a third module, wherein the first module comprises an automatic moving part and a microscopic imaging photographing part, and the second module comprises computer hardware, a relay and a PLC (programmable logic controller) and is used for controlling the first module, identifying and analyzing smear photos.

Description

Analysis system for automatic detection and identification of biological smear

Technical Field

The utility model relates to microscopic imaging photographing and image recognition analysis, in particular to a full-automatic smear microscopic imaging photographing system and an image recognition computer system.

Background

A microscopic imaging system, including a microscope, is an optical instrument composed of a lens or a combination of several lenses, and is mainly used for magnifying tiny objects into an instrument which can be seen by the naked human eye. Microscopic imaging is divided into optical microscopic imaging and electron microscopic imaging (electron microscope). The conventional microscopic imaging device for industries such as medical treatment is simple in structure, low in automation degree, low in imaging speed, mainly operated manually and low in working efficiency. At present, some full-automatic microscope imaging devices exist in the market, but the manufacturing cost is high. Therefore, the popularity of automated microscopic imaging techniques remains to be improved and developed.

Various methods exist for cell and protein and other component analysis, including visual and/or automated examination via light or fluorescence microscopy imaging, including obtaining information about cell lineages, maturation stage, cell count, protein and other component content in a sample.

For blood cells, these methods are typically used to differentiate and/or identify individual blood cells in a sample, count individual blood cells in a sample, and in some cases estimate the size of individual blood cells in a sample. Blood smears can be made and examined if these results (e.g., abnormal whole blood count (CBC) results) indicate the presence of abnormal White Blood Cells (WBCs), red Blood Cells (RBCs), and/or platelets, or if there is a reasonable suspicion of the presence of abnormal cells. Blood smears are often examined to classify and/or identify conditions affecting one or more blood cell types and to monitor individuals undergoing treatment for those conditions. There are many diseases, disorders, and defects that can affect the number and type of blood cells produced, their function, and their longevity. Examples include anemia, myeloproliferative neoplasms, myelopathy, and leukemia.

For proteins and their sugar chains, these methods are generally used to distinguish and/or identify normal and/or abnormal proteins and/or abnormal sugar chains of proteins on a smear, and in some cases to estimate the content of normal and/or abnormal proteins and/or abnormal sugar chain glycoproteins on a smear, using a specific staining solution. The levels of these normal, abnormal proteins, and/or abnormal glycoprotein chains are typically examined to classify and/or identify individuals who affect one or more disorders and to monitor individuals undergoing treatment for such disorders. There are a number of diseases, disorders, and defects that can affect the amount and type of normal and/or abnormal protein produced. Examples include male infertility and sperm nucleoprotein, solid tumors and abnormal glycoprotein (TAP).

Traditional methods involve thinly dispensing a drop of blood or semen onto a slide, followed by staining, and a qualified laboratory personnel manually visually inspecting the stained smear using a microscope. In recent years, image recognition automated digital systems have begun to be used to help analyze various smears more efficiently.

With the continuous enhancement of the computing power of a computer chip, a depth learning algorithm based on statistics (statistics) starts from about 2015, and the depth learning algorithm gradually exceeds the traditional image recognition algorithm in the field of image recognition, so that the accuracy of an image recognition technology is greatly improved. Through carefully choosing and adjusting relevant parameters of the deep learning image recognition algorithm, the technology of the deep learning image recognition algorithm can exceed that of manual naked eyes and observation and analysis by experience. The deep learning algorithm with practical effect and necessary hardware, including graphic cards (GPUs) of the inflight corporation, are only present in a few years, and because the deep learning algorithm relates to the special theory of the mathematical field and because the algorithm parameter selection and debugging are very complex, no economical and practical product exists in the market, particularly in the medical field.

Disclosure of utility model

Aspects of the present disclosure include providing a biological smear automatic detection recognition and digital analysis system that includes a first module including an automatic movement component, i.e., a component that automatically changes the relative position of a smear to a microscopic imaging camera component, and an automatic microscopic imaging camera component. The system also includes a second module including computer hardware and other components; examples of computer hardware components include, an english-weidag display card for running deep learning image recognition software; other component examples include programmable controllers (PLCs), relays, manual switches, sensors for controlling the first module, automatic movement, automatic shooting, artificial intelligence recognition, analysis of smear photographs, and statistical analysis;

Drawings

FIG. 1 illustrates a side view of a first module of an analysis system according to the present disclosure including a stage assembly and a microscopic imaging camera assembly.

Fig. 2 shows a side view of another orientation of a first module of an analysis system according to the present disclosure including a stage assembly and a microscopic imaging camera assembly.

Fig. 3 illustrates a side view of a microscopic imaging camera component of an analysis system in accordance with the present disclosure.

FIG. 4 illustrates a side view of a stage component of an analysis system according to the present disclosure.

FIG. 5 illustrates a side view of a motor and stage interface layer and connecting parts of a stage assembly of an analysis system according to the present disclosure.

FIG. 6 illustrates a side view of a motor and stage interface feature of an analysis system according to the present disclosure.

FIG. 7 illustrates a side view of another orientation of a motor and stage interface feature of an analysis system according to the present disclosure.

FIG. 8 illustrates a host computer according to the present disclosure.

Detailed Description

Aspects of the present disclosure include providing an automated biological smear detection recognition and analysis system that includes a first module including an automated moving component, i.e., a component that automatically changes the relative position of a smear and a microscopic imaging camera component, the automated microscopic imaging camera component. The system also includes a second module including computer hardware and other components; examples of computer hardware components include, an english-weidag display card for running deep learning image recognition software; other component examples include programmable controllers (PLCs), relays, manual switches, sensors for controlling the first module, taking, identifying, analyzing smear photographs, and statistical analysis.

Before the present system is described in more detail, it is to be understood that this disclosure is not limited to particular embodiments described, as such may, of course, vary. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to be limiting, since the scope of the present invention will be limited only by the terms of the appended claims.

Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs.

It will be apparent to those of skill in the art upon reading this disclosure that each of the individual, discrete components and features described and illustrated herein may be readily separated from or combined with any of the other several features without departing from the scope or spirit of the present systems and methods. Any of the recited methods may be performed in the recited order of events or in any other order that is logically possible.

Aspects of the present disclosure include a smear analysis system. The analysis system may be adapted to perform a variety of analyses of interest, as well as combinations thereof. In certain aspects, the analysis system is automated, meaning that the system is capable of performing smear analysis without user intervention.

Automated smear analysis systems are designed to perform automated semen, blood tests. The system may be expandable and process whole blood and body fluid samples to produce hematology results containing relevant parameter information. The system may perform tests on whole blood samples and body fluids to determine the counts of Red Blood Cells (RBCs), platelets (PLTs) and White Blood Cells (WBCs), measure hemoglobin (Hgb), count immature red blood cells, normal/abnormal proteins and their content, as well as any other blood or body fluid parameter of interest.

The system may be used as an automated semen, a hematology analysis system alone, or as part of an integrated system (e.g., configured in various components) with one or more other such automated hematology analysis systems, or a combination thereof.

An example of the stage component and the microscopic imaging photographing component of the first module is shown in fig. 1. In this example configuration, the number of components,

Reference numeral 101 denotes a rectangular component which is fixed to the stage intermediate layer 106 side and is connected to a motor bracket 117;

102 is a base, shared by the stage component and the microscopic imaging photographing component;

103 is an LED lamp, fixed on the base 102;

104 is a condensing lens, which is fixed in the hole on the stage lower layer 122;

105 is an objective lens fixed to the lower end of the lens barrel 111;

106 is an intermediate layer of the stage;

107 is a smear holder placed on top of the stage upper layer 108;

108 is the stage upper layer;

109 is a groove on one side of the smear holder 107, corresponding to a groove 110 on the other side of the smear holder 107, for placing a smear to be detected;

110 is a groove on one side of the smear frame 107, corresponding to the groove 109 on the other side of the smear frame 107, for placing the smear to be detected;

Reference numeral 111 denotes a lens barrel, the lower end of which is connected to the objective lens 105, and the upper end of which is connected to the camera 112;

112 is a camera connected to the upper end of the lens barrel 111; an interface for connecting an output line of the camera is arranged on the camera;

Reference numeral 113 denotes a first barrel holder, which is coupled to the vertical arm 116 via another component;

reference numeral 114 denotes a first a-type worm, which is connected to a rotation shaft of a first motor 119;

reference numeral 115 denotes a first worm wheel which is driven by the first a-type worm 114 and is coupled to a knob shaft for moving the stage forward and backward;

116 is a vertical arm;

Reference numeral 117 denotes a motor bracket, which is a special-shaped part with subsidence on both sides, and is connected to the link 101, the link crossing the stage, and the first motor 119 and the second motor 118 are fixed;

118 is a second motor, fixed in the sedimentation of 117;

Reference numeral 119 denotes a first motor fixed in the sedimentation of 117;

reference numeral 120 denotes a first stage carrier, which is fixed to the base 102 and is coupled to a third stage carrier 121;

121 is a third stage carrier, which is fixed to the base 102, is coupled to the first stage carrier 120, and supports the stage lower layer 122;

reference numeral 122 denotes a stage lower layer, which connects the stage holders two and three;

an example of the stage component and the microscopic imaging photographing component of the first module is shown in fig. 2. In this example configuration, the number of components,

Reference numeral 201 denotes a third worm wheel which drives an L-shaped worm 203 positioned in the center thereof and is driven by a third a-shaped worm 202;

reference numeral 202 denotes a third a-type worm, which is coupled to a rotation shaft of a third motor 225 to drive a third turbine 201;

Reference numeral 203 denotes an L-shaped worm, the center axis of which is aligned with the center axis of the third worm wheel 201, and drives the fourth worm wheel 206;

204 is an L-shaped worm support fixed on the base 222 for supporting the front end of the L-shaped worm;

205 is a vertical arm knob stem, the central axis of which is on a straight line with the central axis of the fourth turbine 206, passing through the center of the fourth turbine 206;

a fourth turbine 206 connected to the knob rod 205 of the vertical arm 208;

reference numeral 207 denotes a first stage carrier, which is fixed to the base 222 and connects the second stage carrier 223 and the third stage carrier;

208 are vertical arms, 116 in fig. 1;

209 is the second motor, 118 in fig. 1;

210 is the first motor, 119 in fig. 1;

211 is a barrel holder one, 113 in fig. 1;

212 is a camera, 112 in fig. 1;

213 is a lens barrel, 111 in fig. 1;

214 is a smear holder, 107 in FIG. 1;

215 is the objective lens, 105 in fig. 1;

216 is a collection optic, 104 in FIG. 1;

217 is a side recess of the smear holder 214, 109 in FIG. 1;

218 is the stage upper layer, 108 in fig. 1;

219 is the stage intermediate layer, 106 in FIG. 1;

220 is a profile part that is coupled to 117 in fig. 1 by a link 224 that spans the stage, a coupling 228;

221 is an LED lamp, 103 in fig. 1;

222 is the base, 102 in fig. 1;

223 is stage carrier two, link stage carrier one 207, support the stage lower layer;

224 is a link across the stage, link 220 and 117 in fig. 1;

Reference numeral 225 denotes a third motor, which is fixed to a motor bracket 226, and which is coupled to the motor shaft 202;

226 is a motor bracket for fixing the third motor 225 to the motor base 227;

227 is a motor stand, secured to the base 222;

228 is a rectangular component fixed to the stage interlayer 219 side, and connected 220;

An example of a microscopic imaging camera of the first module is shown in fig. 3. In this example configuration, the number of components,

301 Is the motor mount, 226 in fig. 2;

302 is a third motor, 225 in fig. 2;

303 is the motor station, 227 in fig. 2;

304 is an L-shaped worm support, 204 in fig. 2;

305 is 206 in fig. 2;

306 is 208 in fig. 2;

Reference numeral 307 denotes a vertical arm slider, which is provided inside the vertical arm 208;

reference numeral 308 denotes a second barrel holder, which connects the first barrel holder 310 and the arm slider 307;

309 is a camera, 212 in fig. 2;

310 is the first barrel holder, 211 in fig. 2;

311 is a lens barrel, 213 in fig. 2;

312 is the objective lens, 215 in fig. 2;

reference numeral 313 denotes a condenser, 216 in fig. 2;

314 are LED lamps, 221 in fig. 2;

315 is the base, 222 in fig. 2;

316 is a knob of LED lamp 314;

317 is a third type a worm, 202 in fig. 2;

318 is an L-shaped worm, 203 in fig. 2;

319 is a third turbine, 202 in fig. 2;

320 is a vertical arm slider 307;

an example of the stage components of the first module is shown in fig. 4. In this example configuration, the number of components,

401 Is 207 in fig. 2;

402 is the subsidence on 401, supporting L-worm 203;

403 is a link across the stage, 224 in FIG. 2;

404 is 101 in fig. 1;

405 is 117 in fig. 1;

Reference numeral 406 denotes a second a-type worm, which is connected to a motor shaft of a second motor 407;

407 is a second motor, 209 in fig. 2;

408 is the first motor, 210 in fig. 2;

409 is the first turbine, 115 in fig. 1;

410 is a first type a worm, 114 in fig. 1;

411 is the stage upper layer, 218 in FIG. 2;

412 is 122 in fig. 1;

413 is 214 in fig. 2;

414 is 217 in FIG. 2;

415 is the stage interlayer, 219 in FIG. 2;

416 is 228 in fig. 2;

417 is 220 in fig. 2;

418 is an LED lamp, 221 in fig. 2;

419 is 223 in fig. 2;

420 is the base, 222 in fig. 2;

Fig. 5 shows an example of a stage intermediate layer, a motor, and a coupling portion thereof in the stage member of the first module. In this example configuration, the number of components,

501 Is 416 in fig. 4;

502 is 403 in fig. 4;

503 is 404 in fig. 4;

504 is 405 in fig. 4;

505 is 406 in fig. 4;

506 is 407 in fig. 4;

507 is 408 in fig. 4;

508 is 409 in fig. 4;

509 is 410 in fig. 4;

510 is a second turbine, which drives the stage to move the knob rod in the left-right direction, the central axis is in a straight line with the central axis of the stage knob rod;

511 is 415 in fig. 4;

512 is 417 in fig. 4;

513 is 512 upper screw holes, connecting 501;

514 is 512 upper screw holes, join 502;

fig. 6 shows an example of parts of the stage intermediate layer, the motor, and the coupling portion thereof, and the motor bracket in the stage member of the first module. In this example configuration, the number of components,

601 Are screw holes for fixing the motor, and two groups of screw holes are 12, 6 groups of screw holes are respectively distributed on a motor bracket 602 in a regular hexagon shape;

602 is a motor mount, 504 in fig. 5;

603. Reference numeral 604 denotes through holes for passing through the motor shaft, 2 in total, and distributed in the motor bracket 602;

605 is a sink one for accommodating stage intermediate layer 511;

606 are screw holes, connecting 501, 4 total;

607 is a screw hole, join 502;

Fig. 7 shows an example of parts of the stage intermediate layer, the motor, and the coupling portion thereof, and the motor bracket in the stage member of the first module. In this example configuration, the number of components,

701 Is Settlement one, 605 in FIG. 6;

702 is 601 in fig. 6;

703 is a second sedimentation for accommodating the first motor 507;

704 is the motor mount, 504 in fig. 5;

705 is 603 in fig. 6;

706 is 604 in fig. 6;

707 is 601 in fig. 6;

708 is a third sedimentation for accommodating the second motor 506;

709 is 607 in FIG. 6;

710 is 606 in fig. 6.

A host computer is shown in fig. 8. In this example configuration, the number of components,

901 Is a computer mainframe housing;

902 is a power button;

903. 904, 905 are data line interfaces; the data lines include camera output lines, PLC control lines, etc.;

906 is a restart button;

The automated smear analysis system disclosed in the present utility model is suitable for automated processing of semen, blood and body fluid samples for hematological analysis.

The exemplification and exemplary detailed description of the present disclosure, including examples in the claims, is intended and intended only to demonstrate the feasibility of the present disclosure, embody the spirit of the claims, facilitate the reader's clear understanding of the present utility model, and not to limit the scope of any claims of the present utility model. It will be apparent to those skilled in the art that any changes and modifications may be made to the utility model without departing from the spirit or scope of the appended claims.

Thus, the above Wen Jinjin illustrates the principles of the present utility model. It will thus be appreciated that those skilled in the art will be able to devise various arrangements which, although not explicitly described or shown herein, embody the principles of the utility model and are still within its spirit and scope.

Furthermore, all examples and conditional language of the disclosure, including the examples in the appended claims, are intended to aid the reader in understanding the principles of the utility model and the concepts contributed by the inventor to furthering the art, and are to be construed as being without limitation to such specifically recited examples.

Furthermore, all statements herein reciting principles, aspects, and embodiments of the utility model, as well as specific examples thereof, are intended to encompass both structural and functional equivalents thereof. Such equivalents include both currently known equivalents as well as equivalents developed in the future, i.e., any elements that perform the same function, regardless of structure, as well as derived functions. Accordingly, the scope of the utility model is not limited to the examples shown and described herein. Rather, the scope and spirit of the utility model is to be construed solely by the appended claims.

Claims (4)

1. An analysis system for automated detection and identification of biological smears, comprising:

The first module comprises an automatic moving part, a stage and a plane movement control part thereof, and an automatic microscopic imaging shooting part, wherein the automatic moving part comprises a part for automatically changing the relative positions of the smear and the microscopic imaging shooting part; and

The second module comprises computer hardware; examples of computer hardware components include a graphics card (GPU), examples of which include an inflight graphics card, for running deep learning image recognition software and its "deep learning algorithm training"; examples of components also include a programmable controller (PLC), a sensor for controlling the first module, taking, identifying, analyzing smear photographs;

Wherein the first and second modules are positioned adjacent to each other such that the first module connects the second module through a data line;

Examples of the components for automatically changing the relative positions of the smear and the imaging and photographing component include one or more stage brackets, one or more motors, one or more A-type worms, one or more turbines, one or more motor brackets and one or more sensors;

Examples of the components include one or more LED lamps, one or more condensing lenses, one or more objective lenses, one or more lens barrels, one or more cameras and output lines thereof, one or more lens barrel supports, one or more microscope stand arms, one or more motors, one or more motor platforms, one or more turbines, one or more L-shaped worms, one or more A-shaped worms, one or more worm supports, one or more relays and one or more PLCs.

2. An analysis system for automated biological smear detection and identification as claimed in claim 1, wherein the first module example includes two motors fixed to the stage by a motor mount; the two motors respectively drive the objective table to move back and forth and left and right through an A-type worm and a turbine; the smear is placed on the stage and moves with the stage.

3. An analysis system for automated biological smear detection and identification as claimed in claim 1, wherein the first module includes a link connecting the stage to two motor supports via a link spanning the stage, the support being connected to the other side of the stage for stiffening the motor supports.

4. An analysis system for automated biological smear detection and identification as claimed in claim 1, wherein the first module includes a motor driving the vertical arm knob bar to move the objective lens up and down slightly through an a-type worm, a worm wheel, an L-type worm and a worm wheel, so that a computer, a relay, a PLC can precisely adjust the distance between the objective lens and the smear.