Method and system for determining optimal insertion segment in a patient's blood vessel

Abstract

A method for determining at least one optimal insertion segment (810a, 810b, 810c, 810d) in a patient's limb for inserting a needle into the patient's vein, wherein the insertion segment (810a, 810b, 810c, 810d) represents an insertion point (820a, 820b, 820c, 820d), an insertion direction, and a maximum insertion length, the method comprising the steps of illuminating the patient's limb with near-infrared illumination, acquiring a near-infrared image of the patient's limb, pre-processing the acquired image to obtain an image of the vein, applying a linear structure detection filter to the image of the vein to obtain a vascular profile map, binarizing the vascular profile map, skeletonizing the vein, defining an insertion segment from the vein skeleton, and classifying the insertion segment according to predetermined classification parameters.

Description

[Technical Field]

[0001] The present invention relates to a method and system for determining an optimal insertion segment in a blood vessel of a patient, human or non-human. The present invention more particularly relates to a method and system for acquiring and processing images that allow the determination of an optimal insertion segment in a blood vessel of a patient. The present invention also relates to an automatic or semi-automatic blood sampling device that uses a system according to the present invention. [Background technology]

[0002] Every day, a large number of vascular access procedures are performed in healthcare facilities, including blood draws, injections, etc. These procedures are time-consuming, repetitive, and potentially dangerous for healthcare workers and patients, and the associated risk of injury must be considered when a needle is introduced into a vein, caused, for example, by a trembling, tired, or inexperienced healthcare worker, or by a patient who moves or reacts in an unhelpful manner.

[0003] Additionally, some patients have vasculature that is less suitable for effective blood collection and may require multiple attempts by the medical professional to insert the needle before reaching a vasculature that will allow blood collection. These repeated attempts can be painful and potentially injurious to the patient, further complicating the sampling procedure for these patients.

[0004] Furthermore, the global coronavirus health crisis has called for the development of systems to limit contact between patients and healthcare workers and / or ensure large-scale screening of the population. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] WO2015158978 Summary of the Invention [Problem to be solved by the invention]

[0006] Therefore, the applicant proposed in WO2015158978 a device for automatic insertion into a patient's vein, comprising means for capturing a near-infrared image of a patient's arm, means for detecting veins in the captured image, a device for holding the detected vein, a needle, and means for inserting the needle into the detected vein.

[0007] Therefore, such a device allows for the automation of blood collection procedures.

[0008] Vein detection by this device is a crucial step to ensure good needle insertion conditions from a health and safety perspective. In particular, it is necessary to find the optimal insertion segment that significantly limits risks while ensuring that the vein is easily reached. The insertion segment is defined by the insertion point, insertion direction, and maximum insertion length.

[0009] The prior art has proposed solutions for detecting blood vessels such as veins, and in particular for assisting operators wishing to perform manual insertion by allowing the person to determine which vein would be most suitable for needle insertion. These solutions use systems for imaging or detecting veins, but such systems can be costly, slow, and sometimes difficult to use.

[0010] However, prior art solutions are limited to assisting the operator, who determines the needle insertion point and needle orientation himself.

[0011] Therefore, the inventors have sought to improve the procedure for determining the optimal insertion segment in order to allow a particularly automatic and autonomous operation of the selection of the optimal insertion segment in a large number of patients with various profiles, i.e., regardless of their morphology, skin pigmentation, marks, moles, hair, etc. [Means for solving the problem]

[0012] Object of the invention The present invention aims to provide a system and method for determining an optimal insertion segment in a patient's vessel.

[0013] Among other things, the present invention aims to provide a system and method for automatically and autonomously determining an optimal insertion segment.

[0014] The present invention particularly aims, in at least one embodiment of the present invention, to provide a system and method for determining the effect on a large number of patients with various profiles, i.e., irrespective of their morphology, skin pigmentation, marks, moles, hair, etc.

[0015] The present invention, in particular in at least one embodiment thereof, aims to provide a system and method for making such a determination that is effective, inexpensive and easy to implement.

[0016] The present invention particularly aims to provide, in at least one embodiment of the present invention, a system and method for determining the orientation of a blood vessel so that possible paths for a needle can be known during needle insertion.

[0017] Detailed Description of the Invention To this end, the present invention provides a method for determining at least one optimal insertion segment in a patient's blood vessel for inserting a needle into said blood vessel, said insertion segment representing an insertion point, an insertion direction and a maximum insertion length in a part of the patient's body, comprising the following steps: illuminating a portion of the patient's body with near-infrared illumination; acquiring a near-infrared image of a portion of the patient's body with at least one camera; - pre-processing the acquired image to obtain an image of the blood vessels visible on the surface of the patient's body part, referred to as a pre-processed image; applying a linear structure detection filter to the pre-processed image to obtain an image, referred to as a vessel profile map, that identifies the vessels visible on the surface of the patient's body part; binarizing the vessel profile map; - a step of skeletonizing the vessels on the binarized vessel profile map, the step being configured to obtain, for each vessel, a vessel skeleton; for each vessel, defining an insertion segment from the skeleton of the vessel; classifying the insert segments according to predetermined classification parameters to identify one or more optimal insert segments.

[0018] Therefore, the method for determining the optimal insertion segment according to the present invention allows the determination of the most favorable insertion segment and the establishment of a classification of these insertion segments to ensure the success and safety of the needle insertion into the patient's blood vessels by performing processing of near-infrared images that allows the best characterization of the subcutaneous blood vessels, e.g., veins, arteries, capillaries, depending on the desired application during needle insertion (sampling, injection, etc.).

[0019] The different steps of the determination method allow for an automatic and autonomous determination of the optimal insertion segment, which is effective, inexpensive, and easy to implement. Contrary to prior art solutions, the present invention is not limited to assistance for a human operator, e.g., by visualizing the location of a blood vessel. Instead, it allows for the precise definition of the insertion segment, i.e., the insertion point where the needle should be inserted, the insertion direction, i.e., the axis along which the needle is inserted, and the maximum insertion length, i.e., the maximum length of the needle's insertable portion, within which the needle can reach the vein, depending on the needle's orientation and the vein's depth. According to current medical practice, the needle insertion angle is generally between 15° and 30° relative to the skin surface. Therefore, the maximum insertion length corresponds to the length of the needle that can be inserted to reach the vein with the minimum insertion angle. If the needle is inserted at a larger angle, the needle will reach the vein with an insertion length shorter than the maximum insertion length. Such a precise definition of the insertion segment allows the use of robotic, automated insertion devices. By following this segment, the needle passes through the different layers that make up the skin (dermis, epidermis, subcutaneous tissue, etc.) until it reaches a blood vessel located in the subcutaneous fatty tissue.

[0020] The insertion segment can be determined in real time to permanently determine the optimal insertion segment as a function of the state of the vessel, which may change over time, in particular the vessel may deform or roll under the influence of mechanical forces, for example when inserting the needle.

[0021] The pre-processing step allows obtaining an image of blood vessels on a part of a patient's body in preparation for filtering in subsequent steps. In particular, the pre-processing step comprises isolating and / or removing irregularities on the skin, such as hairs, moles, tattoos, etc., as well as selectively capillaries, if one wishes to see only veins or arteries, on the image. The purpose is to increase the contrast between the patient's subcutaneous blood vessels and the skin.

[0022] It is also possible to detect the contours of the patient's extremities and selectively remove them from the image, retaining only data relating to the location of blood vessels.

[0023] A vascular profile map is obtained via near-infrared imaging. In particular, due to the difference in near-infrared absorption between the skin layer and the hemoglobin contained in the subcutaneous blood vessels (deoxygenated in veins, oxygenated in arteries), a vascular profile map can be obtained that distinguishes these subcutaneous blood vessels from the rest of the patent (skin, muscle, bone, etc.).

[0024] The processing performed on the vascular profile map can be used in particular for a large number of patients with different profiles, in particular for patients whose veins are difficult to directly identify by a human operator, e.g., a biologist or nurse, by sight and / or by palpation of said veins. As skin pigmentation is not relevant for the method according to the invention, the method is applicable to all phototypes.

[0025] The term "near infrared" is understood to mean wavelengths between 0.7 μm and 3 μm. This definition corresponds in particular to the infrared ranges IR-A and IR-B defined by the International Commission on Illumination (CIE). For detecting blood vessels in a patient's body part, a preferred wavelength interval is between 0.7 μm and 0.9 μm, in particular for detecting veins in the arm.

[0026] The needle is often inserted into a patient's limb, typically into the patient's arm, typically in the area of ​​the cubital fossa.

[0027] The linear structure detection filter is similar to an edge detection filter or a contour detection filter, and can detect the presence of linear structures, particularly blood vessels, on the image in the present invention.

[0028] Classification of the insertion segments allows selection of the best candidate segments for needle insertion.

[0029] According to one variant of the invention, a step of extracting the contours of the vessels identified in the binarized vessel profile map is carried out prior to vessel skeletonization.

[0030] Advantageously, and according to the invention, the classification parameters predetermined for classifying said inserted segments are those of the following list: the location of the segment relative to a known pattern of blood vessel locations on the patient's body part; the average density of all points of the vessel that fall within the contour of the vessel corresponding to the segment, calculated on the vessel profile map; the length of the segment; the depth of the blood vessel in the segment; the diameter of the vessel at the segment; the orientation of the segment; the presence or absence of skin irregularities on the insertion segment; the patient's preferences, and The insertion may be performed in a single step, or in a single step, depending on the patient's previous insertion history.

[0031] According to this aspect of the invention, the classification of the insertion segment depends on one or more parameters, optionally weighted to provide an optimal determination of the optimal insertion segment, in particular to maximize the chances of successful needle insertion and limit safety risks as much as possible.

[0032] The parameters and any weighting of different parameters can be selected based on several criteria, such as the patient's body mass index (BMI), his / her age, the type of needle used, the patient's sampling history, the insertion device's sampling history, the medical professional's preference, the mechanical capabilities of the sampling / injection device, etc.

[0033] The orientation of the segments can be particularly related to the mechanical capabilities of the device performing the insertion, since inserting a needle at an angle too far away from the nominal working axis of the sampling device may not be feasible (taking into account that insertion devices are for example limited to intervals between -90° and 90° relative to the nominal working axis, or smaller or larger intervals, and are not strictly symmetrical depending on the insertion device used).

[0034] Skin irregularities specifically refer to moles, scars, hematomas, petechiae, tattoos, and pimples.

[0035] Advantageously, and according to the invention, the linear structure detection filter is a Frangi filter.

[0036] According to this aspect of the invention, the Frangi filter is particularly suitable for detecting blood vessels. It allows accurate detection of blood vessels, which in turn allows accurate skeletonization of the vessels in the subsequent steps, thereby optimizing the determination of the insertion segment. Furthermore, since the Frangi filter is independent of the scale used (multi-scale filter), this ensures effective detection for each patient, regardless of possible differences in the vessel profiles on the pre-processed images.

[0037] According to other variants of the invention, other types of filters or combinations of filters can be used, in particular second derivative filters.

[0038] Advantageously, and according to the invention, a step of defining an insertion segment from the skeleton of the vessel, said step of defining comprising: A sub-step that creates a node for each point of each skeleton; a sub-step of characterizing each node to form a graph, wherein a node is an end point if it is connected to only a single node, and wherein branches are formed from sets of co-connected nodes having only two adjacent nodes, and each branch is weighted by the number of nodes forming the branch; a sub-step of verifying each graph by comparing each branch with the corresponding vessel on the binarized image; modifying each non-centered branch on the corresponding vessel by splitting the branch into new branches and creating a joining node between each of the new branches; and a sub-step of defining segments, each segment corresponding to a centered branch on its corresponding vessel and having a length greater than a predetermined parameter.

[0039] According to this aspect of the invention, the insertion segment is defined by a skeleton approximation by a graph and by using the branches of this graph to form the segment. Using verification and correction substeps, which can be performed as many times as necessary, it is ensured that each branch is sufficiently centered on the binarized image of the corresponding vessel, i.e. that it is exactly in the center of the vessel, in particular in the center of the extracted contour of the vessel, and has a length long enough to allow needle insertion.

[0040] These substeps allow the segments that can be used for needle insertion to be initially sorted and listed according to a classification according to the method of determination.

[0041] The graph may comprise one or more nodes connected to at least three branches forming a junction node, which allows to retain marks of sub-branches related to irregularities and variations in the shape of the object, thus revealing the topological configuration of the binary object corresponding to the vessel.

[0042] Preferably, before the substep of identifying, the step of defining an insertion segment from the skeleton of the vessel comprises a substep of simplifying the diagram to obtain a final diagram by removing the shortest paths between each of the end points, the longest retained path being the path with the most weighted branches. This final diagram is the diagram used in the following substeps. The search for the shortest segment can be performed using an algorithm for shortest path search, preferably Dijkstra's algorithm.

[0043] Preferably, the step of modifying each of the non-centered branches comprises: identifying criteria for centering branches on the vessel; searching for critical points on the edges that prevent the centralization criterion from being met; splitting the branch point by point from the critical point to form new branches, and splitting new branches if necessary; and a new substep of correcting each new uncentered branch.

[0044] Preferably, the sub-step of defining segments comprises performing double segment removal if two segments relating to the same vessel overlap by more than 65%.

[0045] Advantageously, and according to the invention, the camera is monochromatic and equipped with a near-infrared high-pass filter.

[0046] According to this aspect of the present invention, the image acquired by the camera is directly filtered with a high-pass filter, and the vessel profile map can be easily obtained after pre-processing.

[0047] The term "camera" is understood to mean any device capable of acquiring images and storing and / or transmitting data from these images for processing. The camera may comprise a housing with an image acquisition sensor and a lens. A high-pass filter may be located on the sensor or on the lens, depending on the embodiment. The camera is configured to pick up at least wavelengths corresponding to wavelengths desired to define the insertion segment, but may also be configured to pick up a larger wavelength interval, in which case the desired wavelengths may be targeted by a high-pass filter.

[0048] According to another variant of the invention, near-infrared filtering is performed digitally on the image obtained by the camera, which may be configured to acquire multiple colors (RGB camera), etc.

[0049] The method can use images from multiple cameras, the images being aligned with respect to each other.

[0050] The present invention also relates to a system for determining at least one optimal insertion segment in a patient's blood vessel for inserting a needle into said blood vessel, said segment representing an insertion point, an insertion direction and a maximum insertion length in a part of the patient's body, said system comprising: a unit for acquiring images of the part of the patient's body; and a unit for processing the images acquired by said image acquisition unit, The image acquisition unit a near-infrared illuminator configured to illuminate the portion of the patient's body with near-infrared illumination; at least one camera configured to acquire near-infrared images of a portion of the patient's body; The image processing unit a module for pre-processing an image, called a pre-processed image, configured to provide an image of said blood vessels visible on the surface of said patient's body part; a filtering module configured to apply a linear structure detection filter to the pre-processed image to obtain an image referred to as a vessel profile map that identifies the vessels visible on the surface of the patient's body part; a module for binarizing the vessel profile map; - a module for skeletonizing said vessel on said binarized vessel profile map, said module being configured for obtaining, for each vessel, a skeleton of said vessel; a module for defining, for each vessel, an insertion segment from the skeleton of said vessel; and a module configured to identify one or more optimal insert segments, the module classifying the insert segments according to predetermined classification parameters.

[0051] Advantageously, the system for determining according to the invention implements the method for determining according to the invention.

[0052] Advantageously, the determining method according to the invention is implemented by a determining system according to the invention.

[0053] The present invention also relates to an automatic or semi-automatic insertion device for inserting a needle into a part of the patient's body, such as a patient's limb, preferably a patient's arm, comprising a mechatronic assembly such as a robotic arm, a unit for controlling the mechatronic assembly, an insertion head for the needle attached to the mechatronic assembly, and further comprising a determining system according to the present invention configured to determine an optimal insertion segment for inserting the needle into the part of the patient's body.

[0054] An automatic or semi-automatic insertion device equipped with a determining system according to the present invention can realize, in an automatic or semi-automatic and autonomous manner, the insertion of a needle (for blood sampling or injection) into a part of a patient's body based on one of the optimal insertion segments determined by the determining system. The injection needle can be connected to a syringe, a catheter, etc.

[0055] The insertion device may be a lancing or sampling device if the insertion device is intended to take a blood sample, or an injection device if the insertion device is intended to inject a product into a blood vessel.

[0056] The invention also relates to a method for determining, a system for determining and an insertion device characterized in a combination of all or some of the features described above or below.

[0057] Other objects, features and advantages of the present invention will become apparent from reading the following description, given in a non-limiting manner only, and made with reference to the accompanying drawings, in which: [Brief explanation of the drawings]

[0058] [Figure 1] FIG. 1 is a schematic diagram of a determination method according to one embodiment of the present invention. [Figure 2] FIG. 2 is a diagram of a pre-processed photographic image obtained during the implementation of a method for determining according to one embodiment of the present invention. [Figure 3] FIG. 3 is a vascular profile map obtained during the implementation of a determination method according to one embodiment of the present invention. [Figure 4] FIG. 4 is a binarized image obtained during the implementation of a determination method according to one embodiment of the present invention. [Figure 5] FIG. 5 is an image showing a skeletonization of a vessel obtained during the implementation of a determination method according to one embodiment of the present invention. [Figure 6] FIG. 6 is an image showing a graph representing a vessel skeleton obtained during the implementation of a determination method according to one embodiment of the present invention. [Figure 7] FIG. 7 is an image showing a segment from a graph obtained during the implementation of a method for determining according to one embodiment of the present invention. [Figure 8] FIG. 8 is an image showing determined segments superimposed on a pre-processed image obtained during the implementation of a determining method according to one embodiment of the present invention. [Figure 9] FIG. 9 is a schematic diagram of a determining system according to one embodiment of the present invention. [Figure 10] FIG. 10 is a schematic diagram of an insertion device according to one embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0059] In the figures, for the sake of illustration and clarity, scale and proportions have not been strictly respected.

[0060] Furthermore, identical, similar or analogous components are designated by the same reference numerals in all figures.

[0061] 1 is a schematic illustration of a method for determining, according to one embodiment of the present invention, at least one optimal insertion segment in a part of a patient's body for inserting a needle into a patient's blood vessel, said segment representing an insertion point, an insertion direction, and a maximum insertion length in said part of the patient's body. The blood vessel may be, for example, a vein, an artery, or a capillary.

[0062] The method comprises a step 100 of illuminating a part of a patient's body, such as a patient's limb, in this case the patient's arm, with near-infrared illumination. The near-infrared illumination is comprised of one or more near-infrared lamps. Multiple near-infrared lamps allow for the illumination of the part of the patient's body in a homogeneous manner, the part having a volumetric surface where shadow areas may occur if there are an insufficient number of lamps. The objective is to uniformly illuminate the area of ​​interest.

[0063] The method then comprises acquiring a near-infrared image of a portion of the patient's body with at least one camera at step 120. The use of near-infrared illumination in conjunction with camera capture results in a near-infrared reflectance image, referred to as near-infrared spectroscopy.

[0064] The method then includes a step 130 of preprocessing the acquired image to obtain an image of blood vessels visible on the surface of the patient's body part, referred to as a preprocessed image. A representation of the preprocessed image obtained by the preprocessing step 130 is shown, for example, with reference to FIG. 2. FIG. 2 corresponds to a representation of a photographic image taken by a monochrome camera and then preprocessed. The skin of the patient's limb 220 has shades of gray that vary in intensity depending on the patient's photographic type and the absorption of near-infrared light by the skin. The difference in absorption of near-infrared light between the skin layer and the hemoglobin contained in the subcutaneous blood vessels allows the extraction of blood vessels 210 of the patient's limb 220 on the preprocessed image 200. Furthermore, the dark background 230 on the preprocessed image 200 allows the edge of the limb 220 to be clearly defined.

[0065] The pre-processing step may also include several processing steps that allow obtaining an optimized pre-processed image, such as the following processing steps: - a thresholding step or k-means algorithm to reduce the area to be processed by binarizing the image, i.e., k-means algorithm; - a histogram equalization step to enhance the contrast between the blood vessels and the skin; - applying a filter to remove information that may interfere with the performance of subsequent steps (e.g., groups of hairs on a part of the patient's body, etc.), where the applied filter is, for example, a median filter, a Gaussian filter, or a bilateral filter.

[0066] The method then comprises a step 140 of applying a linear structure detection filter to the preprocessed image to obtain an image, called a vessel profile map, which identifies the vessels visible on the surface of the patient's body part. The vessel profile map obtained by the filter application step 140 is shown, for example, with reference to FIG. 3. The linear structure detection filter applied in this case is a Frangi filter. The image 300 filtered by the Frangi filter allows the very linear structures, in particular the vessels 310 and the contours 320, 330 of the patient's limbs, to be retained in the image.

[0067] The method then comprises a step 150 of binarising the vessel profile map, which comprises thresholding the intensity to obtain an image with only two pixel counts.

[0068] The method then comprises, in this embodiment, a step 160 of extracting the contours of the blood vessels identified in the binarized blood vessel profile map, and a binarized blood vessel profile map 400 comprising the blood vessels obtained by said binarization step 150 and contour extraction step 160 is shown, for example, with reference to Figure 4. The contours of the patient's limbs can be removed from the binarized image so as to retain only data relating to the location of the blood vessels 410.

[0069] The method then comprises a vessel skeletonization step 170, for example from the extracted contours or directly from the binarized vessel contour map, which is configured to obtain, for each vessel, a skeleton of this vessel. The vessel skeletons 510 obtained by said step 170 are shown on the skeletonized binary image 500, for example with reference to FIG. 5. The skeletonization is performed, for example, by a skeletonization algorithm, for example morphological skeletonization or Zhang-Suen skeletonization. This skeletonization makes it possible to obtain skeletons 510, which are sets of curves each describing the center of the vessel object with increased accuracy without compromising its topology.

[0070] The method then includes a step 180 of defining, for each vessel, an insertion segment from the vessel skeleton. Figure 6 shows schematic diagrams 610a, 610b, 610c, and 610d representing the vessel skeleton corresponding to the binarized and filtered image 600 to illustrate the correspondence of each graph between the vessel contour and the skeleton. The dashed graphs 610a, 610b, 610c, and 610d represent approximations of the skeletons 510a, 510b, 510c, and 510d shown in white. First, a node is created for each point in the skeleton. Each node is then characterized to form a graph. If a node is connected to only a single node, it is an end point. A branch is formed from a set of connected nodes with only two neighbors, and each branch is weighted by the number of nodes that form the branch. A junction node is connected to at least three branches. For example, graph 610a is an approximation of skeleton 510a, specifically including end points 630. Graph 610d is an approximation of skeleton 510d, specifically including junction nodes 620.

[0071] A branch between two nodes in the diagram represents a portion of a substantially rectangular skeleton, however the branch is an approximation of the skeleton and may sometimes be off-center with respect to the vessel represented by the skeleton, as can be seen, for example, for graphs 610b and 610d in Figure 6.

[0072] The graph can be simplified to obtain a final graph by removing the shortest path between each end point, and the longest retained path is the path with the most weighted edges. This final graph is used in the subsequent substeps. The search for the shortest segment can be effected using an algorithm for searching shortest paths, preferably Dijkstra's algorithm.

[0073] Processing the graphs in this manner involves a substep of identifying each graph by comparing it with the corresponding vessel on the binarized image, and then correcting each branch that is not centered on the corresponding vessel by splitting the branch into two new branches and creating a joining node between the two new branches.

[0074] In particular, the step of modifying each of the non-centered branches comprises: Identifying (checking) criteria for centering the branch on the vessel; searching for critical points on the edges that prevent the centralization criterion from being met; splitting the branch point by point from the critical point to form new branches, and splitting new branches if necessary; and a new substep of correcting each new uncentered branch.

[0075] Once branches shorter than a predetermined parameter have been removed and all branches have been centered, the inserted segments corresponding to the matching branches are obtained. If duplicate segments are obtained, i.e., if two segments relating to the same vessel overlap by more than 65%, these segments are removed.

[0076] These segments 710 are shown with reference to FIG. 7, which represents segments on a binarized image 700 of a blood vessel. If the insertion segments are restored on the preprocessed image, an image 800 is obtained, which represents the determined segments added to the preprocessed image, as shown in FIG. 8. The insertion segments 810a, 810b, 810c, and 810d are characterized by their insertion points 820a, 820b, 820c, and 820d, their insertion directions, and their maximum insertion lengths, respectively. The insertion points are calculated as the most likely point between the two ends. The most likely point is calculated as a function of, for example, the orientation of the patient's body part, the capabilities of the insertion device, etc. In particular, for insertion into the patient's arm, the insertion point is generally the point closest to the antecubital fossa.

[0077] The method finally comprises a step 190 of classifying the insert segments according to predetermined classification parameters so as to identify one or more optimal insert segments.

[0078] 9 is a schematic diagram illustrating a determining system according to an embodiment of the present invention. The determining system 900 includes an image processing unit 910 having a set of modules configured to implement the determining method described above. A module describes a hardware and / or software brick that allows performing one or more steps of the method described above. Some modules can be included in a single electrical component and / or a single piece of software, or steps performed by one module can require several electrical components and / or pieces of software. Different electrical components may be assembled on a single printed circuit board.

[0079] The processing unit 910 receives images acquired by an image acquisition unit that includes, inter alia, a near-infrared camera 920 and near-infrared illumination 930, which in this case consists of, for example, a number of light-emitting diodes (LEDs) surrounding the camera 920. The camera 920 and illumination 930 can be controlled, for example, by a control module (not shown) located on the same printed circuit board as one or more modules of the image processing unit 910. The camera 920 can also include a near-infrared filter 922. The camera 920 generally includes a housing with a sensor and a lens system with individual lenses that allow for configuring the focal length and desired aperture (not shown). The near-infrared filter 922 can be located on the lens or in the housing, according to embodiments of the present invention.

[0080] Camera 920 and light 930 are aimed at a part of the patient's body, in this case a patient's limb 940, for example the patient's arm, represented here by a cylinder of rotation. The patient's arm rests on support 950.

[0081] Figure 10 shows a schematic representation of an insertion device according to an embodiment of the present invention, comprising a mechatronic assembly such as a robotic arm 16, a unit 20 for controlling the robotic arm, a determining system 900 according to the embodiment of Figure 9, and an insertion head 12. Once the optimal insertion segment has been determined, the control unit 20 sends movement information for the needle holder to the actuators of the robotic arm 16 and the insertion head 12 so as to be able to insert the needle 14 into the part of the body of the patient 10 where sampling is to be performed.

Claims

1. 1. A method for determining at least one optimal insertion segment (810a, 810b, 810c, 810d) in a patient's blood vessel for inserting a needle into the blood vessel, wherein the insertion segment (810a, 810b, 810c, 810d) represents an insertion point (820a, 820b, 820c, 820d) in a part of the patient's body, an insertion direction, and a maximum insertion length, comprising the steps of: illuminating (110) a portion of the patient's body with near-infrared illumination; acquiring (120) a near-infrared image of a portion of the patient's body with at least one camera (920); - pre-processing (130) the acquired image to obtain an image of the blood vessels visible on the surface of the patient's body part, referred to as a pre-processed image; applying (140) a linear structure detection filter to the pre-processed image to obtain an image, referred to as a vessel profile map, that identifies the vessels visible on the surface of the patient's body part; binarizing (150) the vessel profile map; - a step (170) of skeletonizing the vessels on the binarized vessel profile map, the step being configured to obtain, for each vessel, a skeleton of the vessel; for each vessel, defining (180) the insertion segment from the skeleton of the vessel; and classifying (190) the insert segments according to predetermined classification parameters so as to identify one or more optimal insert segments.

2. The predetermined classification parameters for classifying the inserted segments (810a, 810b, 810c, 810d) are the following list: the position of the insertion segment relative to a known pattern of blood vessel positions on the patient's body portion; the average density of all points of the vessel that are contained within the vessel contour corresponding to the insertion segment, calculated on the vessel profile map; the length of the insert segment; the depth of the vessel at the insertion segment; the diameter of the vessel at the insertion segment; the orientation of the insert segment; the presence or absence of skin irregularities on the insertion segment; the patient's preferences, and 2. The method of claim 1, wherein the method is selected from one or more parameters from a history of previous insertions for the same patient.

3. 3. The method of claim 1, wherein the linear structure detection filter is a Frangi filter.

4. Defining (180) the insertion segment from the skeleton of the vessel, the defining step comprising: A sub-step that creates a node for each point of each skeleton; a sub-step of characterizing each node to form a graph, wherein a node is an end point if it is connected to only a single node, and wherein branches are formed from sets of co-connected nodes having only two adjacent nodes, and each branch is weighted by the number of nodes forming the branch; identifying each graph by comparing each branch with the corresponding vessel on the binarized image; modifying each non-centered branch on the corresponding vessel by splitting the branch into new branches and creating a joining node between each of the new branches; 4. The method according to claim 1, further comprising a sub-step of defining said insertion segments, wherein one insertion segment corresponds to a centered branch on its corresponding vessel and has a length greater than a predetermined parameter.

5. 5. The method of claim 1, wherein the camera (920) is monochromatic and is equipped with a near-infrared high-pass filter.

6. 1. A system for determining at least one optimal insertion segment in a blood vessel of a patient for inserting a needle into the blood vessel, the insertion segment representing an insertion point, an insertion direction, and a maximum insertion length in a part of a body of the patient, the system comprising: a unit for acquiring images of the part of the body of the patient; and a unit for processing the images acquired by the image acquisition unit; The image acquisition unit (910) a near-infrared illuminator (930) configured to illuminate a portion of the patient's body with near-infrared illumination; at least one camera (920) configured to acquire near-infrared images of a portion of the patient's body; The image processing unit (910) a module for pre-processing an image, called a pre-processed image, configured to provide an image of said blood vessels visible on the surface of said patient's body part; a filtering module configured to apply a linear structure detection filter to the pre-processed image to obtain an image referred to as a vessel profile map that identifies the vessels visible on the surface of the patient's body part; a module for binarizing the vessel profile map; - for each vessel, a module for skeletonizing said vessel on said binarized vessel profile map to obtain a skeleton of said vessel; a module for defining, for each vessel, the insertion segment from the skeleton of the vessel; the determining system comprising: a module configured to identify one or more optimal insert segments; and a module for classifying the insert segments according to predetermined classification parameters.

7. 7. The system of claim 6, wherein the camera (920) is monochromatic and includes a near-infrared high-pass filter.

8. An automatic or semi-automatic insertion device for inserting a needle into a body part of a patient (10), comprising a mechatronic assembly (16) and a unit (20) for controlling said mechatronic assembly (16); an insertion head (12) for the needle attached to a mechatronic assembly (16); 8. The automatic or semi-automatic insertion device, further comprising a determining system (900) according to claim 6 or 7, configured to determine at least one optimal insertion segment for inserting the needle into a body part of the patient (10).

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