Systems and methods for characterizing a region of interest in a biological tissue

Abstract

A system for characterizing a region of interest of a biological tissue comprising: a sighting device (110) configured to produce a reflection image of an elementary surface of the biological tissue; a microscopic analysis device (120) configured to detect, according to a detection pattern included in said elementary surface, a light beam emitted by the biological tissue in response to illumination of the biological tissue and to generate microscopic analysis information, and to determine from said microscopic analysis information a tissue characterization parameter; a processing module (140) configured to combine a plurality of elementary surface images to produce a surface image of the region of interest and to produce a mapping element of the characterization parameter;a display module (150) configured to display a tissue map comprising said map element, said map being located relative to said surface image. FIG. 1B;

Description

Title of the invention: Systems and methods for characterizing a region of interest of a biological tissue Technical field

[0001] The present description relates to systems and methods for characterizing a region of interest of a biological tissue, and applies in particular to the characterization of a region of interest of the skin in the context of an excision. State of the art

[0002] In the context, for example, of the excision of a skin tumor, it is important for the surgeon to characterize the extent of the tumor as best as possible in order to extract all of the tumor tissue while limiting the extraction of healthy tissue around the tumor. The contours of a spatial extent that encompasses the region of tissue to be extracted are generally called "surgical margins" or "excision margins." The excision margins must also advantageously take into account the presence of a lesion deep in the skin.

[0003] Generally speaking, optical methods are known for determining the margins of excision in surgery.

[0004] For example, the article by A. Alfonso-Garcia et al. [Ref. 1] describes, in neurosurgery, an imaging technique based on multi-photon fluorescence FLlm (for "Fluorescence Lift-time Imaging") which makes it possible to identify, in real time during a surgical intervention, regions of the brain affected by a tumor and healthy regions, in order to delimit the surgical margins. More precisely, the region of interest is filmed using a camera. An analysis of FLlm fluorescence is carried out in parallel using an optical fiber moved by an operator at the region of interest, the optical fiber allowing the transport of the excitation light beam as well as the collection of the fluorescence signal. A characteristic parameter of the analysis by FLlm fluorescence, namely the color-coded fluorescence lifetime, is superimposed on the video images in order to present to the operator an augmented reality view of the region of interest.

[0005] Such a technique is however difficult to adapt to the excision of skin tumors due to the precision required for the delimitation of the excision margins, on the one hand because there is no depth resolution of the fluorescence signal in the technique described above and on the other hand because there may be positioning errors between the surface images acquired by the camera and the representation of the characteristic parameter of the fluorescence, due to inevitable movements of the biological tissue to be analyzed.

[0006] In the published patent application WO2020087164 [Ref. 2], optical coherence tomography images or OCT images for "optical coherence tomography" are used to delineate the margins of excision of ablated tissues, for example to determine whether a tumor has been completely extracted, in particular in breast-conserving surgery procedures. A convolutional neural network or CNN for "Convolutional neural network" is trained to recognize in the OCT images a probability of the presence of anomalies in the region explored. The OCT images can be three-dimensional, which makes it possible to also take into account the tumor regions in depth for the determination of the margins of excision. An annotated image of the three-dimensional image thus acquired can be generated, with an indication of the probability of anomalies in the region of interest.

[0007] However, the method described in [Ref. 2] is suitable for ex vivo applications and would not be suitable for in vivo applications. On the one hand, because the acquisition of all the images from which the analysis is made is long (typically several minutes). On the other hand, because even if artificial intelligence tools are used for the recognition of anomalies in OCT images, these images would remain difficult to interpret for a practitioner in the context of in vivo characterization, during which practitioners are accustomed to observing surface images.

[0008] The present description proposes systems and methods for characterizing a region of interest of a biological tissue, in particular allowing in vivo characterization to easily guide an excision, in particular a characterization of the skin, which allows both excellent precision and can be easily interpreted by a practitioner. Summary of the invention

[0009] In the present description, the term "comprise" means the same as "include", "contain", and is inclusive or open and does not exclude other elements not described or shown. Furthermore, in the present description, the term "approximately" or "substantially" is synonymous with (means the same as) having a lower and / or upper margin of 10%, for example 5%, of the respective value.

[0010] According to a first aspect, the present description relates to a system for characterizing a region of interest of a biological tissue, comprising: - a sighting device comprising: - a full-field illumination device configured to illuminate the biological tissue in a first spectral band; - a two-dimensional detector comprising a detection area; - a full-field imaging device comprising a first optical axis and configured to optically conjugate an elementary surface of the biological tissue with said detection area of ​​the two-dimensional detector, the two-dimensional detector producing, in operation, a reflection image of said elementary surface; - a microscopic analysis device comprising: - a microscope objective comprising a second optical axis, mechanically secured to the first optical axis; - a lighting path configured to illuminate the biological tissue according to a first lighting pattern included in said elementary surface, and in a second spectral band; - a detection path comprising said microscope objective, said detection path being configured to detect, according to a detection pattern included in said elementary surface, a light beam emitted by the biological tissue in response to said illumination of the biological tissue and generate microscopic analysis information; - a first processing module configured to determine, from said microscopic analysis information, at least a first parameter for characterizing the biological tissue at a given number of points of said detection pattern; - a second processing module configured for - combining by mosaicking a plurality of elementary surface images acquired successively by moving the full-field imaging device of the viewing path and having partial overlap, to produce a surface image of the entire region of interest and - producing at least one first mapping element of said at least one first characterization parameter, from the determination of said at least one first characterization parameter for at least a portion of the elementary surface images of said plurality of elementary surface images; - a display module configured to display a tissue map comprising at least said first mapping element, said map being referenced relative to said surface image.

[0011] In the present description, the illumination pattern depends on the illumination path of the microscopic analysis path and may comprise an illumination spot, an illumination line or an illumination surface, for example a rectangular surface resulting from the scanning of an illumination spot or an illumination line. An illumination spot is more precisely defined as the diffraction pattern resulting from the focusing, by the microscope objective of the microscopic analysis path, of a collimated light beam incident on said objective. The illumination pattern may also comprise an illumination surface which does not result from scanning, for example a surface with circular geometry, in the case of a full-field microscopic analysis path.

[0012] The light beam emitted by the biological tissue in response to the illumination of the sample may be a reflected beam, a backscattered beam, or a beam resulting from a process emission at another wavelength (e.g. fluorescence, Raman scattering, etc.)

[0013] Furthermore, an elementary surface is defined by the field in the object space of the full-field imaging device of the aiming device, called "effective field" in the present description. An elementary surface is for example defined by a circle when for example the effective field is limited by the optics of the aiming device, or by a rectangle when the effective field is limited by the detection area of ​​the two-dimensional detector of the aiming device. An image of an elementary surface produced by the aiming device is also called "aiming image" in the present description.

[0014] The detection pattern is included in the elementary surface produced by the aiming device and is included in the illumination pattern or is of the same order of magnitude, and depends on the detection path of the microscopic analysis device. The detection pattern may comprise a detection point, a detection line or a detection surface, for example a rectangular surface resulting from the scanning of a line, or, in the case of a full-field microscopic analysis path, a surface optically conjugated with a detection area of ​​a detector. A detection point is here defined in the object space by an elementary zone optically conjugated with an elementary detector of a detector of the detection path of the microscopic analysis device.

[0015] The characterization system according to the first aspect, due to the original combination of characteristics, allows identification of a mapping of at least a first characterization parameter of the tissue relative to a surface image of the region of interest, with excellent precision, i.e. better than a few microns.

[0016] For example, in exemplary embodiments, the display module is configured to further display said surface image of the entire region of interest, the surface image of the region of interest being easily interpretable by a practitioner. In other exemplary embodiments, the display module is configured to further display another surface image of the entire region of interest, acquired by another imaging system, for example a dermoscopic image acquired by a dermatoscope, and referenced relative to the surface image of the region of interest acquired by the characterization system according to the first aspect.

[0017] For example, in exemplary embodiments, the display module is configured so that said tissue mapping is displayed superimposed on said surface image of the entire region of interest or superimposed on another surface image of the entire region of interest, acquired by another imaging system and referenced relative to the surface image of the region of interest acquired by the characterization system according to the first aspect.

[0018] In other exemplary embodiments, the display module may be configured so that said tissue mapping is displayed juxtaposed with said surface image of the entire region of interest, or juxtaposed with another surface image of the entire region of interest, acquired by another imaging system and referenced relative to the surface image of the region of interest acquired by the characterization system according to the first aspect. In these exemplary embodiments, the display module is further configured to represent, both in said tissue mapping and in the surface image of the entire region of interest, a common cursor, i.e. a graphical element configured to reference the same spatial position on the mapping and said surface image of the entire region of interest.

[0019] Of course, the display module can be configured to operate in one and / or the other of the embodiments described above, at the choice of a user.

[0020] In all cases, excision is facilitated because the practitioner can easily and precisely identify, at the surface of the tissue, the outline of an area of ​​interest, for example the outline of a tumor, even if not directly visible on the surface. This precision is made possible in particular due to the mechanical solidarity between the first optical axis of the full-field imaging device of the aiming device and the second optical axis of the microscope objective of the microscopic analysis device.

[0021] According to one or more exemplary embodiments, the full-field imaging device of the aiming device comprises said microscope objective. In these exemplary embodiments, the first optical axis and the second optical axis are merged, which makes it possible to have a more compact characterization system while benefiting from a quality aiming image since it is obtained with the microscope objective. Furthermore, the identification of the mapping of said at least one first characterization parameter on the surface image is simplified.

[0022] In other embodiments, the full-field imaging device of the aiming device does not include the microscope objective of the microscopic analysis device. In this case, however, the mechanical solidarity of the first optical axis and the second optical axis will make it possible to locate the detection pattern in the aiming image and thus to locate the mapping of the tissue as a function of said at least one first parameter on the surface image of the entire region of interest.

[0023] In exemplary embodiments, the first spectral band of the full-field illumination device of the aiming device and the second spectral band of the illumination path of the microscopic analysis device differ at least partially. This makes it possible in exemplary embodiments to at least partially filter the light coming from the illumination path of the microscopic analysis device and incident in the aiming device or vice versa, to filter at least partially the light coming from the full-field illumination device of the aiming device and incident in the microscopic analysis system.

[0024] According to one or more exemplary embodiments, the full-field illumination device of the viewing path comprises a plurality of light sources arranged on a periphery of a distal face of the microscope objective, i.e. the face of the microscope objective in the space of the biological tissue. This configuration allows direct illumination of the biological tissue. Of course, other configurations are possible for the full-field illumination device of the viewing path.

[0025] According to one or more exemplary embodiments, the illumination path of the microscopic analysis device is configured to illuminate the biological tissue through the microscope objective. In other exemplary embodiments, direct illumination of the biological tissue is possible, without passing through the microscope objective, for example by means of optical fibers.

[0026] According to one or more exemplary embodiments, said microscopic analysis channel is a confocal imaging channel and / or optical coherence tomographic imaging channel and said microscopic analysis information of the biological tissue comprises at least one image of the biological tissue. For example, the microscopic analysis channel is an optical coherence tomographic imaging channel as described in the state of the art and is configured to form B-Scans, C-Scans (or face images) of the biological tissue or 3D images of the biological tissue.As is known, a cross-sectional image of the biological tissue, called a “B-Scan”, is an image formed in a plane parallel to the optical axis of the microscope objective; a cross-sectional image of the sample, called a “C-Scan”, or face image, is an image formed in a plane perpendicular to the optical axis of the microscope objective, and a 3D image of the biological tissue results from the acquisition of a plurality of B-Scan images or C-Scan images and thus allows an analysis of the biological tissue in a volume.

[0027] According to one or more exemplary embodiments, said microscopic analysis pathway is a spectroscopic analysis pathway and said microscopic analysis information of the biological tissue comprises at least one spectrum of said light beam emitted by the sample at at least one point of the sample.

[0028] According to one or more exemplary embodiments, said at least one first parameter for characterizing the biological tissue according to which the first processing module generates a mapping of the tissue from said microscopic analysis information is a parameter chosen from: a morphological measurement, a cytological measurement, an optical measurement, a measurement characterizing a chemical composition, a mechanical measurement, a combination of these measurements, a characterization score terization of the state of the tissue, for example based on at least one of these measures, for example a score indicating a probability of the presence of a lesion, for example a lesion of a predetermined nature.

[0029] According to one or more exemplary embodiments, said first module for processing said microscopic analysis information comprises an artificial intelligence module, for example based on a deep learning model using neural networks.

[0030] According to a second aspect, the present disclosure comprises methods of characterizing a region of interest of a biological tissue implemented by any of the exemplary embodiments of the systems according to the first aspect.

[0031] Thus, the present description comprises, according to a second aspect, a method for characterizing a region of interest of a biological tissue, comprising: - the acquisition of a plurality of reflection images of elementary surfaces of said region of interest of the biological tissue, by means of a sighting device, the sighting device comprising a two-dimensional detector with a detection area and a full-field imaging device comprising a first optical axis, the successively acquired images of elementary surfaces having a partial overlap, the acquisition of an image of an elementary surface comprising: - full-field illumination of said elementary surface in a first spectral band; - the optical conjugation of said elementary surface with said detection area of ​​the two-dimensional detector to generate the image of said elementary surface; - for each image of an elementary surface of a plurality of said images of elementary surfaces thus acquired, a microscopic analysis of the biological tissue at the level of said elementary surface, by means of a microscopic analysis device comprising a microscope objective with a second optical axis mechanically secured to the first optical axis, said microscopic analysis comprising: - illumination of the biological tissue according to a first given illumination pattern included in said elementary surface and in a second spectral band; - the detection, according to a detection pattern included in said elementary surface, of a light beam emitted by the biological tissue in response to said illumination of the biological tissue to produce microscopic analysis information; - processing said microscopic analysis information to determine from said microscopic analysis information at least a first parameter for characterizing the biological tissue at a given number of points of said detection pattern; - the combination by mosaicking of said surface images of the plurality of surface images to produce a surface image of the entire region of interest; - producing at least one first mapping element from said at least one first characterization parameter determined for at least a portion of the elementary surface images of said plurality of elementary surface images; - displaying a mapping of the tissue comprising at least said first mapping element, said mapping being referenced relative to said surface image.

[0032] According to one or more exemplary embodiments, the characterization method further comprises displaying said surface image of the entire region of interest or another surface image of the entire region of interest, acquired by another imaging method and referenced relative to the surface image of the region of interest acquired by means of the method according to the second aspect.

[0033] For example, said tissue mapping is displayed superimposed on said surface image of the entire region of interest or superimposed on said other surface image of the entire region of interest.

[0034] In other exemplary embodiments, said tissue map is displayed juxtaposed to said surface image of the entire region of interest, or juxtaposed to said other surface image of the entire region of interest, a common cursor being further represented in said tissue map and in said surface image of the entire region of interest or in said other image. The common cursor is for example a graphic element configured to locate the same spatial position on the map and said surface image of the entire region of interest or said other image.

[0035] According to one or more exemplary embodiments, the full-field imaging device of the aiming device comprises said microscope objective.

[0036] According to one or more exemplary embodiments, the microscopic analysis of the biological tissue comprises confocal and / or optical coherence tomographic imaging of the biological tissue making it possible to form B-Scans, C-Scans or 3D images of the biological tissue.

[0037] According to one or more exemplary embodiments, the microscopic analysis of the biological tissue comprises a spectroscopic analysis of the sample.

[0038] According to one or more exemplary embodiments, the illumination of the biological tissue for microscopic analysis is done through the microscope objective.

[0039] According to one or more exemplary embodiments, said at least one first parameter for characterizing the biological tissue according to which the mapping of the tissue is established from the microscopic analysis information comprises a parameter chosen from: a morphological measurement, a cytological measurement, a score indicating a probability of presence of a lesion.

[0040] According to one or more exemplary embodiments, the processing of said microscopic analysis information comprises the use of an artificial intelligence module, for example based on a deep learning model using neural networks.

[0041] According to one or more exemplary embodiments, said combination by mosaicking is carried out as the images of said elementary surfaces are acquired, which makes it possible, for example, to have a real-time display of the acquired surface image and of the mapping of said at least one first identification parameter, allowing, for example, a practitioner to make decisions during the acquisition.

[0042] According to one or more exemplary embodiments, said at least one first mapping element is produced as the acquisition progresses.

[0043] In other embodiments, said mosaic combination is established after acquisition of all the elementary surface images (viewing images). There are then fewer processing resources used in real time.

[0044] According to one or more exemplary embodiments, the biological tissue is the skin and the method is implemented in vivo. The method applies for example to the characterization of cancerous lesions.

[0045] According to a third aspect, the present description comprises a method for determining excision margins of a region of biological tissue to be extracted comprising: - the characterization of said biological tissue by means of a characterization method according to the second aspect; - determining the excision margins from said mapping comprising said first mapping element of said at least one first characterization parameter.

[0046] For example, the excision margins are determined from the contour defined by said mapping, for example by adding an additional margin, for example an additional margin of between approximately 0.5 mm and approximately 5 mm. Brief description of the figures

[0047] Other advantages and characteristics of the invention will appear on reading the description, illustrated by the following figures:

[0048] [Fig.lA], a diagram illustrating a first example of a system for characterizing a region of interest of a biological tissue according to the present description;

[0049] [Fig.lB], a diagram illustrating a second example of a system for characterizing a region of interest of a biological tissue according to the present description;

[0050] [Fig.2], a diagram illustrating an example of a system for characterizing a region of interest of a biological tissue implementing a microscopic analysis of optical coherence tomographic imaging type;

[0051] [Fig.3A], a diagram illustrating in a simplified manner an implementation of steps of a method for characterizing a region of interest of a biological tissue, using an example of a characterization system according to the present description;

[0052] [Fig.3B], an example of displaying a surface image of the entire region of interest superimposed on a mapping comprising a plurality of mapping elements respectively of different characterization parameters, obtained by means of an example method according to the present description;

[0053] [Fig.3C], an example of displaying a surface image of the entire region of interest juxtaposed with a mapping comprising a plurality of mapping elements respectively of different characterization parameters, obtained by means of an example of a method according to the present description;

[0054] [Fig.4], a diagram representing a block diagram of a method according to the present description, according to a first example;

[0055] [Fig.5A], a diagram illustrating a step of a characterization method such as described in [Fig.4];

[0056] [Fig.5B], a diagram illustrating a step of a characterization method as described on [Fig.4];

[0057] [Fig.5C], a diagram illustrating a step of a characterization method as described on [Fig.4];

[0058] [Fig.5D], a diagram illustrating a step of a characterization method such as described in [Fig.4];

[0059] [Fig.6], a diagram representing a block diagram of a method according to the present description, according to a second example. Detailed description of the invention

[0060] In the following detailed description, numerous specific details are set forth in order to provide a more thorough understanding of the present disclosure. However, it will be apparent to those skilled in the art that the present disclosure may be implemented without these specific details. In other instances, well-known features have not been described in detail to avoid unnecessarily complicating the disclosure.

[0061] Furthermore, in the figures, the elements are not shown to scale for better visibility.

[0062] [Fig.lA] represents a diagram illustrating a first example 101 of a system for characterizing a region of interest of a biological tissue S according to the present description and [Fig.lB] represents a diagram illustrating a second example 102 of a system for characterizing a region of interest of a biological tissue according to the present description.

[0063] The characterization systems 101, 102 each comprise a sighting device 110 comprising a full-field illumination device 111, for example a set of light-emitting diodes or LEDs, configured to illuminate the biological tissue in a first spectral band, a two-dimensional detector (not shown in the figures) and a full-field imaging device (not shown in the figures), only the optical axis Ai of the full-field imaging device being shown diagrammatically. The full-field imaging device of the sighting device is configured to optically conjugate an elementary surface of the biological tissue with a detection area of ​​the two-dimensional detector, the two-dimensional detector producing, in operation, a reflection image of said elementary surface, called a "sighting image" in the present description.For example, the aiming device 110 comprises a mount 115 configured to receive all or part of the optoelectronic elements forming the full-field imaging device and the two-dimensional detector.

[0064] The characterization systems 101, 102 each further comprise a microscopic analysis device 120 comprising a microscope objective 125 comprising an optical axis A2, mechanically secured to the optical axis Ai of the full-field imaging device.

[0065] In the example of characterization system 101 illustrated in [Fig. 1A], the optical axes Ai of the full-field imaging device of the aiming device 110 and A2 of the microscope objective 125 are distinct. The mechanical solidarity of the axes Ai and A2 is for example ensured by a common mount (not shown in [Fig. 1A]).

[0066] In the exemplary characterization system 102 illustrated in [Fig. 1B], the microscope objective 125 is included in the full-field imaging device of the aiming device 110 and the optical axes Ai and A2 are merged. In this example, a beam splitter element 113 makes it possible to separate the detection paths of the aiming device and the microscopic analysis device.

[0067] In both examples, a distal end of the characterization system can be defined, configured to be in contact or close to the biological tissue S. In the case, for example, of characterization of the skin, the distal end of the characterization system can comprise a glass slide (not shown in the figures) or a mechanical part (not shown in the figures) which makes it possible to fix a predetermined distance between the skin and an entrance pupil of the microscope objective.

[0068] In these examples, the full-field illumination device 111 of the aiming device comprises a set of LEDs arranged on a distal end of the aiming device.

[0069] The microscopic analysis device 120 in each of these examples comprises also an illumination path configured to illuminate the biological tissue, for example through the microscope objective, according to a first illumination pattern included in said elementary surface, and a detection path comprising said microscope objective 125, said detection path being configured to detect according to a detection pattern included in said elementary surface, a light beam emitted by the biological tissue in response to said illumination of the biological tissue and generate microscopic analysis information. An illumination path and a detection path of the microscopic analysis device 120 are described in relation to [Fig.2] in the case of a particular example.

[0070] In the examples shown in [Fig.lA] and [Fig.lB], the microscopic analysis device 120 comprises a mount 121 generally comprising at least a portion of the optoelectronic elements of the detection path of the microscopic analysis device and may comprise at least a portion of the optoelectronic elements of the illumination path. In certain exemplary embodiments, the optoelectronic elements may comprise, in a non-limiting manner, one or other of the following elements: a lighting source, an interferometric assembly, a detector and an associated processing unit, one or more optical systems for ensuring optical conjugations between image planes or pupil planes, one or more deflecting mirrors, one or more scanning systems, etc. The arrangement of such optical elements is known to those skilled in the art and depends on the microscopic analysis that one seeks to carry out.

[0071] In certain embodiments, a portion of said optoelectronic elements may be located outside the mount 121, such as for example a lighting source 124, for example a laser source, a detector 128, for example a camera, associated with a processing unit (not shown), making it possible to generate from a detection signal the microscopic analysis information and, optionally, one or more controllers 122 for controlling the optoelectronic elements arranged in the mount 121. The controller(s) are for example electronic cards configured to control an axial movement of the microscope objective 125 if applicable, or mirrors of a scanning system, a light source, etc. The controller(s), as well as the source 124, may be controlled by a control unit (not shown).

[0072] When the microscopic analysis device 120 is configured for confocal imaging and / or optical coherence tomographic imaging, said microscopic analysis information comprises at least one image of the biological tissue. When the microscopic analysis device 120 is configured for spectroscopic analysis, said microscopic analysis information comprises at least one spectrum of said light beam emitted by the illuminated biological tissue.

[0073] Note that in other embodiments, the lighting source of the lighting path and / or the detector of the detection path can be integrated into the mount 121.

[0074] In the examples illustrated in [Fig.lA] and [Fig.lB], separate mounts 115 and 121 are shown. Of course, in practice, in exemplary embodiments, a single mount may be provided for the arrangement of the elements of the aiming device and the microscopic analysis device.

[0075] In exemplary embodiments, as illustrated for example in [Fig.3A], an additional mount (not shown in [Fig.1A] and [Fig.1B]) may also be provided to ensure mechanical solidarity between the optical axes by securing the mounts 121, 115, the microscope objective 125 and the full-field imaging device of the aiming device.

[0076] The characterization systems 101, 102 further comprise a first processing module 130 and a second processing module 140. The first processing module 130 is configured to determine from said microscopic analysis information at least a first parameter for characterizing the biological tissue at a given number of points of said detection pattern. The second processing module 140 is configured to combine by mosaicking a plurality of elementary surface images acquired successively by moving the full-field imaging device of the viewing path and having a partial overlap, to produce a surface image of the entire region of interest.The second processing module 140 is also configured to produce at least one first mapping element of said at least one first characterization parameter, from the determination of said at least one first characterization parameter for each elementary surface image of said plurality of elementary surface images.

[0077] Generally speaking, the processing modules, processing unit or control unit referred to in the present description may comprise one or more physical entities, and may be gathered in one or more computers. When in the present description, reference is made to calculation or processing steps for the implementation in particular of method steps, it is understood that each calculation or processing step may be implemented by software, hardware, firmware, microcode or any appropriate combination of these technologies. When software is used, each calculation or processing step may be implemented by computer program instructions or software code. These instructions may be stored or transmitted to a storage medium readable by the control unit and / or be executed by the control unit in order to implement these calculation or processing steps.

[0078] The characterization systems 101, 102 further comprise a module display 150 configured to display a tissue map comprising at least said first mapping element, said map being referenced relative to said surface image, as will be explained in more detail later.

[0079] In the example of [Fig. 1B], the first optical axis and the second optical axis being merged, the identification of the mapping of said at least one characterization parameter on the surface image is simplified. However, in the example of [Fig. 1A], the mechanical solidarity of the first optical axis and the second optical axis makes it possible to identify the detection pattern in the sighting image and thus to identify the mapping of said at least one characterization parameter on the surface image of the entire region of interest.

[0080] [Fig.2] represents a diagram illustrating an example of a system for characterizing a region of interest of a biological tissue implementing a microscopic analysis of the optical coherence tomographic imaging type, for example an LC-OCT type pathway as described for example in [Ref.3].

[0081] The characterization system 200 comprises in this example a microscope objective 125 common to a microscopic analysis device 120 and to a wide-field imaging device 211 of a sighting device 110. In this example, the mount(s) are not shown. The characterization system 200 comprises, as in the previous examples, the processing modules 130, 140, for example modules of a computer 240, as well as the display module 150.

[0082] The aiming device 110 thus comprises in this example the microscope objective 125, the beam splitter element 113, a full-field illumination device 111 configured to illuminate the biological tissue in a first spectral band, a two-dimensional detector 215 with a detection area 216, and one or more imaging elements represented in [Fig. 2] by the elements 217, 218 and configured to form, with said microscope objective 125, a full-field imaging device 211 which optically combines a given effective field of the sample with the detection area 216 of the two-dimensional detector 215. The aiming device thus makes it possible to form a sighting image in surface reflection of an elementary surface whose dimensions are defined by the effective field. The two-dimensional detector 215 is connected to the processing module 140 configured to combine by mosaicking a plurality of elementary surface images.

[0083] In this example, the full-field illumination device 111 comprises a plurality of light sources arranged on a distal portion of the characterization system 200, for example on a periphery of a distal face of the microscope objective 125, the full-field illumination device allowing direct illumination of the biological tissue S. The light sources are for example light-emitting diodes emitting at wavelengths between approximately 400 nm and approximately 800 nm. Of course, other illumination devices are possible, such as a source arranged upstream of the microscope objective and a beam splitter element, for example a beam splitter cube, configured to direct an illumination beam through the microscope objective, towards the biological tissue.

[0084] In the example of [Fig. 2], the microscopic analysis device 120 comprises an illumination path configured to illuminate the sample through the microscope objective 125 according to a given illumination pattern in a second spectral band which may differ at least partially from the first spectral band. The illumination path comprises for example an illumination source 222, configured for example for the emission of a collimated light beam, a cylindrical deflecting lens or mirror 232 (for example in the case of an LC-OCT type path), a splitter element 233 (splitter cube or splitter plate) and a reflective element 234 (optional) configured to send an illumination beam emitted by the illumination source towards the microscope objective 125.The illumination path also comprises in this example a scanning device 231 of the illumination beam configured to scan the illumination beam in one or two dimensions and the separating element 113 configured to separate the viewing path and the microscopic analysis path.

[0085] The illumination source 222 may comprise, for example, a coherent (spatially), polychromatic, collimated light emission source. Optics and / or spatial filters (not shown) may make the source collimated and / or coherent and / or with a specific spectral distribution. The central wavelength of the source depends on the application, for example between 600 nm and 1500 nm and the spectral width between, for example, approximately 50 nm and 250 nm. In the case of an LC-OCT application as described, for example, in Ref. 3, the illumination source 222 may comprise, for example, and in a non-limiting manner, a supercontinuum laser spectrally filtered by an optical fiber for an emission around approximately 800 nm and collimated by an off-axis parabolic mirror.In the case of an application to full-field tomographic imaging or FF-OCT (according to the abbreviation of the English expression “Full Field OCT”), as described for example in the article by E. Beaurepaire et al. [Ref. 4]), the illumination source can be chosen to be spatially non-coherent and include means for full-field illumination of the sample, for example a Kôhler illumination system.

[0086] The cylindrical optical element 232 is optional and allows microscopy with illumination along a line (“line-field” microscopy).

[0087] The scanning device 231 of the illumination beam can be configured for a one-dimensional or two-dimensional scanning of a point or a line to form in a known manner a sectional image of the sample called “B-Scan”, that is to say in a plane parallel to the optical axis of the microscope objective, a sectional image of the sample called "C-Scan", or face image, that is to say in a plane perpendicular to the optical axis of the microscope objective, or a 3D image of the sample resulting from the acquisition of a plurality of B-Scan images or C-Scan images. As previously, the scanning device may comprise one or more scanning elements chosen from the following elements: galvanometric mirrors, polygonal mirrors, electro- or acousto-optic deflection systems, or a combination of these different elements (in the case of a two-dimensional scan). The scanning device may also include optics for combining at least one of said scanning elements with an entrance pupil of the microscope objective 125 in order, for example, to avoid vignetting.

[0088] The detection path of the microscopic analysis device is configured to detect a light beam emitted by the sample in response to said illumination of the sample, according to a given detection pattern. In this particular (non-limiting) example, the detection path comprises an interferometer for implementing optical coherence tomographic microscopy. More specifically, the interferometer comprises an object arm with the microscope objective 125, the scanning device 231 and reflective or partially reflective elements 113, 234, 233 configured to send a beam emitted by the sample S in response to said illumination of the sample to a detector 128.

[0089] The interferometer of the detection path further comprises a reference arm, separated in this example from the object arm by the separator cube 233, and comprising in a known manner a microscope objective 238 (optional), for example similar to the microscope objective 125 to ensure dispersion compensation, a dispersion compensation system (optional, not shown), a reference mirror 235, a platform 239 (optional) configured for example to move the reference mirror 235 when modulation of the optical path on the reference arm is required. The detection path further comprises in this example an objective 236 configured to optically conjugate, with the microscope objective, a plane of the sample S with a detection area of ​​the detector 128.

[0090] The detector 128 comprises in this example an optical sensor with a detection area, and may also include spatial filters for confocal detection, if this is not ensured by the dimensions of the detection area, and / or spectral filters to limit the detected wavelength band. The sensor may comprise an elementary detection surface (e.g. a photodiode) in the case of a point scanning system, a one-dimensional sensor (e.g. a linear camera) in the case of a line-field system, or a two-dimensional sensor of which only a region of interest is considered in order to act as an elementary detection area or a one-dimensional sensor. In the case of an FF-OCT application, a two-dimensional sensor mensional can be used conventionally.

[0091] In operation, interference is created at the detection area of ​​the detector 128 between the light coming from the reference arm and the light backscattered by the illuminated sample according to the illumination pattern, possibly and in a known manner with a modulation of the path difference between the reference arm and the object arm of the sample, for the formation of tomographic images, in particular face images.

[0092] A processing unit (not shown) receives, in a known manner, detection signals generated by the detector 128 and resulting from the detection of interference and is configured for the reconstruction of microscopic images from the detection signals, for example 2D sectional images (B-Scan or C-Scan). The processing unit can be connected to a storage unit (not shown) for the generated images and / or videos. The processing unit is connected to the processing module 130 configured to generate from the tomographic images a mapping of the tissue at a given number of points of said detection pattern as a function of at least one parameter for characterizing the biological tissue, as will be explained in more detail later.

[0093] Such a microscopic analysis device 120 thus functions as an optical coherence tomographic microscopy channel known from the state of the art.

[0094] Although a particular example is shown in [Fig. 2], those skilled in the art will understand that the characterization system according to the present description applies to any known state-of-the-art setup for optical coherence tomographic microscopy, the optomechanical elements shown in [Fig. 2] being able to be adapted accordingly or more generally to any known setup for the microscopic analysis of a biological tissue.

[0095] [Fig.3A] represents a diagram illustrating in a simplified manner an implementation of steps of a method for characterizing a region of interest ROI of a biological tissue S, around a suspect region 350, for example a suspect region visible on the skin, by means of a characterization system 300 according to the present description.

[0096] As in the previous examples, the characterization system 300 generally comprises a viewing device 110 and a microscopic analysis device 120, the wide-field imaging device of the viewing device 110 comprising in this example the microscope objective 125 of the microscopic analysis device and the viewing and microscopic analysis paths being separated by the separating element 113.

[0097] In this example, at least part of the elements of the aiming device and of the microscopic analysis device, including the microscope objective 125, are included in a common mount 301 equipped with a handle 302 and called a “probe” in the description. As previously, one can define a distal end of such a probe intended to come into contact or close to the tissue that one seeks to characterize, for example the skin.

[0098] In operation, the aiming device 110 allows the successive acquisition of reflection images of elementary surfaces 311 or “aiming images” of said region of interest ROI of the biological tissue S, the images of elementary surfaces being acquired successively and having a partial overlap.

[0099] For each sighting image of a plurality of said sighting images thus acquired, a microscopic analysis of the biological tissue at the sighting image is carried out by means of the microscopic analysis device 120. As described previously, the microscopic analysis comprises the illumination of the biological tissue, for example through the microscope objective, according to a first given illumination pattern included in said elementary surface and the detection, according to a detection pattern 321 included in said elementary surface, of a light beam emitted by the biological tissue in response to said illumination of the biological tissue to produce microscopic analysis information, for example an image (not shown in [Fig.3A]).

[0100] The characterization method then comprises the processing of said microscopic analysis information to determine, for each sighting image, at least a first parameter for characterizing the biological tissue at a given number of points of said detection pattern.

[0101] The characterization parameter is, for example and in a non-limiting manner: a morphological measurement (for example, presence of cellular and tissue structures in different layers of the tissue, thickness of one or more layers of the tissue), a cytological measurement (for example, a density of cell nuclei, for example, a density of keratinocyte nuclei, or an anisotropy of collagen), an optical measurement (optical density, fluorescence measurement, multiphoton measurement), a chemical measurement (Raman measurement, spectroscopic measurement), a mechanical measurement (for example, elastography), or a combination of these measurements.

[0102] The characterization parameter may also comprise a score based for example on one or more of the aforementioned measurements, possibly with a weighting. For example, such a score may express the presence or absence of lesion within the tissue, in a binary or non-binary manner (for example via a probability percentage, a number on a given scale or a binary result).

[0103] Thus, by way of example, in the example of [Fig.3A], the characterization parameter expresses the presence 332 or the absence 331 of lesion within the tissue.

[0104] The definition of the characterization parameter can also result, according to examples, in the detection of an identical property at several different depths. For example, a characterization parameter might be "greater than 70% probability of being a lesion, measured at a depth greater than 100 pm."

[0105] Note that the generation of the decision of presence / absence of lesion or of the percentage of probability can be carried out by artificial intelligence, by means of an artificial intelligence module, for example based on a deep learning model using neural networks.

[0106] Generally, such an artificial intelligence module can be used to determine a characterization parameter based on one or a combination of the aforementioned measurements.

[0107] Thus, in exemplary embodiments, a deep learning model, based on neural networks, can be used on cross-sectional images (B-Scans or C-Scans) to detect the presence of a pathology, for example a Basal Cell Carcinoma (BCC) with a score between 0 and 1. All of these scores viewed opposite form a map of the pathological areas and the healthy areas. A precise boundary can be calculated using a threshold delimiting the risk areas.

[0108] In an exemplary embodiment, a ResNet-18 model developed by Microsoft ® with a binary output is trained to predict the presence or absence of BCC on vertical section images (B-Scans). The model is used to predict on each 3D image a detection score of 0 and 1. In order to limit the risks of underestimating the lesion, a threshold can be used to define the pathological areas. The convex hull of this area can be considered as the area to be removed for the practitioner.

[0109] In another exemplary embodiment, an EfficientNet-B3 model developed by Google ® with a binary output is trained to predict the presence or absence of BCC on vertical section images (B-Scans). The model is used to predict on each 3D image a detection score of 0 and 1. In order to limit the surgery area as much as possible, a threshold can be used to define the pathological areas. The convex hull of this area can be considered as the area to be removed for the practitioner.

[0110] Furthermore, it is entirely possible to have several characterization parameters at one point (if several characterization parameters are verified at this point), for example “probability of more than 70% that it is a lesion” and “thickness of the epidermis less than 100 pm”).

[0111] [Fig.3B] thus illustrates a first example of displaying a 360 surface image of the entire region of interest ROI obtained using a method according to the present description, on which the suspect region 350 is visible. Examples of methods are described in more detail using [Fig.4] and [Fig.6]. Superimposed on the image of surface 360, we observe a first mapping element 361 of a first characterization parameter, a second mapping element 362 of a second characterization parameter and a third mapping element 363 of a third characterization parameter.

[0112] Note that in exemplary embodiments, said mapping element(s) may be displayed superimposed on another surface image of the entire region of interest (not shown in the figures), obtained by means of another imaging system and referenced relative to the 360 ​​surface image of the entire region of interest ROI obtained using a method according to the present description. Such another surface image of the entire region of interest is, for example, a dermoscopic image obtained by a dermatoscope.

[0113] [Fig.3C] illustrates a second example of displaying a 360 surface image of the entire region of interest ROI obtained using a method according to the present description, on which the suspect region 350 is visible.

[0114] In this example, the display module is configured so that the mapping of the tissue according to one or more parameters is displayed juxtaposed with said surface image of the entire region of interest. The display module is then configured to further represent in said mapping of the tissue and in said surface image of the entire region of interest, a common cursor 380. The common cursor may be a graphic element configured to locate the same spatial position on the mapping and on the surface image of the entire region of interest.

[0115] As previously, it will also be possible to envisage displaying the mapping of the tissue in a juxtaposed manner with another surface image of the entire region of interest, for example a dermoscopic image, obtained by means of another imaging system and located relative to the 360 ​​surface image of the entire region of interest ROI.

[0116] [Fig.4] illustrates in detail a diagram representing a synoptic of a first example of a characterization method according to the present description, in particular for implementing the method in an in vivo characterization of a biological tissue. The method is for example implemented with a characterization system of the type described with reference to the preceding figures. [Fig.5A], [Fig.5B] and [Fig.5C] illustrate steps of a method as described in [Fig.4].

[0117] As illustrated in [Fig.3A], in the case where the characterization system forms a probe 300 that can be manipulated by an operator, for example in the context of in vivo characterization, the method comprises a step 401 of positioning the probe 300 at the region of interest ROI of the biological tissue S that one seeks to characterize. Of course, in ex vivo characterization, a displacement relative position of the characterization system and the sample can also be done by moving the sample.

[0118] The method then comprises the successive acquisition 411, 412 of reflection images of elementary surfaces of said region of interest of the biological tissue, by means of a sighting device as described previously and comprising a two-dimensional detector and a full-field imaging device, the successively acquired elementary surface images having a partial overlap.

[0119] For example, as illustrated in [Fig.4], the method comprises (step 411) the acquisition and display by means of a display module of a first image of an elementary surface, called "target image" in the present description. Then, if the region of interest has not been entirely covered (step 431), the operator can move the probe (412) to image an elementary surface adjacent to the elementary surface previously imaged by the target device.

[0120] As illustrated in [Fig.5A], the movement can be done starting from the suspect region 350 visible to the practitioner and then moving away from the region 350 to cover the entire ROI region.

[0121] As illustrated in [Fig. 4], for each image of an elementary surface of a plurality of said images of elementary surfaces thus acquired, a microscopic analysis of the biological tissue 421 is carried out at said elementary surface, by means of a microscopic analysis device as described previously. The microscopic analysis notably comprises the illumination of the biological tissue according to a first given illumination pattern included in said elementary surface, and the detection, according to a detection pattern included in said elementary surface, of a light beam emitted by the biological tissue in response to said illumination of the biological tissue to produce microscopic analysis information.

[0122] The method then comprises processing the microscopic analysis information to determine from said microscopic analysis information at least one first parameter for characterizing the biological tissue at a given number of points of said detection pattern and produce a mapping element of the characterization parameter. As illustrated in [Fig.4], this step may more precisely comprise an analysis step 422 in which an attempt is made to identify at least one detection zone of the detection pattern for which the microscopic analysis information corresponds to at least one characterization parameter. If this is the case, the zone(s) are recorded (step 423) within the corresponding sighting image.

[0123] [Fig.5B] thus illustrates for example a plurality of sighting images (see for example 311, 312) for which the detection pattern is a detection line, respectively indicated by 321, 322. The white and gray areas respectively represent different characterization parameters.

[0124] The method then comprises combining by mosaicking 441 the surface images of the plurality of surface images to obtain a surface image of the entire region of interest. The mosaicking combination can be done by a known technique, comprising for example a registration step and a stitching step, such techniques being described for example in the article by J. Ogien et al. [Ref. 5].

[0125] [Fig.5C] thus illustrates a surface image of the entire region of interest resulting from the mosaic combination of the sight images.

[0126] Furthermore, at least one mapping element corresponding to at least one parameter is reconstructed (step 451) from the zones recorded for at least a plurality of the sighting images.

[0127] It is then possible to display (step 461) the surface image of the entire region of interest and a map comprising at least said map element, said map being located in said surface image, as shown in [Fig.3B] or in [Fig.3C].

[0128] [Fig.5D] thus schematically represents the surface image 360 ​​of the entire region of interest ROI on which is superimposed a mapping element 361 corresponding for example to the region identified as “presenting a lesion”, from the microscopic analysis information at the level of each sighting image.

[0129] [Fig.6] illustrates in detail a diagram representing a block diagram of a second example of a characterization method according to the present description.

[0130] The method comprises, as previously, a step 601 of positioning the probe at the region of interest of the biological tissue that one seeks to characterize.

[0131] The method then comprises the successive acquisition 611, 612 of reflection images of elementary surfaces of said region of interest of the biological tissue, by means of a sighting device comprising a two-dimensional detector and a full-field imaging device, as described previously, the successively acquired elementary surface images having a partial overlap.

[0132] In this example, however, the method comprises, after each step 611 of an image of an elementary surface or “sight image”, a reconstitution 641 of an image by mosaicking from the sight image acquired and the mosaic reconstituted until then during the method and the display 642 of the image mosaic. As previously, the mosaicking is carried out according to known techniques, such as those described for example in [Ref. 5].

[0133] Then, if the region of interest has not been entirely covered (step 651), the operator can move the probe (612) to image an elementary surface adjacent to the surface elementary previously imaged by the aiming device.

[0134] As illustrated in [Fig.6], for each image of an elementary surface of a plurality of said acquired elementary surface images, a microscopic analysis 621 of the biological tissue is carried out at said elementary surface, by means of a microscopic analysis device as described previously. The microscopic analysis notably comprises the illumination of the biological tissue according to a first given illumination pattern included in said elementary surface, and the detection, according to a detection pattern included in said elementary surface, of a light beam emitted by the biological tissue in response to said illumination of the biological tissue to produce microscopic analysis information.

[0135] The method then comprises processing the microscopic analysis information to determine from said microscopic analysis information at least one first parameter for characterizing the biological tissue at a given number of points of said detection pattern and producing, from a plurality of the sighting images, a mapping element of the characterization parameter. As illustrated in [Fig.6], this step may more precisely comprise an analysis step 622 in which it is sought to identify at least one detection zone of the detection pattern for which the microscopic analysis information corresponds to at least one characterization parameter. If this is the case, the zone(s) are recorded (step 623) within the corresponding sighting image.

[0136] In the method example illustrated in [Fig.6], at least one mapping element corresponding to at least one parameter is reconstructed from the areas recorded for a plurality of the sighting images.

[0137] In this example however, the method comprises more precisely, in the case 631 where zones associated with the characterization parameters have already been recorded, a step 632 of reconstituting at least one mapping element corresponding to at least one characterization parameter, from said recorded zones.

[0138] The method further comprises (step 633) the display of the mapping element(s) thus reconstituted, for example superimposed on the image mosaic or alternatively juxtaposed, as described previously. Thus, a user sees, during the characterization process, the image mosaic forming and growing as new sighting images are acquired, and superimposed or juxtaposed on the mosaic, the mapping element(s).

[0139] It is thus possible for a practitioner to have an overview of the acquisition and therefore to better orient themselves, for example, in relation to a wide-field image previously acquired by dermoscopy, for example. In addition, this configuration potentially also makes it possible to display the mapping in real time, and therefore allows the practitioner to make decisions based on the mapping during the acquisition (e.g. example of going in a particular direction during the acquisition, or of stopping to directly extract a part of the tissue based on the information provided by the mapping).

[0140] When the entire region has been covered (step 651), the image of the entire region of interest obtained by mosaicking during the process is recorded (step 661) as well as the reconstitution (step 662) of at least one map corresponding to at least one characterization parameter, from the map elements recorded during the process.

[0141] Although described through a certain number of exemplary embodiments, the systems and methods for characterizing a region of interest of a biological tissue according to the present description include various variations, modifications and improvements which will be obvious to those skilled in the art, it being understood that these various variations, modifications and improvements are part of the scope of the invention as defined by the following claims. References

[0142] Ref. 1: A. Alfonso-Garcia et al. “Real-time augmented reality for delineation of surgical margins during neurosurgery using autofluorescence lifetime contrast”, J Bio-photonics, 2020 Jan;13(l):e201900108

[0143] Ref 2: WO2020087164

[0144] Ref. 3: Published patent application WO2015092019

[0145] Ref. 4: E. Beaurepaire et al. "Full-field optical coherence microscopy" Opt. Lett. 23, 244-246 (1998)

[0146] Réf. 5 : Ogien et al., "Video-mosaicking ofhuman skin in vivo using handheld line-field confocal optical cohérence tomography" Proc. SPIE 11211, Photonics in Der-matology and Plastic Surgery 2020, 1121114 (19 February 2020) /

Claims

1. Claims System for characterizing (101, 102, 200) a region of interest (ROI) of a biological tissue (S), comprising: - a sighting device (110) comprising: - a full-field illumination device (111) configured to illuminate the biological tissue in a first spectral band; - a two-dimensional detector (215) comprising a detection area (216); - a full-field imaging device (211) comprising a first optical axis (AJ) and configured to optically conjugate an elementary surface of the biological tissue with said detection area of ​​the two-dimensional detector, the two-dimensional detector producing, in operation, a reflection image of said elementary surface; - a microscopic analysis device (120) comprising: - a microscope objective (125) comprising a second optical axis (A2), mechanically secured to the first optical axis; - a lighting path configured to illuminate the biological tissue according to a first lighting pattern included in said elementary surface, and in a second spectral band; - a detection path comprising said microscope objective, said detection path being configured to detect, according to a detection pattern included in said elementary surface, a light beam emitted by the biological tissue in response to said illumination of the biological tissue and generate microscopic analysis information; - a first processing module (130) configured to determine from said microscopic analysis information at least one first parameter for characterizing the biological tissue at a given number of points of said detection pattern; - a second processing module (140) configured to - combining by mosaicking a plurality of elementary surface images acquired successively by moving the full-field imaging device of the viewing path and having partial overlap, to produce a surface image of the entire region of interest and - produce at least one first mapping element of said at least one first characterization parameter, from the determination of said at least one first characterization parameter for at least a portion of the elementary surface images of said plurality of elementary surface images; - a display module (150) configured to display a mapping of the tissue comprising at least said first mapping element, said mapping being referenced relative to said surface image.

2. The characterization system of claim 1, wherein the display module is configured to further display said surface image of the entire region of interest or another surface image of the entire region of interest acquired by another imaging system and referenced to said surface image of the entire region of interest.

3. The characterization system of claim 2, wherein the display module is configured to display said tissue mapping superimposed on said surface image of the entire region of interest or said other surface image of the entire region of interest.

4. A characterization system according to any one of claims 2 or 3, wherein the display module is configured so that said tissue map is displayed juxtaposed with said surface image of the entire region of interest or with said other surface image of the entire region of interest, the display module being configured to further represent a common cursor in said tissue map and in said surface image of the entire region of interest or in said tissue map and in said other surface image of the entire region of interest.

5. A characterization system according to any preceding claim, wherein the full-field imaging device of the aiming device comprises said microscope objective.

6. Characterization system according to any one of the preceding claims, wherein said at least one first parameter for characterizing the biological tissue comprises a parameter chosen from: a morphological measurement, a cytological measurement, an optical measurement, a measurement characterizing a chemical composition, a mechanical measurement, a combination of these measurements, a score for characterizing the state of the tissue, for example based on at least one of these measurements.

7. Characterization system according to any one of the preceding claims, wherein said first module for processing said microscopic analysis information comprises an intelligence module artificial intelligence based on a deep learning model using neural networks.

8. A characterization system according to any preceding claim, wherein said microscopic analysis device is configured for confocal imaging and / or optical coherence tomographic imaging and said microscopic analysis information of the biological tissue comprises at least one image of the biological tissue.

9. A characterization system according to any one of claims 1 to 7, wherein said microscopic analysis device is configured for spectroscopic analysis and said microscopic analysis information of the biological tissue comprises at least one spectrum of said light beam emitted by the biological tissue.

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