A procedure for the morphological treatment of microwave radar images in the medical field that uses different hypotheses about the medium traversed by microwave signals
Patent Information
- Application Number
- ES2022724823T
- Authority / Receiving Office
- ES · ES
- Patent Type
- Patents
- Current Assignee / Owner
- Filing Date
- 2022-05-04
- Publication Date
- 2026-08-31
- Estimated Expiration
- 2042-05-04
Smart Images
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Abstract
Description
Morphological treatment procedure for microwave radar images in the medical field that uses different hypotheses about the medium traversed by microwave signals TECHNICAL FIELD The invention relates to the field of medical imaging using electromagnetic waves in the microwave frequency band and more particularly to medical imaging for the analysis of human tissues or organs permeable to electromagnetic waves. The invention finds particular application in breast imaging and the detection of breast pathologies. STATE OF THE ART Microwave imaging techniques allow for the imaging of human organs permeable to electromagnetic waves and are promising techniques in the field of breast imaging and the detection of pathologies such as breast cancers. Microwave imaging employs emitting probes configured to illuminate all or part of the organ to be imaged using electromagnetic waves. The emitted waves pass through the area to be imaged and are received by receiving probes. These probes can also be configured to both emit and receive simultaneously. The received waves have passed through the area to be imaged, reflecting off obstacles encountered at points of dielectric contrast (for example, a cancerous lesion located within healthy tissue). The sum of the transmission coefficients thus measured between the emitting and receiving probes forms a multistatic acquisition. These multistatic acquisitions serve as input for radar imaging processing modules, enabling the creation of a 2D or 3D radar image of the organ or a portion thereof.To obtain images that best represent the area to be imaged, it is necessary to know in advance the dielectric medium along the different paths traveled by the electromagnetic waves between the emission probes, each point of the considered area to be imaged, and the reception probes. However, this prior knowledge of the dielectric properties of the organs to be imaged is not available and requires formulating hypotheses about the medium traversed, which leads to images that may be of poor quality. US2013 / 018591 A1 (GRZEGORCZYK TOMASZ M [US]) (2013-01-17) discloses a microwave imaging apparatus that uses an antenna beam to collect electromagnetic field information for a material being examined by imaging. An image processing procedure and device utilize the discrete dipole approximation (DDA) and drastically reduce the time required for processing the measured data and estimating the properties of the interrogated material. An initial assessment of the material properties is performed, and the acquired field is estimated. These results are compared with the measured results, and incremental changes in the material properties are calculated. The updated material properties are then used to recalculate the field. Document CN 111067524 A (UNIV TIANJIN) (2020-04-28) discloses a procedure for estimating the average dielectric properties of microwave breast imaging. The procedure comprises the following steps: stretching each breast MRI image source, discretizing each breast tissue, adding a skin layer referencing the breast contour, and establishing a three-dimensional breast model through interpolation; defining a tumor position and tumor radius in a three-dimensional breast model; deploying an antenna array on the skin surface; performing a point source substitution; allowing each antenna to emit signals sequentially; allowing the other antennas to receive signals; and subjecting all received signals to imaging using a confocal algorithm; and obtaining a corresponding average breast dielectric constant. US patent 2005 / 107692 A1 (LI JIAN [US] ET AL) (2005-05-19) discloses a system for examining biological tissue, which consists of irradiating a tissue area with a plurality of hyperfrequency radiation pulses. The hyperfrequency pulses are swept across a range of microwave frequencies. In response to the swept hyperfrequency pulses, the tissue area emits a plurality of thermoacoustic signals. An image of the tissue area is then formed from the plurality of thermoacoustic signals. US patent 2019 / 175095 A1 (BORE CHRIS [GB]) (2019-06-13) discloses a medical imaging system comprising a hyperfrequency antenna array: transmitting and receiving antennas separated from each other. The microwave antenna array has several configurations that define the positions of the antennas with respect to the body part. The medical imaging system further comprises an actuator designed to move the microwave antenna array between the configurations and a processor configured to obtain a data set for the microwave signals produced in each of the microwave antenna array configurations and to generate an output indicative of the internal structure of the body part from a concatenation of the data sets. The paper "Super-resolution radar imaging for breast cancer detection with microwaves: the integrated information selection criteria," by Fasoula A. et al., presented at the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, July 23, 2019 (2019-07-23), pages 1868-1874, discloses a data preprocessing scheme for frequency selection and spatial filtering modules integrated into a TR-MUSIC (Time-Reversal Multiple Signal Classification) algorithm for microwave breast imaging. A novel frequency selection scheme is proposed, such that the TR-MUSIC imaging algorithm is applied to the discrete frequencies that transmit most of the useful information from within the breast.A sub-image selection criterion, based on the balance of image intensity between the exterior and interior of the breast, further strengthens the robustness of the imaging system against residual coupling or other sources of interference. Finally, a spatial filtering approach is presented that limits the contribution of each sensor sector (subset) to its neighborhood (i.e., the area best illuminated by the given antenna array). EXPLANATION OF THE INVENTION The invention improves the quality of radar images for the analysis of human tissues or organs. Specifically, it allows for the detection of one or more regions of interest in radar images, corresponding to physical objects that may be lesions. To that effect, the invention proposes, according to a first aspect, a medical image processing procedure according to claim 1. The invention is advantageously complemented by the following features, taken alone or in any of their technically possible combinations: - Morphological treatment consists of determining the solidity of one or more pixel regions of the image, identifying a region of interest if the associated solidity is above a threshold. - at least N=2 sets, preferably at least N=3 sets of Ai > 1 values, 1 i N, of characteristic parameter (pcfib) of the medium traversed by the signals are considered. - The sets overlap totally or partially in terms of variation intervals and / or in terms of values. - The persistence assessment consists of determining a percentage of presence of a region of interest in the morphological images, a region of interest being validated for a percentage higher than a threshold. - The probe network comprises K > 1 probes arranged around the area to be imaged, said network being mobile according to vertical positions around the area to be imaged, each configuration being an angular sector of probes composed of M > 1 probes with M < K, each configuration being angularly displaced by at least one probe with respect to another configuration; for each sector, each of the probes emits in turn so as to produce the signals acquired for the configuration, determining an elementary radar image for each angular sector by set of characteristic parameter values. According to a second aspect, the invention proposes a computer program product comprising program code instructions for the execution of the steps of the procedure according to the first aspect of the invention, when this procedure is executed by at least one processor. According to a third aspect, the invention proposes a medical imaging device comprising a processing unit configured to implement a procedure according to the first aspect of the invention. The combination of several configurations and the use of various characteristic values of the traversed medium as a hypothesis allows for managing the heterogeneity of the dielectric properties of the area to be imaged, which are not known a priori. Furthermore, the persistence of a morphologically identified region of interest for at least B > 1 sets among N sets (with B / N 1) implies a validation of the region of interest, i.e., a high probability that it corresponds to a physical object / injury present in the imaged area versus an artifact. Additionally, the solidity criterion used is a shape descriptor that allows for an advantageous morphological identification of the regions of interest. PRESENTATION OF THE FIGURES Other features, objectives, and advantages of the invention will become apparent from the following description, which is purely illustrative and not limiting, and which should be read in conjunction with the accompanying drawings, in which: - Figure 1 schematically illustrates a microwave medical imaging system according to one embodiment of the invention; - Figure 2 illustrates stages of a microwave radar image morphological processing procedure according to the invention; - Figure 3 illustrates a microwave radar image obtained during a procedure according to the invention; - Figure 4a, Figure 4b, Figure 4c, Figure 4d and Figure 4e illustrate morphological breast images of a patient, obtained by means of a microwave radar morphological image processing procedure according to the invention. - Figure 5a, Figure 5b, Figure 5c and Figure 5d illustrate morphological breast images of a patient, obtained by a microwave radar morphological image processing procedure according to the invention. In all figures, similar elements carry identical references. DETAILED DESCRIPTION Figure 1 illustrates a microwave medical imaging device 1 comprising an examination table 11 on which a patient 12 is lying. In particular, the patient 12 is lying in the prone position. The examination table 11 comprises an opening 13, preferably circular, which allows the immersion of the patient's breast 14 in a tank 15 filled with a biocompatible transition fluid whose dielectric properties are optimized to improve the transmission of electromagnetic waves within the breast. A network 16 of electromagnetic wave emitters 161 in the microwave range (shown below with dashes) is arranged around the tank 15. In transmission, it illuminates the observed medium, and in reception, it receives the signals reflected from the scene to be imaged. The probes 161 are advantageously distributed regularly around the tank, preferably in a ring surrounding it, as illustrated in Figure 1. Advantageously, the probes are configured to emit signals in the 0.5–6 GHz frequency band. More generally, the imaging system operates in a multi-static manner, allowing the area to be imaged to be illuminated by using multiple transmitting and receiving probes in different configurations around the area. The probes can also be configured to transmit and receive simultaneously. In each multistatic acquisition, all or part of the area to be imaged is successively illuminated by preselected probes operating in transmit mode. The transmitting probes in the network and their number are chosen based on the breast area to be imaged. For each transmitting probe, the signal is received by preselected receiving probes. The receiving probes in the network and their number are chosen based on the breast area to be imaged. Each multistatic acquisition is therefore considered to correspond to a series of signal transmissions / receptions by probes according to a specific configuration. The configuration is thus understood as the definition of a set of emitting probes and the definition of a set of receiving probes that allow a multistatic acquisition of all or part of the breast, with said probes arranged in a certain way in the space around the breast. To switch between configurations and control the various multi-static acquisitions, the system comprises a probe network control unit 17 connected to a control and processing unit 18 (e.g., a processor and / or a computer). This control and processing unit 18 is configured to control the network, perform acquisitions, ensure the storage of acquired data, carry out radar image processing, and implement a morphological image processing procedure, which will be described later. A storage unit 19 stores the entire set of acquired multi-static data and a certain amount of data that can be used in the image processing stages or generated by the image processing. Additionally, a display unit 20 displays and visualizes the acquired images.The control and processing unit 18, the storage unit 19, and the display unit 20 can be integrated directly into the imaging device or physically located elsewhere. Image processing can be performed offline. As you may have understood, to obtain images of the entire breast, several successive configurations of transmitting and receiving probes are defined. These configurations cover different areas of the breast to be imaged and are chosen so that, ultimately, they encompass the entire breast to be imaged. For each configuration, the multistatic acquisitions of the transmission coefficients between the emitting and receiving probes allow, after radar image processing, obtaining an elementary radar image. The set of elementary images obtained allows for the reconstruction of a 2D or 3D radar image of the imaged area, in this case, the breast. For information on the radar processing of the multistatic emission / reception signals that enable the reconstruction of 2D or 3D radar images, please refer, for example, to the following publications: - AJ Devaney, Time reversal imaging of obscured targets from multistatic data, IEEE Trans. Propag. Antennas (2005) . doi:10.1109 / TAP.2005.846723; - Marengo, EA; Gruber, F.K. Simonetti, F. Time-reversal MUSIC imaging of extended targets. IEEE Trans. Image Process.2007, 16, 1967-1984. doi:10.1109 / TIP.2007.899193; -Hossain, MD; Mohan, AS Cancer Detection in Highly Dense Breasts Using Coherently Focused Time-Reversal Microwave Imaging. IEEE Trans. Comput. Imaging 2017, 3, 928-939. doi:10.1109 / TCI.2017.2737947.- A. Fasoula, BM Moloney, L. Duchesne, JDG Cano, BL Oliveira, J. Bernard, MJ Kerin, Super-resolution radar imaging for breast cancer detection with microwaves: the integrated information criteria selection, in: 41st Annu. Int. Conf. IEEE Eng. Med. Biol. Soc., 2019. The 2D or 3D radar images obtained are advantageously exploited within the framework of a processing procedure that will be described below. As mentioned in the introduction, determining each elementary radar image theoretically requires knowing in advance the dielectric medium of the surface (i.e., the medium traversed) along the path between each transmitting probe and each receiving probe. However, this information is not available. As will be described, the invention implements a parameter pcfib that corresponds to a hypothesis about the average composition of the medium traversed by the electromagnetic wave in the breast (or, more generally, the imaged area) in terms of dielectric permittivity. This parameter pcfib corresponds to a percentage mixture of fibroglandular and adipose tissue in the breast. For example, pcfib = 30% corresponds to a medium containing 30% fibroglandular tissue and 70% adipose tissue. The dielectric properties of the breast tissue are then defined as a weighted average (pcfib weighting) of the dielectric properties of the fibroglandular and adipose tissues. For examples of dielectric permittivity values for fibroglandular and adipose tissue in the breast, reference may be made, for example, to the following publications: - T. Sugitani, SI Kubota, SI Kuroki, K. Sogo, K. Arihiro, M. Okada, T. Kadoya, M. Hide, M. Oda, T. Kikkawa, Complex permittivities of breast tumor tissues obtained from cancer surgeries, Appl. Phys. Lett. (2014) doi:10.1063 / 1.4885087; - M. Lazebnik, L. McCartney, D. Popovic, CB Watkins, MJ Lindstrom, J. Harter, S. Sewall, A. Magliocco, JH Booske, M. Okoniewski, SC Hagness, Phys. Med. Biol. (2007) doi:10.1088 / 0031–9155 / 52 / 10 / 001. Below, a morphological treatment procedure of microwave radar images in relation to Figure 2 is described. Initially, (n) P > 1 configuration(s) of the probe network (stage E0) is defined, so that the entire breast to be imaged can be covered and a 3D radar image of the breast can be subsequently reconstructed. Next, for each configuration, a multi-static acquisition of the transmission coefficients measured between the transmitting and receiving probes is performed (stage E1). Several multi-static acquisitions are then available (P > 1 multi-static acquisitions). Next, the signals acquired for each configuration are processed to obtain elementary microwave radar images for each of the configurations (E2 stage). In particular, to process these signals, several sets (N > 1 sets) of Ai values (Ai > 1 values, with 1 ≤ i ≤ N) of the pcfib parameter are considered. Values of the pcfib parameter are then obtained by configuration. Thus, elementary microwave radar images are obtained from the signals of each multistatic acquisition, each of which has been obtained for a specific value of the pcfib parameter. The idea here is to obtain elementary images according to different hypotheses about the medium traversed by the electromagnetic waves. Advantageously, the sets of values for the pcfib parameter overlap totally or partially in terms of variation and / or in terms of values. For example, you can have one set comprising the values 10% and 20%, and another set comprising the values 5%, 15%, and 25%. In this example, we have one set whose values range between 10% and 20%, and another set whose values range between 5% and 25%. These two sets therefore share a common range of variation between 10% and 20%. In another example, we can have one set comprising the values 10%, 20% and another set comprising the values 20%, 25%, 30%. In this example, the sets have one value in common: 20%. In yet another example, we can have one set comprising the values 10%, 20%, and 25%, and another set comprising the values 5%, 10%, and 30%. In this example, these two sets share a common range of variation between 10% and 25% and a common value of 10%. At least two sets of values for the parameter pcfib are considered, one set of which may have a wider range of variation for the pcfib values than the other set. Here, the terms "wide" and "narrow" are relative terms that are understood by comparing the ranges of variation. The idea here is to have overlaps between the sets of values. The choice of the variation intervals of the pcfib parameter for the different sets is made in relation to the variability existing in terms of breast compositions and density. Advantageously, wide variation intervals lead to images that comprise a more complete representation of the region of interest, and narrow variation intervals potentially lead to partial representations of detectable lesions. For example, within the breast image framework, N=5 sets of variation can be chosen: - three sets with narrow ranges of variation: between 10% and 20%, taking the pcfib parameter, for example, the following values in this interval: 10%, 15%, 20% between 30% and 40%, taking the pcfib parameter, for example, the following values in this interval: 30%, 35%, 40% between 50% and 60%, taking the pcfib parameter, for example, the following values in this interval: 50%, 55%, 60% - two sets with wide ranges of variation: between 20% and 50%, taking the pcfib parameter, for example, the following values in this interval: 20%, 25%, 30%, 35%, 40%, 45%, 50% between 10% and 60%, taking the pcfib parameter, for example, the following values in this interval: 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%. For each configuration, an elementary microwave radar image is selected for each set (stage E3) and corresponds to one of the values of the parameter (pcfib) for the set; therefore, for each configuration, one elementary image is selected per set. Such a selected image is likely to contain a region of interest corresponding to a physical object, potentially a lesion. In the example above, there are then five elementary images per configuration (one elementary image per set) that will be used for reconstruction. This selection consists specifically of using at least one of the image focusing metrics, such as, for example, the criteria described in the following documents (a combination of several criteria may be used): - S. Pertuz, D. Puig, MA Garcia, Analysis of focus measurement operators for shape-from-focus, Pattern Recognit. (2013) . Doi:10.1016 / j.patcog.2012.11.011. - O'loughlin, D.; Krewer, F.; Glavin, M.; Jones, E.; O'halloran, M. Focal quality metrics for the objective evaluation of confocal microwave images. Int. J. Microw. Wirel. Technol. 2017, 9, 1365-1372. Doi:10.1017 / S1759078717000642. Each selected image may contain one or more regions of interest, a selection made according to at least one image focus criterion. In effect, the selection is performed using one or more focus criteria. For example, for a given criterion, the image that yields the minimum metric value, among all others for that criterion, is selected. It is observed that, from one configuration to another, the selection of the elementary image for the same given set may have been carried out with different values of the pcfib parameter belonging to that set. From the elementary images obtained for the different configurations, a 2D or 3D radar image of the imaged area is reconstructed for each of the sets (stage E4). Thus, a radar image reconstructed for each set of pcfib values is available. Each microwave radar image thus reconstructed from the imaged area undergoes morphological processing to detect regions of interest, if any (step E5). The resulting microwave morphological image contains none, one, or several identified regions of interest. This morphological processing consists specifically of identifying connected objects in the image using a thresholding procedure and retaining as regions of interest those connected objects that correspond to a set of morphological characteristics, in particular, the volumetric size of the connected object, the level of solidity of the connected object, the intensity level within the connected object, and the contrast level between the intensity within the connected object and the intensity within other potentially identified connected objects in the same image.At this stage, several morphological images of the breast are available, each morphological image being obtained by a set of pcfib values; each morphological image contains none, one or several identified regions of interest. Preferably, morphological treatment is based on the solidity criterion. Solidity is calculated as the ratio between the volume of the object and the volume of its convex hull. In general, the greater the solidity of a region of interest, the more "filled" that region of interest will be (a region of interest without gaps), the more well-defined and convex its contour will be, and therefore the greater the likelihood that it corresponds to a mass. In the case of breast imaging, this solidity criterion can be used to support the differentiation between a breast mass and a focal asymmetry ("island" of normal breast tissue, without a defined convex outer border). This notion of a well-defined and convex contour of a solid breast mass is explained, for example, in the following publications: - TF de Brito Silva, AC de Paiva, AC Silva, G. Braz Júnior, JDS de Almeida, Classification of breast masses in mammograms using geometric and topological feature maps and shape distribution, Res. Biomed. Eng. (2020) . doi:10.1007 / s42600-020-00063-x; - N. Safdarian, M. Hedyezadeh, Detection and Classification of Breast Cancer in Mammography Images Using Pattern Recognition Methods, Multidiscip. Cancer Research (2019) . doi:10.30699 / acadpub.mci.3.4.13. In practice, the robustness of a region of interest must exceed a given level in order for that region of interest to be identified in a morphological image of a given set. Next, the persistence of each previously identified region of interest is evaluated across different morphological images. The goal is to morphologically validate the regions of interest that are persistent for various hypotheses about the medium traversed by the electromagnetic waves (stage E6). Persistence evaluation refers to the presence of a 3D-located region of interest in the same area across multiple morphological images. Here, we will assess whether the regions of interest identified by the morphological analysis are present in several images within the same area. This evaluation primarily involves using criteria such as spatial clustering to associate the detected regions of interest with one another. Persistence therefore allows for the morphological validation of the region of interest, that is, its association with a physical object if the region of interest is present in a certain proportion of the number of morphological images. As mentioned, at least two sets of pcfib values are advantageously considered, and preferably at least three sets. This is important for implementing the persistence assessment stage. A region of interest is considered valid if it persists across multiple morphological images. In the case of two sets, the region of interest must be present in both images to be valid. In the case of three sets, the region of interest must be present in either two out of three images or three out of three images to be valid. In general, a region of interest will be considered persistent if it is present in at least a percentage of morphological images that must be defined according to the type of region sought. These regions of interest, validated through persistence, then have a high probability of corresponding to a real lesion or tumor, rather than an artifact, for example. This persistence can be associated with a degree of confidence at the detection level. Additionally, the imaging system comprises a horizontal circular array of K > 1 measuring probes positioned around a cylinder of dielectric material. The circular array can be moved along the vertical axis. The organ under examination (breast) is placed inside the cylinder and is therefore surrounded by this array. A dielectric transition medium within the cylinder where the breast is positioned optimizes the penetration of the electromagnetic waves emitted by the probes into the breast. The vertical positions of the array are predefined, with constant or variable distance intervals between each position, and cover the vertical extent of the breast. Multistatic measurements are performed for each of the vertical positions of the probe network. As an example of the implementation of the acquisition stage, consider L > 1 angular sectors each composed of M > 1 probes from the probe network (M < K). For example, L=18 angular sectors of M=6 probes with, in this case, each sector angularly displaced relative to each other by R=1 probe along the contour of a network of K=18 probes. For each of the M=6 probe angular sectors, each probe transmits in turn, and for each transmitting probe, the other probes in the angular sector successively receive the signal corresponding to the echoes from the obstacles encountered, especially in the breast. The set of transmission coefficients measured between the transmitting and receiving probes of the considered angular sector constitutes a multistatic acquisition. This multistatic acquisition is repeated for the set of L=18 M=6 probe angular sectors. Then, the vertical grid is shifted one interval along the vertical axis, and the multistatic measurements are repeated again for the different angular sectors. A grid configuration corresponds to an angular sector in a given vertical position. Angular sector acquisitions allow imaging around the breast by formulating various hypotheses about the pcfib values in each angular sector at each vertical position. This optimally accounts for the variable and heterogeneous structure of the breast in terms of dielectric properties, which can change depending on the viewing position, and reveals the non-uniform angular response of breast lesions. Thus, the sectorization of the area to be imaged is leveraged in combination with the different hypotheses about the pcfib parameter to improve the detection of regions of interest. Types of images obtained with the invention Figure 3 illustrates a reconstructed microwave radar image for a set of pcfib values such that 10% pcfib ≤ 60%. This radar image is represented in the coronal view of the breast. In this radar image, several pixel regions stand out in terms of intensity. The objective of morphological treatment is to process this type of radar image to identify regions of interest that could correspond to suspicious areas. Figures 4a, 4b, 4c, 4d, and 4e illustrate various morphological images of a patient's breast, obtained after morphological processing of reconstructed microwave radar images for five sets of pcfib parameter values. These morphological images are represented in the coronal view of the breast. In this example, the morphological images correspond to five sets of pcfib parameter values: - Figure 4a: 10% pcfib, 60% - Figure 4b: 20% pcfib 50% - Figure 4c: 10% pcfib 20% - Figure 4d: 30% pcfib 40% - Figure 4e: 50% pcfib 60% Regarding the radar image in Figure 3, morphological processing allowed the identification of a single region of interest. This region of interest is consistent across all five morphological images and is therefore validated. It should be noted that the identified region of interest has different contours in each morphological image, confirming that the microwave radar signature of the detected object varies depending on the sets of pcfib values considered. Figures 5a, 5b, 5c, and 5d illustrate morphological images of another patient's breast obtained after morphological processing of reconstructed microwave radar images, also for five sets of pcfib parameter values. These five sets of values are identical to those considered in the previous figures (the previous patient). In this example, the morphological processing identified a single region of interest that was persistent in four of the five morphological images. This region of interest is therefore validated. The fifth morphological image, corresponding to the set of values 10% pcfib 20%, is not shown because no persistent region of interest was identified in it. Unlike the previous example, the identified region of interest is presented as a constellation, but it remains a single, unified object connected according to the previously applied treatments.This illustrates that the microwave radar signature of the detected object varies significantly depending on the sets of pcfib values considered. The region of interest corresponds to a lesion with a distributed shape, highly irregular shape, and a highly heterogeneous texture.
Claims
1. A method for processing medical images of human tissue from a patient's body area, and in particular the breast, by means of a medical imaging device (1) comprising a network of electromagnetic wave emitting / receiving probes in the microwave range consisting of K > 1 probes separated from each other, the network P > 1 comprising different configurations defining emitting probes and receiving probes for one or more positions around the area, wherein the emitting probes are configured to emit microwave signals so as to illuminate a body area and the receiving probes are configured to receive microwave signals after diffusion and reflection in the area, the probes being complementaryly configured to emit and receive simultaneously,the procedure comprising the following steps implemented in a processing unit of the medical imaging device: - acquiring (E1) the signals produced in P > 1 antenna array configurations; - the procedure comprising for each configuration: - processing (E2) the signals acquired for N > 1 sets of Ai > 1 values, 1 i N, of a characteristic parameter (pcfib) of the dielectric properties of the human tissues traversed by the signals, so as to obtain elementary microwave radar images; - selecting (E3) , in each of the N sets according to at least one image focusing criterion, an elementary microwave radar image, each selected elementary image corresponding to one of the values of the parameter (pcfib) of the set; one elementary image being selected per set for a configuration; - the procedure comprising for each set: - reconstructing (E4) ,From the selected elementary radar images of each configuration, a radar image of a patient's body area is reconstructed to create a 3D radar image for each set; the procedure being characterized in that it further comprises, for each set: - morphologically treating (E5) each reconstructed radar image to obtain a morphological image in which one or more regions of interest, if any, are identified as potentially containing a lesion; - evaluating (E6) the persistence of each region of interest in the different morphological images obtained to morphologically validate the region of interest, the persistence evaluation consisting of assessing whether the regions of interest are present in several morphological images within the same area.
2. The procedure according to claim 1, wherein the morphological treatment (E5) consists of determining the solidity of one or more pixel regions of the image.
1. A region of interest is identified if the associated solidity exceeds a threshold.
2. A processing method according to any of the preceding claims, wherein at least N=2 sets, preferably at least N=3 sets, of Ai > 1 values, 1 ≤ N, of the characteristic parameter (pcfib) of the medium traversed by the signals are considered.
3. A method according to claim 3, wherein the sets overlap totally or partially in terms of variation intervals and / or values.
4. A method according to any of the preceding claims, wherein the persistence assessment consists of determining a percentage of presence of a region of interest in the morphological images, a region of interest being validated for a percentage exceeding a threshold.
5. A method according to any of the preceding claims, wherein the probe network comprises K > 1 probes arranged around the area to be imaged.said mobile network being arranged in vertical positions around the area to be imaged, each configuration being an angular sector of probes composed of M > 1 probes with M < K, each configuration being angularly displaced by at least one probe with respect to another configuration; for each angular sector, each of the probes emits in turn so as to produce the acquired signals for the configuration, determining an elementary radar image for each angular sector by a set of characteristic parameter values (pcfib).
7. Computer program product comprising program code instructions for executing the steps of the procedure according to any one of claims 1 to 6,when this procedure is executed by at least one processor.
8. Medical imaging device comprising a processing unit configured to implement a procedure according to any one of claims 1 to 6.