Automated Stabilization, Enhancement and Capillaries Segmentation in Videocapillaroscopy

Oral capillaroscopy is a critical and non-invasive technique used to evaluate microcirculation. Its ability to observe small vessels in vivo has generated significant interest in the field. Capillaroscopy serves as an essential tool for diagnosing and prognosing various pathologies, with anatomic–pathological lesions playing a crucial role in their progression. Despite its importance, the utilization of videocapillaroscopy in the oral cavity encounters limitations due to the acquisition setup, encompassing spatial and temporal resolutions of the video camera, objective magnification, and physical probe dimensions. Moreover, the operator’s influence during the acquisition process, particularly how the probe is maneuvered, further affects its effectiveness. This study aims to address these challenges and improve data reliability by developing a computerized support system for microcirculation analysis. The designed system performs stabilization, enhancement and automatic segmentation of capillaries in oral mucosal video sequences. The stabilization phase was performed by means of a method based on the coupling of seed points in a classification process. The enhancement process implemented was based on the temporal analysis of the capillaroscopic frames. Finally, an automatic segmentation phase of the capillaries was implemented with the additional objective of quantitatively assessing the signal improvement achieved through the developed techniques. Specifically, transfer learning of the renowned U-net deep network was implemented for this purpose. The proposed method underwent testing on a database with ground truth obtained from expert manual segmentation. The obtained results demonstrate an achieved Jaccard index of 90.1% and an accuracy of 96.2%, highlighting the effectiveness of the developed techniques in oral capillaroscopy. In conclusion, these promising outcomes encourage the utilization of this method to assist in the diagnosis and monitoring of conditions that impact microcirculation, such as rheumatologic or cardiovascular disorders

Review on Photomicrography based Full Blood Count (FBC) Testing and Recent Advancements

With advancements in related sub-fields, research on photomicrography in life science is emerging and this is a review on its application towards human full blood count testing which is a primary test in medical practices. For a prolonged period of time, analysis of blood samples is the basis for bio medical observations of living creatures. Cell size, shape, constituents, count, ratios are few of the features identified using DIP based analysis and these features provide an overview of the state of human body which is important in identifying present medical conditions and indicating possible future complications. In addition, functionality of the immune system is observed using results of blood tests. In FBC tests, identification of different blood cell types and counting the number of cells of each type is required to obtain results. Literature discuss various techniques and methods and this article presents an insightful review on human blood cell morphology, photomicrography, digital image processing of photomicrographs, feature extraction and classification, and recent advances. Integration of emerging technologies such as microfluidics, micro-electromechanical systems, and artificial intelligence based image processing algorithms and classifiers with cell sensing have enabled exploration of novel research directions in blood testing applications.

assessment of blood capillaries and structural proteins localization

The papillary dermis of human skin is responsible for its biomechanical properties and for supply of epidermis with chemicals. Dermis is mainly composed of structural protein molecules, including collagen and elastin, and contains blood capillaries. Connective tissue diseases, as well as cardiovascular complications have manifestations on the molecular level in the papillary dermis (e.g. alteration of collagen I and III content) and in the capillary structure. In this paper we assessed the molecular structure of internal and external regions of skin capillaries using two-photon fluorescence lifetime imaging (FLIM) of endogenous compounds. It was shown that the capillaries are characterized by a fast fluorescence decay, which is originated from red blood cells and blood plasma. Using the second harmonic generation signal, FLIM segmentation was performed, which provided for spatial localization and fluorescence decay parameters distribution of collagen I and elastin in the dermal papillae. It was demonstrated that the lifetime distribution was different for the inner area of dermal papillae around the capillary loop that was suggested to be due to collagen III. Hence, we propose a generalized approach to two-photon imaging of the papillary dermis components, which extends the capabilities of this technique in skin diagnosis

Multi-dimensional local binary pattern texture descriptors and their application for medical image analysis

Texture can be broadly stated as spatial variation of image intensities. Texture analysis and classification is a well researched area for its importance to many computer vision applications. Consequently, much research has focussed on deriving powerful and efficient texture descriptors. Local binary patterns (LBP) and its variants are simple yet powerful texture descriptors. LBP features describe the texture neighbourhood of a pixel using simple comparison operators, and are often calculated based on varying neighbourhood radii to provide multi-resolution texture descriptions. A comprehensive evaluation of different LBP variants on a common benchmark dataset is missing in the literature. This thesis presents the performance for different LBP variants on texture classification and retrieval tasks. The results show that multi-scale local binary pattern variance (LBPV) gives the best performance over eight benchmarked datasets. Furthermore, improvements to the Dominant LBP (D-LBP) by ranking dominant patterns over complete training set and Compound LBP (CM-LBP) by considering 16 bits binary codes are suggested which are shown to outperform their original counterparts. The main contribution of the thesis is the introduction of multi-dimensional LBP features, which preserve the relationships between different scales by building a multi-dimensional histogram. The results on benchmarked classification and retrieval datasets clearly show that the multi-dimensional LBP (MD-LBP) improves the results compared to conventional multi-scale LBP. The same principle is applied to LBPV (MD-LBPV), again leading to improved performance. The proposed variants result in relatively large feature lengths which is addressed using three different feature length reduction techniques. Principle component analysis (PCA) is shown to give the best performance when the feature length is reduced to match that of conventional multi-scale LBP. The proposed multi-dimensional LBP variants are applied for medical image analysis application. The first application is nailfold capillary (NC) image classification. Performance of MD-LBPV on NC images is highest, whereas for second application, HEp-2 cell classification, performance of MD-LBP is highest. It is observed that the proposed texture descriptors gives improved texture classification accuracy

Computing the number of groups for color image segmentation using competitive neural networks and fuzzy c-means

Se calcula la cantidad de grupos en que los vectores de color son agrupados usando fuzzy c-meansFuzzy C-means (FCM) is one of the most often techniques employed for color image segmentation; the drawback with this technique is the number of clusters the data, pixels’ colors, is grouped must be defined a priori. In this paper we present an approach to compute the number of clusters automatically. A competitive neural network (CNN) and a self-organizing map (SOM) are trained with chromaticity samples of different colors; the neural networks process each pixel of the image to segment, where the activation occurrences of each neuron are collected in a histogram. The number of clusters is set by computing the number of the most activated neurons. The number of clusters is adjusted by comparing the similitude of colors. We show successful segmentation results obtained using images of the Berkeley segmentation database by training only one time the CNN and SOM, using only chromaticity data

Visibility of capillaries in turbid tissues: an analytical approach

Purpose: Visualization and monitoring of capillary loops in dermis and mucosa are interesting for various clinical applications, including rheumatology, early cancer, and shock detection. However, the limitations of existing imaging technologies are not well understood. Therefore, this study aimed to elucidate peculiarities of the subsurface defect visualization in realistic skin imaging geometries. Methods: We used a perturbation approach for the light propagation in turbid tissues with mismatched boundaries. Defects were considered as negative light sources immersed in homogeneous media, which was described using diffuse approximation. The contrast ratio was used as an image quality metric. Results: We have developed the single point subsurface defect model and extended it to horizontally- and vertically-arranged linear inhomogeneities. In particular, we have obtained explicit analytical expressions for the single point defect and the infinite linear defect buried at a certain depth (horizontally-arranged), which allows direct experimental verification. Conclusions: The developed approach can be used for quick rough estimates while designing and optimizing imaging systems

Клінічні аспекти та цитоморфофункціональні особливості слизової оболонки носа при хронічній патології внутрішньоносових структур та їх верифікація на основі даних комп’ютерної томографії

Background. Approximately 30% of the general human population suffers from chronic pathology of intranasal structures, the main manifestations of which are impaired nasal breathing and sense of smell. The main instrumental diagnostic methods for this pathology are X-ray computed tomography (CT), which allows obtaining data on the architecture of the anatomical structures of the upper respiratory tract, and rhinomanometry, based on the results of which it is possible to assess the functional capacity of the nasal cavity during breathing. Also, a thorough study of the cytological material of the mucous membrane of the upper respiratory tract is an important component in determining the functional state of the nasal cavity, clarifying the diagnosis and choosing a treatment method. This allows the doctor to determine the composition and number of cellular elements in the material, assess their condition (destruction, proliferation, dystrophy, necrosis, etc.), ascertain the intensity of the body’s reactive abilities, monitor the dynamics of tissue recovery or the healing process in them, and encourages researchers to study in more detail and comparing the materials of clinical, radiological and cytological studies with the aim of developing a pathogenetically directed complex treatment of patients with nasal breathing disorders. Therefore it is necessary to know aspects of correlation between the results of rhinocytography and CT data in typical pathological conditions with nasal congestion are considered. Purpose – is to study the clinical aspects and cytomorphological and functional features of the nasal mucosa in patients with pathology of intranasal structures with respiratory and olfactory disorders and research their independent verification based on the CT data. Materials and Methods. Clinical examination of patients included the study of complaints, anamnesis of the disease, examination of the ENT organs, rhinomanometry, endoscopic examination of the nasal cavity and nasopharynx, The CT of the paranasal sinuses using 3D cone beam tomography on the Vatech PaX-i3D device, as well as cytological examination of the nasal mucosa. The criteria for participation in the study were the absence of chronic diseases of the cardiovascular, respiratory, digestive, urinary systems, as well as heredity burdened by these diseases. Results. Formation of a different nature of the course and severity of disorders is associated with inflammatory, dyscirculatory and trophic disorders in the nasal mucosa, which weaken both mucociliary clearance and local immunity. This applies mainly to the I group of observations. The consequence of a decrease in local immunity factors in the nasal mucosa is microbial contamination, which is associated with a long-term nasal breathing disorder in the I and II groups of observations, up to five years and six months, respectively. The results of rhinocytography mostly correspond with the aerodynamic models data of nasal сavity from the CT datasets. Conclusions. Despite the reliability of the examinations carried out by us, the cytological examination of the nasal mucosa is only an additional analysis, the interpretation of which should be based on the clinical picture of a particular patient. Proposed aerodynamic model from CT-datasets actually provides an independent verification of the aerodynamic characteristics of the nasal cavity, obtained from rhinomanometry data, and may indicate a violation of nasal breathing according to changes in the internal anatomical configuration of the nasal chanel.Актуальність. Приблизно 30% загальної людської популяції страждає на хронічну патологію внутрішньоносових структур, основними проявами якої є порушення носового дихання та нюху. Основними інструментальними діагностичними методами для виявлення даної патології є рентгенівська комп’ютерна томографія, яка дозволяє отримати дані про архітектоніку анатомічних структур верхніх дихальних шляхів, та риноманометрія, за результами якої можливо оцінити функціональну спроможність носової порожнини при диханні. Досконале дослідження цитологічного матеріалу слизової оболонки верхніх дихальних шляхів також є важливою складовою у визначенні функціонального стану носової порожнини, уточненні діагнозу і вибору методу лікування. Це дозволяє лікарю визначати склад і кількість клітинних елементів у матеріалі, оцінювати їх стан (деструкцію, проліферацію, дистрофію, некроз та ін.), констатувати напруженість реактивних властивостей організму, відстежувати динаміку відновлення тканин чи процес загоєння в них, та спонукає дослідників до більш детального вивчення і зіставлення матеріалів клінічного, радіологічного та цитологічного досліджень з метою розробки патогенетично спрямованого комплексного лікування хворих із порушеннями носового дихання. Тому в роботі розглядаються аспекти кореляції між результатами риноцитографії та даними комп’ютерної томографії у разі типових патологічних станів з порушеннями носового дихання. Мета роботи – вивчення клінічних аспектів і цитоморфофункціональних особливостей слизової оболонки носа у хворих з патологією внутрішньоносових структур з респіраторно-ольфакторними порушеннями та проведення їх незалежної верифікації на основі даних комп’ютерної томографії. Матеріали та методи. Клінічне обстеження хворих включало вивчення скарг, анамнезу захворювання, огляд ЛОР-органів, проведення риноманометрії, ендоскопічне дослідження порожнини носа та носоглотки, комп’ютерної томографії (КТ) навколоносових пазух за допомогою конусно-променевої томографії в форматі 3D на апараті Vatech PaX-i3D, а також цитологічне дослідження слизової оболонки носа. Критеріями участі в дослідженні були відсутність хронічних захворювань серцевосудинної, дихальної, травної, сечовидільної систем, а також обтяженої за цими захворюваннями спадковості. Результати та їх обговорення. Формування різного характеру перебігу та тяжкості порушень пов’язане із запальними, дисциркуляторними та трофічними порушеннями слизової оболонки носа, які послаблюють як мукоциліарний кліренс, так і місцевий імунітет. Це стосується переважно I групи спостережень. Наслідком зниження факторів місцевого імунітету в слизовій оболонці носа є мікробна контамінація, що супроводжується тривалим порушенням носового дихання в І та ІІ групах спостереження до 5 і 6 місяців відповідно. Результати риноцитографії повністю кореспондуються на основі аеродинамічних моделей носової порожнини, які створені за даними комп’ютерної томографії. Висновки. Незважаючи на достовірність проведених нами досліджень, цитологічне дослідження слизової оболонки носа є лише додатковим аналізом, інтерпретація якого повинна базуватися на клінічній картині конкретного пацієнта. Запропонована аеродинамічна модель із КТ-даних фактично забезпечує незалежну верифікацію аеродинамічних характеристик порожнини носа, отриманих за даними риноманометрії, і може свідчити про порушення носового дихання відповідно до змін внутрішньої анатомічної конфігурації носового каналу

Image Processing Algorithms for Diagnostic Analysis of Microcirculation

Microcirculation has become a key factor for the study and assessment of tissue perfusion and oxygenation. Detection and assessment of the microvasculature using videomicroscopy from the oral mucosa provides a metric on the density of blood vessels in each single frame. Information pertaining to the density of these microvessels within a field of view can be used to quantitatively monitor and assess the changes occurring in tissue oxygenation and perfusion over time. Automated analysis of this information can be used for real-time diagnostic and therapeutic planning of a number of clinical applications including resuscitation. The objective of this study is to design an automated image processing system to segment microvessels, estimate the density of blood vessels in video recordings, and identify the distribution of blood flow. The proposed algorithm consists of two main stages: video processing and image segmentation. The first step of video processing is stabilization. In the video stabilization step, block matching is applied to the video frames. Similarity is measured by cross-correlation coefficients. The main technique used in the segmentation step is multi-thresholding and pixel verification based on calculated geometric and contrast parameters. Segmentation results and differences of video frames are then used to identify the capillaries with blood flow. After categorizing blood vessels as active or passive, according to the amount of blood flow, quantitative measures identifying microcirculation are calculated. The algorithm is applied to the videos obtained using Microscan Side-stream Dark Field (SDF) imaging technique captured from healthy and critically ill humans/animals. Segmentation results were compared and validated using a blind detailed inspection by experts who used a commercial semi-automated image analysis software program, AVA (Automated Vascular Analysis). The algorithm was found to extract approximately 97% of functionally active capillaries and blood vessels in every frame. The aim of this study is to eliminate the human interaction, increase accuracy and reduce the computation time. The proposed method is an entirely automated process that can perform stabilization, pre-processing, segmentation, and microvessel identification without human intervention. The method may allow for assessment of microcirculatory abnormalities occurring in critically ill and injured patients including close to real-time determination of the adequacy of resuscitation