Pathological Deformations Research Articles

MAFE-Net: retinal vessel segmentation based on a multiple attention-guided fusion mechanism and ensemble learning network.

The precise and automatic recognition of retinal vessels is of utmost importance in the prevention, diagnosis and assessment of certain eye diseases, yet it brings a nontrivial uncertainty for this challenging detection mission due to the presence of intricate factors, such as uneven and indistinct curvilinear shapes, unpredictable pathological deformations, and non-uniform contrast. Therefore, we propose a unique and practical approach based on a multiple attention-guided fusion mechanism and ensemble learning network (MAFE-Net) for retinal vessel segmentation. In conventional UNet-based models, long-distance dependencies are explicitly modeled, which may cause partial scene information loss. To compensate for the deficiency, various blood vessel features can be extracted from retinal images by using an attention-guided fusion module. In the skip connection part, a unique spatial attention module is applied to remove redundant and irrelevant information; this structure helps to better integrate low-level and high-level features. The final step involves a DropOut layer that removes some neurons randomly to prevent overfitting and improve generalization. Moreover, an ensemble learning framework is designed to detect retinal vessels by combining different deep learning models. To demonstrate the effectiveness of the proposed model, experimental results were verified in public datasets STARE, DRIVE, and CHASEDB1, which achieved F1 scores of 0.842, 0.825, and 0.814, and Accuracy values of 0.975, 0.969, and 0.975, respectively. Compared with eight state-of-the-art models, the designed model produces satisfactory results both visually and quantitatively.

Lung lobe segmentation in computed tomography images based on multi‐feature fusion and ensemble learning framework

AbstractLung lobe segmentation in computed tomography (CT) images can be regarded as essential supporting information for the diagnosis and treatment of lung diseases, yet it is a challenging uncertainty for the complex segmentation task due to the diverse structures like indistinguishable pulmonary arteries and veins, unpredictable pathological deformation and blurring pulmonary fissures. To circumvent these challenges, we present a productive deep learning network based on multi‐feature fusion and ensemble learning approach to highlight pulmonary fissure representation and suppress other structures for lung lobe segmentation in CT images. Considering that pulmonary fissures are the physical boundaries of lung lobes, a multi‐feature fusion approach is presented to integrate original images, enhanced fissure magnitude images, and enhanced fissure orientation images to highlight shape representation for semantic segmentation. In addition, a deep‐supervised ensemble learning network is employed to combine multiple inducers for lung lobe segmentation improvement. The performance of the proposed deep learning model is validated in experiments with an available dataset, it acquired a high IoU value and a low Hausdorff distance compared with manual references. Experimental results demonstrate that the proposed computational model based on multi‐feature fusion and deep‐supervised ensemble learning framework has an improved predictive performance than many state‐of‐the‐art deep neural networks in lung lobe segmentation.

Электрокардиографические изменения в раннем периоде после плановой реваскуляризации миокарда

INTRODUCTION: To date, highly effective methods of myocardial protection have been developed, which are widely used in cardiac surgery. At the same time, the problem of perioperative myocardial infarction still exists and is one of the causes of adverse cardiovascular events and mortality, both at the hospital stage of treatment and in the long-term period. A factor leading to such a complication may be acute dysfunction of the coronary bypass graft, the timely detection and elimination of which will reduce the negative consequences of myocardial damage. The relevance of the study results from investigation of the relationship between the angiographic data and the character of ischemic changes on the electrocardiogram of patients with and without proven acute dysfunction of coronary bypass graft. AIM: Identification of the most pathognomonic electrocardiographic signs of dysfunction of coronary bypass grafts in the early postoperative period after planned myocardial revascularization. MATERIALS AND METHODS: The study included 196 (1.86%) of 10,550 patients operated for coronary artery disease in Chelyabinsk Center of Cardiovascular Surgery from 2011 to 2020, who underwent emergency angiography after planned coronary artery bypass graft surgery due to the appearance of signs of myocardial damage in the early postoperative period. Depending on the type of angiographic findings and the chosen treatment tactics, patients were divided to 3 groups. Group I (n = 86) included patients in whom angiography revealed defects in the area of large bypassed coronary arteries, of them 60 patients underwent endovascular treatment, and 26 patients underwent repeated open surgery. Group II (n = 33) consisted of patients in whom bypass graft dysfunction was noted, but, however, due to the small diameter or pronounced diffuse lesion of the bypassed coronary arteries, all the patients underwent conservative therapy. Group III included 77 patients in whom hemodynamically significant defects in grafts and native arteries were not identified. RESULTS: When studying postoperative electrocardiographic data, it was found that significant differences between the groups were obtained only in the occurrence of ventricular arrhythmias (P1–2 = 0.027; P2–3 = 0.01). As for other pathological electrocardiographic signs and their combinations, no statistical differences were found. CONCLUSIONS: An isolated electrocardiographic study in the early postoperative period does not permit to identify patients with dysfunction of coronary bypass grafts. It is necessary to develop a diagnostic algorithm, including instrumental and laboratory methods, for accurate diagnosis of myocardial ischemia caused by impaired graft function or pathological deformation of the coronary bed due to surgical procedures.

The Phenomenology of the “Sitting Inside”: A Socio-Philosophical Analysis

The article deals with the problem of transforming human subjectivity. Factors which condition the formation of the internal concept of the Self, as a phenomenon “sitting inside,” are defined. Aspects connected with the concept of “norm” and “pathology” from positions of modern philosophy, social psychology, psychoanalysis and medicine are analyzed. The relevance of the study: at present, there is a radical revision of ideas about the inner component of the self-concept. The aim of the study is to explore the socio-philosophical aspects of multiple subjectivities of the individual from the perspective of the phenomenon of “sitting inside”. In addition to the general scientific methods of analysis and synthesis, the research methodology involves the application of methods such as the systematic method, the method of interdisciplinary research and the method of hypothetical modelling. The author’s interpretation of the phenomenon of “multiple subjectivities” is given. The results of the study have been the subject of numerous discourses at scientific and practical conferences at international and all-Russian levels and seminars. The study concludes that the phenomenon of “sitting inside” should be characterized as a pathological deformation of personality subjectivity.

Taxonomic and palaeobiological implications of a large, pathological sabretooth (Carnivora, Felidae, Machairodontinae) from the Lower Pliocene of South Africa

AbstractWe describe the most complete postcranial remains of a pathological, large‐bodied sabretooth from the Lower Pliocene site of Langebaanweg ‘E’ Quarry (South Africa). The skeleton consists of hind limb and vertebral elements that exhibit distinctive exostoses, osteophytes and eburnation. We performed a quantitative morphological comparison of the new postcranial remains found in Langebaanweg, with other Neogene and Quaternary sabretooth and non‐sabretooth felids, consisting of the genera Amphimachairodus, Machairodus, Lokotunjailurus, Dinofelis, Panthera, Homotherium and Smilodon from several sites in Africa, Europe and North America, using principal component analysis and Mosimann transformations. Although the pathological deformation of the remains distorted some of the linear measurements, most of the analysed variables do not contain pathological features, and strongly indicate that the Langebaanweg sabretooth is morphologically closer to Machairodus aphanistus and Lokotunjailurus emageritus than it is to Amphimachairodus giganteus. This indicates that the remains could belong to an undetermined sabretooth species from the Langebaanweg locality. The observed pathologies in the foot and lumbar spine are consistent with diagnostic criteria for severe osteoarthritis (due to maturity), which would have limited limb mobility with severe consequences for hunting success.

CEL-Unet: a novel CNN architecture for 3D Segmentation of Knee Bones affected by Severe Osteoarthritis for PSI-Based Surgical Planning.

Unet architectures are promising deep learning networks exploited to perform the automatic segmentation of bone CT images, in line with their ability to deal with pathological deformations and size-varying anatomies. However, bone degeneration, like the development of irregular osteophytes as well as mineral density alterations might interfere with this automated process and demand extensive manual refinement. The aim of this work is to implement an innovative Unet variant, the CEL-Unet, to improve the femur and tibia segmentation outcomes in osteoarthritic knee joints. In this network the decoding path is split into a region and contour-aware branch to increase the prediction reliability in such pathological conditions. The comparison between the segmentation results achieved with a standard Unet and its novel variant (CEL-Unet) was performed as follows: the Unet was trained with 5 different loss functions: Dice Loss, Focal Loss, Exponential Logarithmic Loss, Double Cross Entropy Loss and Distanced Cross Entropy loss. The CEL-Unet was instead trained with two loss functions, one for each of the network outputs, namely Mask and Edge, yielding the so-called Combined Edge Loss (CEL) function. A set of 259 knee CT scans was used to train the model and test segmentation performance. The CEL-Unet outperformed all other Unet-based models, reaching the highest Jaccard values of about 0.97 and 0.96 on femur and tibia, respectively. Clinical Relevance- With the increasing rate of Total Knee Arthoplasty deep learning-based methods can achieve fast accurate and automatic 3D segmentation of the knee joint bones to enhance new costumized pre-operative planning.

CEL-Unet: Distance Weighted Maps and Multi-Scale Pyramidal Edge Extraction for Accurate Osteoarthritic Bone Segmentation in CT Scans

Unet architectures are being investigated for automatic image segmentation of bones in CT scans because of their ability to address size-varying anatomies and pathological deformations. Nonetheless, changes in mineral density, narrowing of joint spaces and formation of largely irregular osteophytes may easily disrupt automatism requiring extensive manual refinement. A novel Unet variant, called CEL-Unet, is presented to boost the segmentation quality of the femur and tibia in the osteoarthritic knee joint. The neural network embeds region-aware and two contour-aware branches in the decoding path. The paper features three main technical novelties: 1) directed connections between contour and region branches progressively at different decoding scales; 2) pyramidal edge extraction in the contour branch to perform multi-resolution edge processing; 3) distance-weighted cross-entropy loss function to increase delineation quality at the sharp edges of the shapes. A set of 700 knee CT scans was used to train the model and test segmentation performance. Qualitatively CEL-Unet correctly segmented cases where the state-of-the-art architectures failed. Quantitatively, the Jaccard indexes of femur and tibia segmentation were 0.98 and 0.97, with median 3D reconstruction errors less than 0.80 and 0.60 mm, overcoming competitive Unet models. The results were evaluated against knee arthroplasty planning based on personalized surgical instruments (PSI). Excellent agreement with reference data was found for femoral (0.11°) and tibial (0.05°) alignments of the distal and proximal cuts computed on the reconstructed surfaces. The bone segmentation was effective for large pathological deformations and osteophytes, making the techniques potentially usable in PSI-based surgical planning, where the reconstruction accuracy of the bony shapes is one of the main critical factors for the success of the operation.

Human Impact on Antler Conformation in Western Red Deer (Cervus elaphus elaphus Linnaeus, 1758)

A stray find of red deer antler from Sweden with the braincase was collected due to an apparently pathological deformation, the strongly retarded right antler. Measurements of the complete left antler inspired the analysis of general antler conformation in order to place this archaeological specimen in a zoological context. This stray find and another prehistoric antler from Sweden as well as three complete prehistoric antlers from Hungary were metrically compared using measurements of over 17,000 trophies of extant red deer from Hungary. The results confirmed that the stray specimen from Sweden and prehistoric antlers from Hungary were similar in that they were stouter (smaller length measurements but greater circumferences) than their 20th century counterparts. Most of their measurements fell within the ±1 standard deviation interval of the means of extant trophies. The pathological lesion on the studied stray specimen directed attention to the role of human selection. Twentieth century record trophies show a significant increase in antler weight and “quality” as defined in the international trophy grading system. While these morphometric observations cannot be taken as a proxy for absolute dating or precise contextual identification for the stray find central to this study, its size and apparent lack of consistent human selection (pathological deformation, “archaic” antler proportions) point to possibly early origins, prior to major human influence.

Symbiotic embedment structures in Silurian Caryocrinites (Echinodermata, Rhombifera, Hemicosmitida)

AbstractA variety of pits representing symbiotic embedments, sometimes associated with pathological deformation in the host, are known from the skeletons of Paleozoic stalked echinoderms. These structures are well known from multiple genera of crinoids and a limited number of blastozoans but have not previously been described in detail from the skeletons of rhombiferans. This is surprising given the abundance of rhombiferans in certain deposits, the co-occurrence of rhombiferans with frequently infested taxa, including diploporitans, in multiple assemblages, and the morphological similarity between certain rhombiferan taxa and coeval infested crinoids. The common hemicosmitid rhombiferan Caryocrinites Say, 1825 is widespread throughout the middle Silurian of eastern North America and is herein reported to contain symbiotic (potentially parasitic) embedment structures. Specimens were collected from the lower portion of the mudstone lithofacies of the Massie Formation (Wenlock, Sheinwoodian) at the Napoleon quarry of southeastern Indiana, USA. Strong host specificity is indicated by the absence of pits in C. ornatus Say, 1825 and exclusive infestation of a smaller co-occurring species of Caryocrinites. Thecae with embedment structures are consistently smaller than thecae without such structures, with pitted specimens being restricted to a narrow range of thecal heights (20–24 mm). All embedment structures are present only on the proximal portion of thecae, with individual specimens containing between one and 30 pits. No elevated rims or significant swelling were observed on any specimens, and all pits are relatively small (~1 mm in diameter). The presence of symbiotic embedment structures represents an additional example of a crinoid-like aspect to the ecology of Caryocrinites.

Automatic vertebrae recognition from arbitrary spine MRI images by a category-Consistent self-calibration detection framework.

Accurate vertebrae recognition is crucial in spinal disease localization and successive treatment planning. Although vertebrae detection has been studied for years, reliably recognizing vertebrae from arbitrary spine MRI images remains a challenge. The similar appearance of different vertebrae and the pathological deformations of the same vertebrae makes it difficult for classification in images with different fields of view (FOV). In this paper, we propose a Category-consistent Self-calibration Recognition System (Can-See) to accurately classify the labels and precisely predict the bounding boxes of all vertebrae with improved discriminative capabilities for vertebrae categories and self-awareness of false positive detections. Can-See is designed as a two-step detection framework: (1) A hierarchical proposal network (HPN) to perceive the existence of the vertebrae. HPN leverages the correspondence between hierarchical features and multi-scale anchors to detect objects. This correspondence tackles the image scale/resolution challenge. (2) A Category-consistent Self-calibration Recognition (CSRN) Network to classify each vertebra and refine their bounding boxes. CSRN leverages the dictionary learning principle to preserve the most representative features; it imposes a novel category-consistent constraint to force vertebrae with the same label to have similar features. CSRN then innovatively formulates message passing into the deep learning framework, which leverages the label compatibility principle to self-calibrate the wrong pre-recognitions. Can-See is trained and evaluated on a capacious and challenging dataset of 450 MRI scans. The results show that Can-See achieves high performance (testing accuracy reaches 0.955) and outperforms other state-of-the-art methods.

A framework for pulmonary fissure segmentation in 3D CT images using a directional derivative of plate filter

Imaging pulmonary fissures by CT provides useful information on diagnosis of pulmonary diseases. Automatic segmentation of fissures is a challenging task due to the variable appearance of fissures, such as inhomogeneous intensities, pathological deformation and imaging noise. To overcome these challenges, we propose an anisotropic differential operator called directional derivative of plate (DDoP) filter to probe the presence of fissure objects in 3D space by modeling the profile of a fissure patch with three parallel plates. To reduce the huge computation burden of dense matching with rotated DDoP kernels, a family of spherical harmonics are particularly utilized for acceleration. Additionally, a two-stage post-processing scheme is introduced to segment fissures. The performance of our method was verified in experiments using 55 scans from the publicly available LOLA11 dataset and 50 low-dose CT scans of lung cancer patients from the VIA-ELCAP database. Our method showed superior performance compared to the derivative of sticks (DoS) method and the Hessian-based method in terms of median and mean F1−score. The median F1−score for DDoP, DoS-based and Hessian-based methods on the LOLA11 dataset was 0.899, 0.848 and 0.843, respectively, and the mean F1−score was 0.858 ± 0.103, 0.781 ± 0.165 and 0.747 ± 0.239, respectively.

ОПТИМИЗАЦИЯ ХИРУРГИЧЕСКОГО ЛЕЧЕНИЯ ПАТОЛОГИЧЕСКОЙ ИЗВИТОСТИ ПОЗВОНОЧНОЙ АРТЕРИИ

Objective: Analysis of the results of standard and optimized surgical treatment of vertebral artery (VA) tortuosity. Methods: The results of surgical treatment of 52 patients with VA tortuosity were analyzed. There were 18 men (34.6%), and 34 women (65.4%). The age of patients ranged from 23 to 75 years. C- and S-shaped kicking of VA occurred in 38 cases, coiling in 8 cases and Powers syndrome in 6 cases. In 28 (53.8%) patients there was also hypoplasia of the contralateral VA, and in 7 (13.5%) cases there was a pathological deformation of the internal carotid artery. Results: Depending on the shape of the tortuosity, 4 techniques of reconstructive operations were performed to eliminate tortuosity. In the postoperative period thrombosis of the anastomosis line noted in 2.8% of cases, TIA – in 1.9%, and stroke – in 1.9%. The immediate and long-term results in the groups showed the effectiveness and best results in the group of patients who underwent lateralization of the VA of the author’s modification. Also established that for VA coiling, the method of choice is to move and implantation of VA into the carotid artery. Conclusions: Correction of VA tortuosity should be differentiated, and the choice of the method of surgery technique should depend on the type of tortuosity and concomitant vascular pathology. The lateral and anterior moving VA ostium helps to reduce the rate of anastomosis thrombosis and greatly facilitates the surgery technique. Keywords: Vertebral artery, tortuosity, kinking, coiling, vertebrobasilar insufficiency, chronic cerebral ischemia, surgical treatment.

The evaluation of a role of the inconsistency of connective tissue in the development of pathological deformations of cerebral vessels in patients with primary headaches

Vascular malformations of the brain may cause headaches, seizures, strokes, or bleeding in the brain. Some researchers believe that the type of malformation determines the symptoms and progression of the disease. To analyse manifestations of connective tissue failure in patients with pathological deformations of cerebral vessels The study included 60 patients aged 17-46 years with primary headaches treated in 1st Republic Clinic in Tashkent between 2016–2018 years. Patients were divided into 2 groups: patients with (30 patients) and without (30 patients) abnormalities of cerebral vessels. The examination included a clinical neurological examination, MRI with angiography and duplex scan 1st group showed that the folded skin was easily pulled back by several centimeters, and then quickly returned to its original position. At the time of the study, chronic arthralgia without signs of joint inflammation was found in 13.7% of patients. Scoliosis, kyphosis, their combination, as well as flat feet were noted. At the same time, in the observed patients, the breakdown in the strength of the internal organs tissues manifested itself in the form of hernia, 7.8% of cases, the lowering of the internal genitalia-9.7%, in 21.3% in the anamnesis, premature rupture of the membranes, premature birth and postpartum hemorrhage Diffuse inconsistency of connective tissue was revealed in patients with deformations of cerebral vessels. Furthermore, to identify pathology from the connective tissue, it is necessary to include a screening of connective tissue in the primary headache examination

Pair-wise vs group-wise registration in statistical shape model construction: representation of physiological and pathological variability of bony surface morphology

Statistical shape models (SSM) of bony surfaces have been widely proposed in orthopedics, especially for anatomical bone modeling, joint kinematic analysis, staging of morphological abnormality, and pre- and intra-operative shape reconstruction. In the SSM computation, reference shape selection, shape registration and point correspondence computation are fundamental aspects determining the quality (generality, specificity and compactness) of the SSM. Such procedures can be made critical by the presence of large morphological dissimilarities within the surfaces, not only because of anthropometrical variability but also mainly due to pathological abnormalities. In this work, we proposed a SW pipeline for SSM construction based on pair-wise (PW) shape registration, which requires the a-priori selection of the reference shape, and on a custom iterative point correspondence algorithm. We addressed large morphological deformations in five different bony surface sets, namely proximal femur, distal femur, patella, proximal fibula and proximal tibia, extracted from a retrospective patient dataset. The technique was compared to a method from the literature, based on group-wise (GW) shape registration. As a main finding, the proposed technique provided generalization and specificity median errors, for all the five bony regions, lower than 2 mm. The comparative analysis provided basically similar results. Particularly, for the distal femur that was the shape affected by the largest pathological deformations, the differences in generalization, specificity and compactness were lower than 0.5 mm, 0.5 mm, and 1%, respectively. We can argue the proposed pipeline, along with the robust correspondence algorithm, is able to compute high-quality SSM of bony shapes, even affected by large morphological variability.

Learning a Probabilistic Model for Diffeomorphic Registration.

We propose to learn a low-dimensional probabilistic deformation model from data which can be used for the registration and the analysis of deformations. The latent variable model maps similar deformations close to each other in an encoding space. It enables to compare deformations, to generate normal or pathological deformations for any new image, or to transport deformations from one image pair to any other image. Our unsupervised method is based on the variational inference. In particular, we use a conditional variational autoencoder network and constrain transformations to be symmetric and diffeomorphic by applying a differentiable exponentiation layer with a symmetric loss function. We also present a formulation that includes spatial regularization such as the diffusion-based filters. In addition, our framework provides multi-scale velocity field estimations. We evaluated our method on 3-D intra-subject registration using 334 cardiac cine-MRIs. On this dataset, our method showed the state-of-the-art performance with a mean DICE score of 81.2% and a mean Hausdorff distance of 7.3 mm using 32 latent dimensions compared to three state-of-the-art methods while also demonstrating more regular deformation fields. The average time per registration was 0.32 s. Besides, we visualized the learned latent space and showed that the encoded deformations can be used to transport deformations and to cluster diseases with a classification accuracy of 83% after applying a linear projection.

Проблема особистісних деструкцій та збереження професійного здоров’я в умовах сучасного соціуму

The article shows that under the personal destructions understand the pathological process of destruction of the structure of the individual or its individual elements. Personal destructions include such formations of the human psyche that create barriers in its contacts with others and thus complicate the realization of their own goals. The main types of destructive changes in personality include pathological deformation of personal needs and motives, destructive changes in character and temperament, violations of volitional regulation of behavior, systems of interpersonal relationships, formation of inadequate self-esteem. Among the leading forms of personal destruction are partial and deep personal destruction, as well as temporary (transient), with the subsequent restoration of the functioning of all structural components of the personality, and progressive (irreversible), followed by a personal defect. It is established that personal destructions can be as a result of self-destructive activity of the person, as well as purposeful external influence, or as a result of psycho-traumatic and crisis situations, in particular loss of a person's disability. The negative (crisis) type of personal attitude of the examinees to the situation of temporary disability is defined, which distinguishes the unpreparedness for its adoption, consideration of the existing conditions as crisis with distortion of life plans and prospects, and the adaptive (constructive) type, with adequate assessment of the current situation adoption, formation of an adaptive model of behavior. It is established that the determinants of personal destruction are social and psychological characteristics that cause negative changes in the cognitive, emotional, semantic and communicative spheres of personality. As indicators of the destruction of the cognitive sphere of the personality are rigidity, limited thinking and conservatism; emotional sphere - psycho-emotional exhaustion, emotional instability; the semantic sphere - reduction of personal achievements, insufficient cognitive activity, the communicative sphere - social distance, reduction of interpersonal contacts, seclusion and self-centeredness.

THE CLINICAL-HAEMODYNAMICAL PECULIARITIES OF ISCHEMIC STROKES WITH UNDERLYING SYMPTOMATIC ARTERIAL HYPERTENSION

30 patients were examined in the acute period of ischemic stroke in anterior cerebral circulation of vasorenal etiology, which is caused by the tortuosity of the extracranial vessels. It was found that the pathological deformation of the vessels is more often due to acquired pathology, in particular arterial hypertension, which increases the hydrodynamic load on the vascular wall, which must be considered in the choice of tactics for treating this pathology.

An oriented derivative of stick filter and post-processing segmentation algorithms for pulmonary fissure detection in CT images

Abstract Knowledge of pulmonary fissure anatomy is valuable in localization of lesions and evaluation of lung disease. Under CT imaging, pulmonary fissure detection is an intricate task due to factors such as pathological deformation, partial volume effect and intensity variability. To solve the problem, an oriented derivative of stick (ODoS) filter and a post-processing segmentation algorithm are introduced for pulmonary fissure detection. Here, the ODoS filter is proposed as an improvement to an existing derivative of stick (DoS) filter by merging the stick orientation information for pulmonary fissure enhancement, which will increase its clutter discriminating ability especially on those linking to the fissure object. Based on an observation that the pulmonary fissures often appear as coplanar structures and have similar directions across the sagittal plane, we present an orientation partition scheme for fissure patches and noise separation in different orientation partition. After removing the small-sized noise, the purified patches from different partitions are iteratively integrated by a fissure patches integration scheme for pulmonary fissure segmentation. With the additional direction constraint, the ODoS filtering response can be more completely detected and the noise residual could be kept at the lowest level. The performance of our algorithms is validated in experiments with a publicly available challenge dataset, i.e. the LObe and Lung Analysis 2011 (LOLA11) data, including 55 CT scans. Compared with manual references, the proposed method acquired a high median F1-score of 0.877. The effectiveness of our scheme was verified by visual inspection and quantitative evaluation.

On the linear sizes of vertebrae and intervertebral discs of children in the beginning of puberty.

Study Design:We collected experimental data concerning vertebrae sizes and performed an investigation of these data for different patient ages by methods of mathematical statistics.Purpose:The standard dimensions of vertebrae and intervertebral discs are of major importance for obtaining a comprehensive understanding of spine diseases and their successful treatment. The purpose is to study these sizes for children at the age of 9–14 years.Overview of Literature:Unfortunately, this issue is poorly presented in the corresponding literature. There are no systematic results. Only particular cases are presented.Materials and Methods:Experimental is based on the: results of X-ray investigations of children spines. Theoretical background is given by methods of mathematical statistics.Results:Systematic description of vertebrae sizes for children of age 9–14 is given. This specific age interval is the most common period of initiation of various pathological deformations of human spine.Conclusions:The acquired data both reflect the process of spine growth and can serve for building correct mathematical models of a healthful or diseased spine.

Pathological deformations of the internal carotid artery: modern aspects of etiopathogenesis, diagnostics and surgical treatment (review)

Deformation of the internal carotid artery is a variant of pathology of brachiocephalic arteries. The importance of the study of this pathology for health professionals of various specialitiesarises from the lack of data concerning its etiology, mechanisms of development, approaches to diagnostics and treatment. The review considers opinions of domestic and foreign experts on key issues of pathological deformations of the internal carotid artery. The main risk factors for congenital and acquired pathological deformations of the internal carotid artery are systematized. The comprehensive observation of patients is necessary by means of ultrasonic duplex scanning aortic arch branches, magnetic resonance angiography and computed tomography. Approaches to the surgical correction of pathological deformations of the internal carotid artery described in the scientific literaturedemonstrate possibilities for the treatment of these patients.