Search
Search results for: ABDOMINAL AORTA SEGMENTATION
-
Assessment of particular abdominal aorta section extraction from contrast-enhanced computed tomography angiography
PublicationThe aim of this work is to improve the accuracy of extraction of a particular abdominal aorta section and to reduce the distortion in three-dimensional Computed Tomography Angiography (CTA) images. Imaging modality and quality plays crucial role in the medical diagnostic process, thus ensuring high quality of images is essential at every stage of acquisition and processing.Noise is defined as a disturbance of the image quality...
-
Abdominal Aortic Aneurysm segmentation from contrast-enhanced computed tomography angiography using deep convolutional networks
PublicationOne of the most common imaging methods for diagnosing an abdominal aortic aneurysm, and an endoleak detection is computed tomography angiography. In this paper, we address the problem of aorta and thrombus semantic segmentation, what is a mandatory step to estimate aortic aneurysm diameter. Three end-to-end convolutional neural networks were trained and evaluated. Finally, we proposed an ensemble of deep neural networks with underlying...
-
Late Aortic Remodeling after Endovascular Repair of Complicated Type B Aortic Dissection—TEVAR Protects Only the Covered Segment of Thoracic Aorta
PublicationIntroduction: TEVAR is the preferred way of treatment of complicated type B aortic dissection. The purpose of the study was to assess the impact of TEVAR on aortic remodelling in the thoracic and abdominal segment in long-term follow-up. Methods: 23 patients with complicated type B aortic dissection were treated by TEVAR in years 2004-2012 in our Department. Aortic remodelling was rated based on preoperative and final follow-up...
-
AORTA
Journals -
Full-field in vivo experimental study of the strains of a breathing human abdominal wall with intra-abdominal pressure variation
PublicationThe presented study aims to assess the mechanical behaviour of the anterior abdominal wall based on an in vivo experiment on humans. Full-field measurement of abdominal wall displacement during changes of intra-abdominal pressure is performed using a digital image correlation (DIC) system. Continuous measurement in time enables the observation of changes in the strain field during breathing. The understanding of the mechanical...
-
Abdominal epilepsy in patient of schizophrenia - a diagnostic dilemma
PublicationAbdominal epilepsy is a rare and uncomman cause of recurrent abdominal pain. It is commonly occuring in children, but rarely in adolescent and elderly. Paroxysmal episodes of abdominal pain with neurological symptoms like dizziness, lethargy, and abnormal electroencephalogram and remarkable response to anticonvulsant confirms the diagnosis. Here we present a case of schizophrenia, who has repoted with recurrent abdominal pain...
-
Numerical Model of the Aortic Valve Implanted Within Real Human Aorta
PublicationCardiovascular system diseases are the main cause of deaths in developed and developing countries. The main reasons are myocardial infarction, heart failure, stroke and valvular diseases. These are caused mainly by arteriosclerosis. The valvular diseases involve a significant burden for the health care system and their frequency is rising with the patient age. This work describes the tools and numerical models appropriate for modeling...
-
Instance segmentation of stack composed of unknown objects
PublicationThe article reviews neural network architectures designed for the segmentation task. It focuses mainly on instance segmentation of stacked objects. The main assumption is that segmentation is based on a color image with an additional depth layer. The paper also introduces the Stacked Bricks Dataset based on three cameras: RealSense L515, ZED2, and a synthetic one. Selected architectures: DeepLab, Mask RCNN, DEtection TRansformer,...
-
Modelling of Abdominal Wall Under Uncertainty of Material Properties
PublicationThe paper concerns abdominal wall modelling. The accurate prediction and simulation of abdominal wall mechanics are important in the context of optimization of ventral hernia repair. The shell Finite Element model is considered, as the one which can be used in patient-specific approach due to relatively easy geometry generation. However, there are uncertainties in this issue, e.g. related to mechanical properties since the properties...
-
Mechanical compatibility of implants used in hernia repair with abdominal wall
PublicationThe paper deals with a membrane model of a synthetic surgical mesh for treatment of abdominal hernia. The authors analyse the compatibility of two implant types with the human wall: Dualmesh Gore and Proceed. The finite element method is applied to simulate tjhe behavior of the proposed model. Due fact that recurrences are usually caused by connection failure, this study is focused on reaction forces in supports representing the...
-
Stiffness change of abdominal prosthesis Optomesh™ under cyclic loading
PublicationAbdominal prostheses are used in humans for abdominal wall strengthening or reconstruction. From the mechanical point of view they are membranes, so their basic mechanical property is tensile stiffness. This property is experimentally identified for a selected implant, OptomeshTM. The obtained results are described herein. Uni-axial simple and cyclic tension tests are a basis for the analysis. Both kinds of tests allowed to distinguish...
-
Isogeometric Shell FE Analysis of the Human Abdominal Wall
PublicationIn this paper a nonlinear isogeometric Kirchhoff-Love shell model of the human abdominal wall is proposed. Its geometry is based on in vivo measurements obtained from a polygon mesh that is transformed into a NURBS surface, and then used directly for the finite element analysis. The passive response of the abdominal wall model under uniform pressure is considered. A hyperelastic membrane model based on the Gasser-Ogden-Holzapfel...
-
MEAN SHIFT BASED SEGMENTATION FOR BLEEDING REGIONS IN ENDOSCOPIC VIDEOS
PublicationWith a set of 38 manually marked bleeding regions form endoscopic videos, the authors attempted to find an optimal image segmentation method for reproducing doctor’s markup. Mean shift segmentation combined with HSV histogram segmentation were used as a segmentation method, which was then optimized by tuning the parameters of the method using global optimization algorithm. A target function for measuring the quality of segmentation was...
-
Ensembling noisy segmentation masks of blurred sperm images
PublicationBackground: Sperm tail morphology and motility have been demonstrated to be important factors in determining sperm quality for in vitro fertilization. However, many existing computer-aided sperm analysis systems leave the sperm tail out of the analysis, as detecting a few tail pixels is challenging. Moreover, some publicly available datasets for classifying morphological defects contain images limited only to the sperm head. This...
-
Membrane model of human abdominal wall. Simulations vs. in vivo measurements
PublicationThe study presents a methodology of defining a numerical model of human abdominal wall based on the experimentally registered data of the abdomen geometry due to variations of the intraabdominal pressure. The abdominal wall is modelled here as a simple homogeneous membrane structure made of linear orthotropic material The displacements registered during the increase of pressure are compared with the re-sults of the model static...
-
Global sensitivity analysis of membrane model of abdominal wall with surgical mesh
PublicationThe paper addresses the issue of ventral hernia repair. Finite Element simulations can be helpful in the optimization of hernia parameters. A membrane abdominal wall model is proposed in two variants: a healthy one and including hernia defect repaired by implant. The models include many uncertainties, e.g. due to variability of abdominal wall, intraabdominal pressure value etc. Measuring mechanical properties with high accuracy...
-
Abdominal Radiology
Journals -
ABDOMINAL IMAGING
Journals -
Review of Segmentation Methods for Coastline Detection in SAR Images
PublicationSynthetic aperture radar (SAR) images acquired by airborne sensors or remote sensing satellites contain the necessary information that can be used to investigate various objects of interest on the surface of the Earth, including coastlines. The coastal zone is of great economic importance and is also very densely populated. The intensive and increasing use of coasts and changes of coastlines motivate researchers to try to assess...
-
Deep Instance Segmentation of Laboratory Animals in Thermal Images
PublicationIn this paper we focus on the role of deep instance segmentation of laboratory rodents in thermal images. Thermal imaging is very suitable to observe the behaviour of laboratory animals, especially in low light conditions. It is an non-intrusive method allowing to monitor the activity of animals and potentially observe some physiological changes expressed in dynamic thermal patterns. The analysis of the recorded sequence of thermal...
-
Biomechanics of the front abdominal wall as a potential factorleading to recurrence with laparoscopic ventral hernia repair
PublicationThis study investigated the front abdominal wallto describe its elasticity in vivo and searched for elongationsthat possibly stretched an implanted mesh, therebycausing fixation failure and subsequent recurrence.To measure front abdominal wall elongations, amodel of fascia movements was created. Eight healthyvolunteers were measured during exercise to determine theextent of elongations in their front abdominal wall. Videoswere...
-
A novel in vivo approach to assess strains of the human abdominal wall under known intraabdominal pressure
PublicationThe study concerns mechanical behaviour of a living human abdominal wall. A better mechanical understanding of a human abdominal wall and recognition of its material properties is required to find mechanically compatible surgical meshes to significantly improve the treatment of ventral hernias. A non-invasive methodology, based on in vivo optical measurements is proposed to determine strains of abdominal wall corresponding to...
-
SegSperm - a dataset of sperm images for blurry and small object segmentation
Open Research DataMany deep learning applications require figure-ground segmentation. The performance of segmentation models varies across modalities and acquisition settings.
-
Computational Methods for Liver Vessel Segmentation in Medical Imaging: A Review
PublicationThe segmentation of liver blood vessels is of major importance as it is essential for formulating diagnoses, planning and delivering treatments, as well as evaluating the results of clinical procedures. Different imaging techniques are available for application in clinical practice, so the segmentation methods should take into account the characteristics of the imaging technique. Based on the literature, this review paper presents...
-
Self-organising maps in the analysis of strains of human abdominal wall to identify areas of similar mechanical behaviour.
PublicationThe study refers to the application of a type of artificial neural network called the Self-Organising Map (SOM) for the identification of areas of the human abdominal wall that behave in a similar mechanical way. The research is based on data acquired during in vivo tests using the digital image correlation technique (DIC). The mechanical behaviour of the human abdominal wall is analysed during changing intra-abdominal pressure....
-
Material Identification of the Human Abdominal Wall Based On the Isogeometric Shell Model
PublicationThe human abdominal wall is an object of interest to the research community in the context of ventral hernia repair. Computer models require a priori knowledge of constitutive parameters in order to establish its mechanical response. In this work, the Finite Element Model Updating (FEMU) method is used to identify an heterogeneous shear modulus distribution for a human abdominal wall model, which is based on nonlinear isogeometric...
-
Deep learning based thermal image segmentation for laboratory animals tracking
PublicationAutomated systems for behaviour classification of laboratory animals are an attractive alternative to manual scoring. However, the proper animals separation and tracking, especially when they are in close contact, is the bottleneck of the behaviour analysis systems. In this paper, we propose a method for the segmentation of thermal images of laboratory rats that are in close contact during social behaviour tests. For this, we are...
-
Accelerating Video Frames Classification With Metric Based Scene Segmentation
PublicationThis paper addresses the problem of the efficient classification of images in a video stream in cases, where all of the video has to be labeled. Realizing the similarity of consecutive frames, we introduce a set of simple metrics to measure that similarity. To use these observations for decreasing the number of necessary classifications, we propose a scene segmentation algorithm. Performed experiments have evaluated the acquired...
-
Image Segmentation of MRI image for Brain Tumor Detection
Publicationthis research work presents a new technique for brain tumor detection by the combination of Watershed algorithm with Fuzzy K-means and Fuzzy C-means (KIFCM) clustering. The MATLAB based proposed simulation model is used to improve the computational simplicity, noise sensitivities, and accuracy rate of segmentation, detection and extraction from MR...
-
Semantic segmentation training using imperfect annotations and loss masking
PublicationOne of the most significant factors affecting supervised neural network training is the precision of the annotations. Also, in a case of expert group, the problem of inconsistent data annotations is an integral part of real-world supervised learning processes, well-known to researchers. One practical example is a weak ground truth delineation for medical image segmentation. In this paper, we have developed a new method of accurate...
-
Three-objective antenna optimization by means of kriging surrogates and domain segmentation
PublicationIn this paper, an optimization framework for multi-objective design of antenna structures is discussed which exploits data-driven surrogates, a multi-objective evolutionary algorithm, response correction techniques for design refinement, as well as generalized domain segmentation. The last mechanism is introduced to constrain the design space region subjected to sampling, which permits reduction of the number of training data samples...
-
Adaptive Hounsfield Scale Windowing in Computed Tomography Liver Segmentation
PublicationIn computed tomography (CT) imaging, the Hounsfield Unit (HU) scale quantifies radiodensity, but its nonlinear nature across organs and lesions complicates machine learning analysis. This paper introduces an automated method for adaptive HU scale windowing in deep learning-based CT liver segmentation. We propose a new neural network layer that optimizes HU scale window parameters during training. Experiments on the Liver Tumor...
-
Constitutive Modelling of Knitted Abdominal Implants in Numerical Simulations of Repaired Hernia Mechanics
PublicationThe paper presents a numerical approach to describe mechanical behavior of anisotropic textile material, which is a selected abdominal prosthesis. Two constitutive nonlinear concepts are compared. In the first one the material is considered composed from two families of threads (dense net model) and in the second one the material is homogeneous but anisotropic (as proposed by Gassel, Ogden, Holzapfel). Parameters of both models...
-
Examining Quality of Hand Segmentation Based on Gaussian Mixture Models
PublicationResults of examination of various implementations of Gaussian mix-ture models are presented in the paper. Two of the implementations belonged to the Intel’s OpenCV 2.4.3 library and utilized Background Subtractor MOG and Background Subtractor MOG2 classes. The third implementation presented in the paper was created by the authors and extended Background Subtractor MOG2 with the possibility of operating on the scaled version of...
-
Breast MRI segmentation by deep learning: key gaps and challenges
PublicationBreast MRI segmentation plays a vital role in early diagnosis and treatment planning of breast anomalies. Convolutional neural networks with deep learning have indicated promise in automating this process, but significant gaps and challenges remain to address. This PubMed-based review provides a comprehensive literature overview of the latest deep learning models used for breast segmentation. The article categorizes the literature...
-
Scene Segmentation Basing on Color and Depth Images for Kinect Sensor
PublicationIn this paper we propose a method for segmenting single images from Kinect sensor by considering both color and depth information. The algorithm is based on a series of edge detection procedures designed for particular features of the scene objects. RGB and HSV color planes are separately analyzed in the first step with Canny edge detector, resulting in overall color edges mask. In depth images both clear boundaries and smooth...
-
Mechanics of mesh implanted into abdominal wall under repetitive load. Experimental and numerical study
PublicationThere are a number of papers discussing medical and mechanical aspects of ventral hernia management. Despite intensive work on the problem understanding, recurrences of the sickness still happen too often. For that reason new aspects of the problem must be considered. In this paper, a change in the abdominal implant’s stiffness is discussed, which is caused by cyclic loading. Such loading influence abdominal implant e.g. while...
-
Accuracy of Pretreatment Ultrasonography Assessment of Intra-Abdominal Spread in Epithelial Ovarian Cancer: A Prospective Study
PublicationThe aim of this study was to test the accuracy of ultrasonography performed by gynecological oncologists for the preoperative assessment of epithelial ovarian cancer (EOC) spread in the pelvis and abdominal cavity. A prospective, observational cohort study was performed at a single tertiary cancer care unit. Patients with suspected EOC were recruited and underwent comprehensive transvaginal and abdominal ultrasonography performed...
-
Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images
PublicationBackground: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using arti- ficial intelligence. However, only two papers have dealt with complex BI-RADS classifications. Purpose: This study addresses the automatic classification of breast lesions into binary classes (benign vs. ma- lignant)...
-
Combined numerical and experimental approach to determine numerical model of abdominal scaffold
PublicationA proper junction of the prosthesis and the abdominal wall is important in successful hernia repair. The number of tacks should be balanced to assure appropriate mesh fixation and not to induce post-operative pain. Numerical simulations help to find this balance. The study is aimed at creating a proper numerical model of a knitted surgical mesh subjected to boundary conditions and load occurring in the abdominal cavity. Continuous,...
-
Comparison of Selected Neural Network Models Used for Automatic Liver Tumor Segmentation
PublicationAutomatic and accurate segmentation of liver tumors is crucial for the diagnosis and treatment of hepatocellular carcinoma or metastases. However, the task remains challenging due to imprecise boundaries and significant variations in the shape, size, and location of tumors. The present study focuses on tumor segmentation as a more critical aspect from a medical perspective, compared to liver parenchyma segmentation, which is the...
-
Surface sliding in human abdominal wall numerical models: Comparison of single-surface and multi-surface composites
PublicationDetermining mechanical properties of abdominal soft tissues requires a coupled experimental-numerical study, but first an appropriate numerical model needs to be built. Precise modeling of human abdominal wall mechanics is difficult because of its complicated multi-layer composition and large variation between specimens. There are several approaches concerning simplification of numerical models, but it is unclear how far one could...
-
Urban scene semantic segmentation using the U-Net model
PublicationVision-based semantic segmentation of complex urban street scenes is a very important function during autonomous driving (AD), which will become an important technology in industrialized countries in the near future. Today, advanced driver assistance systems (ADAS) improve traffic safety thanks to the application of solutions that enable detecting objects, recognising road signs, segmenting the road, etc. The basis for these functionalities...
-
Orthotropic membrane as a mechanical model of surgical implant in abdominal hernia repair
PublicationEven though the incisional hernia repair surgery is a well known procedure, mechanical properties of the tissue-implant system are unknown so the implantation of the repairing mesh is quite intuitive and, recurrences of the illness still take place. The main objective of the study is to define an operated hernia model that can be used for surgery planning and the assessment of the repair persistence. The load applied to the structure...
-
Application Of Generative Adversarial Network for Data Augmentation and Multiplication to Automated Cell Segmentation of the Corneal Endothelium
PublicationConsidering the automatic segmentation of the endothelial layer, the available data of the corneal endothelium is still limited to a few datasets, typically containing an average of only about 30 images. To fill this gap, this paper introduces the use of Generative Adversarial Networks (GANs) to augment and multiply data. By using the ``Alizarine'' dataset, we train a model to generate a new synthetic dataset with over 513k images....
-
Leveraging spatio-temporal features for joint deblurring and segmentation of instruments in dental video microscopy
PublicationIn dentistry, microscopes have become indispensable optical devices for high-quality treatment and micro-invasive surgery, especially in the field of endodontics. Recent machine vision advances enable more advanced, real-time applications including but not limited to dental video deblurring and workflow analysis through relevant metadata obtained by instrument motion trajectories. To this end, the proposed work addresses dental...
-
Medical Image Segmentation Using Deep Semantic-based Methods: A Review of Techniques, Applications and Emerging Trends
PublicationSemantic-based segmentation (Semseg) methods play an essential part in medical imaging analysis to improve the diagnostic process. In Semseg technique, every pixel of an image is classified into an instance, where each class is corresponded by an instance. In particular, the semantic segmentation can be used by many medical experts in the domain of radiology, ophthalmologists, dermatologist, and image-guided radiotherapy. The authors...
-
Comparison of image pre-processing methods in liver segmentation task
PublicationAutomatic liver segmentation of Computed Tomography (CT) images is becoming increasingly important. Although there are many publications in this field there is little explanation why certain pre-processing methods were utilised. This paper presents a comparison of the commonly used approach of Hounsfield Units (HU) windowing, histogram equalisation, and a combination of these methods to try to ascertain what are the differences...
-
Sperm segmentation and abnormalities detection during the ICSI procedure using machine learning algorithms
Publication(1) About 15-20% of couples struggle with the problem of infertility. 30 to 40% of these cases are caused by abnormalities in the structure and motility of sperm. Sometimes the only possibility for such people is to use the procedure of artificial insemination. CASA systems are used to increase the efficiency of this procedure by selecting the appropriate sperm cell. (2) This paper presents an approach to the sperm classification...
-
Deep Learning-Based Cellular Nuclei Segmentation Using Transformer Model
PublicationAccurate segmentation of cellular nuclei is imperative for various biological and medical applications, such as cancer diagnosis and drug discovery. Histopathology, a discipline employing microscopic examination of bodily tissues, serves as a cornerstone for cancer diagnosis. Nonetheless, the conventional histopathological diagnosis process is frequently marred by time constraints and potential inaccuracies. Consequently, there...