An efficient CNN-BiLSTM model for multi-class intracranial hemorrhage classification

Intracranial hemorrhage (ICH) refers to a type of bleeding that occurs within the skull. ICH may be caused by a wide range of pathology, including, trauma, hypertension, cerebral amyloid angiopa- thy, and cerebral aneurysms. Different subtypes of ICH exist based on their location in the brain, including epidural hemorrhage (EDH), subdural hemorrhage (SDH), subarachnoid hemorrhage (SAH), intraventricular hemorrhage (IVH), and intraparenchymal hemorrhage (IPH). Prompt de- tection and management of ICH are crucial as it is a life-threatening medical emergency with high morbidity and mortality rates. Despite accounting for only 10-15% of all strokes, ICH is respon- sible for over 50% of stroke-related deaths. Therefore, the presence, type, and location of an ICH must be immediately diagnosed so that the patients can receive medical intervention. However, accurately identifying ICH in CT slices can be challenging due to the brain’s complex anatomy and the variability in hemorrhage appearance. [...

Pulmonary Image Segmentation and Registration Algorithms: Towards Regional Evaluation of Obstructive Lung Disease

Pulmonary imaging, including pulmonary magnetic resonance imaging (MRI) and computed tomography (CT), provides a way to sensitively and regionally measure spatially heterogeneous lung structural-functional abnormalities. These unique imaging biomarkers offer the potential for better understanding pulmonary disease mechanisms, monitoring disease progression and response to therapy, and developing novel treatments for improved patient care. To generate these regional lung structure-function measurements and enable broad clinical applications of quantitative pulmonary MRI and CT biomarkers, as a first step, accurate, reproducible and rapid lung segmentation and registration methods are required. In this regard, we first developed a 1H MRI lung segmentation algorithm that employs complementary hyperpolarized 3He MRI functional information for improved lung segmentation. The 1H-3He MRI joint segmentation algorithm was formulated as a coupled continuous min-cut model and solved through convex relaxation, for which a dual coupled continuous max-flow model was proposed and a max-flow-based efficient numerical solver was developed. Experimental results on a clinical dataset of 25 chronic obstructive pulmonary disease (COPD) patients ranging in disease severity demonstrated that the algorithm provided rapid lung segmentation with high accuracy, reproducibility and diminished user interaction. We then developed a general 1H MRI left-right lung segmentation approach by exploring the left-to-right lung volume proportion prior. The challenging volume proportion-constrained multi-region segmentation problem was approximated through convex relaxation and equivalently represented by a max-flow model with bounded flow conservation conditions. This gave rise to a multiplier-based high performance numerical implementation based on convex optimization theories. In 20 patients with mild- to-moderate and severe asthma, the approach demonstrated high agreement with manual segmentation, excellent reproducibility and computational efficiency. Finally, we developed a CT-3He MRI deformable registration approach that coupled the complementary CT-1H MRI registration. The joint registration problem was solved by exploring optical-flow techniques, primal-dual analyses and convex optimization theories. In a diverse group of patients with asthma and COPD, the registration approach demonstrated lower target registration error than single registration and provided fast regional lung structure-function measurements that were strongly correlated with a reference method. Collectively, these lung segmentation and registration algorithms demonstrated accuracy, reproducibility and workflow efficiency that all may be clinically-acceptable. All of this is consistent with the need for broad and large-scale clinical applications of pulmonary MRI and CT

Pattern Recognition

Pattern recognition is a very wide research field. It involves factors as diverse as sensors, feature extraction, pattern classification, decision fusion, applications and others. The signals processed are commonly one, two or three dimensional, the processing is done in real- time or takes hours and days, some systems look for one narrow object class, others search huge databases for entries with at least a small amount of similarity. No single person can claim expertise across the whole field, which develops rapidly, updates its paradigms and comprehends several philosophical approaches. This book reflects this diversity by presenting a selection of recent developments within the area of pattern recognition and related fields. It covers theoretical advances in classification and feature extraction as well as application-oriented works. Authors of these 25 works present and advocate recent achievements of their research related to the field of pattern recognition

Personality Identification from Social Media Using Deep Learning: A Review

Social media helps in sharing of ideas and information among people scattered around the world and thus helps in creating communities, groups, and virtual networks. Identification of personality is significant in many types of applications such as in detecting the mental state or character of a person, predicting job satisfaction, professional and personal relationship success, in recommendation systems. Personality is also an important factor to determine individual variation in thoughts, feelings, and conduct systems. According to the survey of Global social media research in 2018, approximately 3.196 billion social media users are in worldwide. The numbers are estimated to grow rapidly further with the use of mobile smart devices and advancement in technology. Support vector machine (SVM), Naive Bayes (NB), Multilayer perceptron neural network, and convolutional neural network (CNN) are some of the machine learning techniques used for personality identification in the literature review. This paper presents various studies conducted in identifying the personality of social media users with the help of machine learning approaches and the recent studies that targeted to predict the personality of online social media (OSM) users are reviewed

The impact of arterial input function determination variations on prostate dynamic contrast-enhanced magnetic resonance imaging pharmacokinetic modeling: a multicenter data analysis challenge, part II

This multicenter study evaluated the effect of variations in arterial input function (AIF) determination on pharmacokinetic (PK) analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data using the shutter-speed model (SSM). Data acquired from eleven prostate cancer patients were shared among nine centers. Each center used a site-specific method to measure the individual AIF from each data set and submitted the results to the managing center. These AIFs, their reference tissue-adjusted variants, and a literature population-averaged AIF, were used by the managing center to perform SSM PK analysis to estimate Ktrans (volume transfer rate constant), ve (extravascular, extracellular volume fraction), kep (efflux rate constant), and τi (mean intracellular water lifetime). All other variables, including the definition of the tumor region of interest and precontrast T1 values, were kept the same to evaluate parameter variations caused by variations in only the AIF. Considerable PK parameter variations were observed with within-subject coefficient of variation (wCV) values of 0.58, 0.27, 0.42, and 0.24 for Ktrans, ve, kep, and τi, respectively, using the unadjusted AIFs. Use of the reference tissue-adjusted AIFs reduced variations in Ktrans and ve (wCV = 0.50 and 0.10, respectively), but had smaller effects on kep and τi (wCV = 0.39 and 0.22, respectively). kep is less sensitive to AIF variation than Ktrans, suggesting it may be a more robust imaging biomarker of prostate microvasculature. With low sensitivity to AIF uncertainty, the SSM-unique τi parameter may have advantages over the conventional PK parameters in a longitudinal study

Developmental delays and subcellular stress as downstream effects of sonoporation

Posters: no. 2Control ID: 1672434OBJECTIVES: The biological impact of sonoporation has often been overlooked. Here we seek to obtain insight into the cytotoxic impact of sonoporation by gaining new perspectives on anti-proliferative characteristics that may emerge within sonoporated cells. We particularly focused on investigating the cell-cycle progression kinetics of sonoporated cells and identifying organelles that may be stressed in the recovery process. METHODS: In line with recommendations on exposure hardware design, an immersion-based ultrasound platform has been developed. It delivers 1 MHz ultrasound pulses (100 cycles; 1 kHz PRF; 60 s total duration) with 0.45 MPa peak negative pressure to a cell chamber that housed HL-60 leukemia cells and lipid-shelled microbubbles at a 10:1 cell-tobubble ratio (for 1e6/ml cell density). Calcein was used to facilitate tracking of sonoporated cells with enhanced uptake of exogenous molecules. The developmental trend of sonoporated cells was quantitatively analyzed using BrdU/DNA flow cytometry that monitors the cell population’s DNA synthesis kinetics. This allowed us to measure the temporal progression of DNA synthesis of sonoporated cells. To investigate whether sonoporation would upset subcellular homeostasis, post-exposure cell samples were also assayed for various proteins using Western blot analysis. Analysis focus was placed on the endoplasmic reticulum (ER): an important organelle with multi-faceted role in cellular functioning. The post-exposure observation time spanned between 0-24 h. RESULTS: Despite maintaining viability, sonoporated cells were found to exhibit delays in cell-cycle progression. Specifically, their DNA synthesis time was lengthened substantially (for HL-60 cells: 8.7 h for control vs 13.4 h for the sonoporated group). This indicates that sonoporated cells were under stress: a phenomenon that is supported by our Western blot assays showing upregulation of ER-resident enzymes (PDI, Ero1), ER stress sensors (PERK, IRE1), and ER-triggered pro-apoptotic signals (CHOP, JNK). CONCLUSIONS: Sonoporation, whilst being able to facilitate internalization of exogenous molecules, may inadvertently elicit a cellular stress response. These findings seem to echo recent calls for reconsideration of efficiency issues in sonoporation-mediated drug delivery. Further efforts would be necessary to improve the efficiency of sonoporation-based biomedical applications where cell death is not desirable.postprin

A study on the change in plasma membrane potential during sonoporation

Posters: no. 4Control ID: 1680329OBJECTIVES: There has been validated that the correlation of sonoporation with calcium transients is generated by ultrasound-mediated microbubbles activity. Besides calcium, other ionic flows are likely involved in sonoporation. Our hypothesis is the cell electrophysiological properties are related to the intracellular delivery by ultrasound and microbubbles. In this study, a real-time live cell imaging platform is used to determine whether plasma membrane potential change is related to the sonoporation process at the cellular level. METHODS: Hela cells were cultured in DMEM supplemented with 10% FBS in Opticell Chamber at 37 °C and 5% CO2, and reached 80% confluency before experiments. The Calcein Blue-AM, DiBAC4(3) loaded cells in the Opticell chamber filled with PI solution and Sonovue microbubbles were immerged in a water tank on a inverted fluorescence microscope. Pulsed ultrasound (1MHz freq., 20 cycles, 20Hz PRF, 0.2-0.5MPa PNP) was irradiated at the angle of 45° to the region of interest for 1s.The real-time fluorescence imaging for different probes was acquired by a cooled CCD camera every 20s for 10min. The time-lapse fluorescence images were quantitatively analyzed to evaluate the correlation of cell viability, intracellular delivery with plasma membrane potential change. RESULTS: Our preliminary data showed that the PI fluorescence, which indicated intracellular delivery, was immediately accumulated in cells adjacent to microbubbles after exposure, suggesting that their membranes were damaged by ultrasound-activated microbubbles. However, the fluorescence reached its highest level within 4 to 6 minutes and was unchanged thereafter, indicating the membrane was gradually repaired within this period. Furthermore, using DIBAC4(3), which detected the change in the cell membrane potential, we found that the loss of membrane potential might be associated with intracellular delivery, because the PI fluorescence accumulation was usually accompanied with the change in DIBAC4 (3) fluorescence. CONCLUSIONS: Our study suggests that there may be a linkage between the cell membrane potential change and intracellular delivery mediated by ultrasound and microbubbles. We also suggest that other ionic flows or ion channels may be involved in the cell membrane potential change in sonoporation. Further efforts to explore the cellular mechanism of this phenomenon will improve our understanding of sonoporation.postprin