Medical and Biological Engineering and Computing Medical and Biological Engineering and Computing RSS feedThis is an RSS file. You can use it to subscribe to this data in your favourite RSS reader or to display this data on your own website or blog.

Generative adversarial network: a statistical-based deep learning paradigm to improve detecting breast cancer in thermograms
AbstractThermography, as a harmless modality, thanks to its low equipment complexity in parallel with quick and cheap access, has been able to come up as a method with significant potential in the diagnosis of some cancers in recent years. However, the complexity of the images resulting from this method has caused the use of deep learning to interpret thermograms. A limiting factor in this process is the strong dependence of deep learning methods on the number of training data, which is a serious challenge in thermography due to the young age of this technology and the lack of available images. In this paper, an attempt is...
Source: Medical and Biological Engineering and Computing - December 27, 2023 Category: Biomedical Engineering Source Type: research

Finite element modeling and analysis of effect of preexisting cervical degenerative disease on the spinal cord during flexion and extension
This study aimed to investigate the effect of various types of preexisting herniated cervical disc and the ligamentum flavum ossification on the spinal cord during cervical flexion and extension. A detailed dynamic fluid-structure interaction finite element model of the cervical spine with the spinal cord was developed and validated. The changes of von Mises stress and maximum principal strain within the spinal cord in the period of normal, hyperflexion, and hyperextension were investigated, considering various types and grades of disc herniation and ossification of the ligamentum flavum. The flexion and extension of the c...
Source: Medical and Biological Engineering and Computing - December 27, 2023 Category: Biomedical Engineering Source Type: research

MCAFNet: multiscale cross-layer attention fusion network for honeycomb lung lesion segmentation
In this study, we propose a novel multi-scale cross-layer attention fusion network (MCAFNet) specifically designed for the segmentation of honeycomb lung lesions, taking into account their shape specificity and similarity to surrounding vascular shadows. The MCAFNet incorporates several key modules to enhance the segmentation performance. Firstly, a multiscale aggregation (MIA) module is introduced in the input part to preserve spatial information during downsampling. Secondly, a cross-layer attention fusion (CAF) module is proposed to capture multiscale features by integrating channel information and spatial information f...
Source: Medical and Biological Engineering and Computing - December 27, 2023 Category: Biomedical Engineering Source Type: research

Automated identification of protein expression intensity and classification of protein cellular locations in mouse brain regions from immunofluorescence images
AbstractKnowledge of protein expression in mammalian brains at regional and cellular levels can facilitate understanding of protein functions and associated diseases. As the mouse brain is a typical mammalian brain considering cell type and structure, several studies have been conducted to analyze protein expression in mouse brains. However, labeling protein expression using biotechnology is costly and time-consuming. Therefore, automated models that can accurately recognize protein expression are needed. Here, we constructed machine learning models to automatically annotate the protein expression intensity and cellular lo...
Source: Medical and Biological Engineering and Computing - December 27, 2023 Category: Biomedical Engineering Source Type: research

A dynamic spatiotemporal model for fall warning and protection
This study proposed the concept of identifying “Imbalance Point” to warn the body imbalance, allowing sufficient time to recover balance. And if falling cannot be avoided, an impact sign is released by detecting the “Fall Point” prior to the impact. To achieve this goal, motion prediction model and balance recovery model are integrated i nto a spatiotemporal framework to analyze dynamic and kinematic features of body motion. Eight healthy young volunteers participated in three sets of experiment: Normal trial, Recovery trial and Fall trial. The body motion in the trials was recorded using Microsoft Azure Kinect. Th...
Source: Medical and Biological Engineering and Computing - December 23, 2023 Category: Biomedical Engineering Source Type: research

Identification of key gene expression associated with quality of life after recovery from COVID-19
In this study, a group of machine learning algorithms analyzed the whole blood RNA-seq data from patients with different PASC levels. The purpose of this analysis was to identify the gene markers associated with PASC and the special expression patterns for different PASC levels. By comparing the quality of life of patients after the acute phase of COVID-19 and before the disease, samples in the dataset were divided into three groups, namely, “Better,” “The Same,” and “Worse.” Each patient was represented by the expression levels of 58,929 genes. The machine learning-based workflow included six feature-ranking a...
Source: Medical and Biological Engineering and Computing - December 21, 2023 Category: Biomedical Engineering Source Type: research

Effect of transmural pressure on the estimation of arterial stiffness index from the photoplethysmographic waveform
AbstractThe aim of this study was to find the effect of transmural pressure on the determination of the photoplethysmographic (PPG) waveform arterial stiffness index (PPGAI). The study was conducted on 51 subjects without diagnosis of cardiovascular disease, aged between 24 and 74  years. The relation between the transmural pressure, which is the difference between the arterial blood pressure and the PPG sensor contact pressure, and the PPGAI was determined. PPG, beat-to-beat blood pressure, and sensor contact pressure signals were recorded from the index, middle, and ring f inger. The PPG sensor contact pressure of the i...
Source: Medical and Biological Engineering and Computing - December 21, 2023 Category: Biomedical Engineering Source Type: research

Driving fatigue detection based on brain source activity and ARMA model
AbstractFatigue among drivers is a significant issue in society, and according to organizational reports, it substantially contributes to accidents. So accurate fatigue detection in drivers plays a crucial role in reducing the number of people fatalities or injured resulting from accidents. Several methods are proposed for fatigue driver recognition among which electroencephalography (EEG) is one. This paper proposed a method for fatigue recognition by EEG signals with extracted features from source and sensor spaces. The proposed method starts with preprocessing by applying filtering and artifact rejection. Then source lo...
Source: Medical and Biological Engineering and Computing - December 20, 2023 Category: Biomedical Engineering Source Type: research

Strength of ensemble learning in automatic sleep stages classification using single-channel EEG and ECG signals
In this study, a strong ensemble learning model is proposed to enhance the ability of classification models in accurate sleep staging, particularly in multi-class classification. We asserted that high-accuracy sleep classification is achievable using only single-channel electroencephalogram (EEG) and electrocardiogram (ECG) by combining their best-extractable features in the time and frequency domains we recommended. More importantly, the superiority of the recommended method, which is the simultaneous use of stacking and bagging, over conventional machine learning classifiers in sleep staging was demonstrated, using the M...
Source: Medical and Biological Engineering and Computing - December 20, 2023 Category: Biomedical Engineering Source Type: research

Sixty years in service to international biomedical engineering community
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Source: Medical and Biological Engineering and Computing - December 19, 2023 Category: Biomedical Engineering Source Type: research

DMpDP: a Diagnostic Multiple-patient DermoFeature Profile store-and-forward teledermoscopy system
AbstractTelehealth demand is rapidly growing along with the necessity of providing wide-scale services covering multiple patients at the same time. In this work, the development of a store-and-forward (SAF) teledermoscopy system was considered. The dermoFeatures profile (DP) was proposed to decrease the size of the original dermoscopy image using its most significant features in the form of a newly generated diagonal alignment to generate a small-sized image DP, which is based on the extraction of a weighted intensity-difference frequency (WIDF) features along with morphological features (MOFs). These DPs were assembled to...
Source: Medical and Biological Engineering and Computing - December 19, 2023 Category: Biomedical Engineering Source Type: research

OVME-REG: Harris hawks optimization algorithm based optimized variational mode extraction for eye blink artifact removal from EEG signal
AbstractThe electroencephalogram (EEG) recordings from the human brain are useful for detecting various brain syndromes. These recordings are typically contaminated by high amplitude eye blink artifacts, which leads to deliberate misinterpretation of the EEG signal. Recently, variational mode extraction (VME) has been used to detect eye blink artifacts. But, the VME performance is impacted by the balancing parameter and center frequency selection. Therefore, this research uses two metaheuristic algorithms, particle swarm optimization and Harris hawks optimization, to determine the optimal set of the VME parameters. In the ...
Source: Medical and Biological Engineering and Computing - December 18, 2023 Category: Biomedical Engineering Source Type: research

Improving signal-to-noise ratio by maximal convolution of longitudinal and transverse magnetization components in MRI: application to the breast cancer detection
ConclusionBy convolving two orthogonal magnetization vectors, the qualified images with higher new SNR were created, which included the image with the best SNR. In other words, to optimize the adoption of MRI technique and enable the possibility of wider use, an optimal and cost-effective examination has been suggested. Our proposal aims to shorten the MRI examination to further reduce interpretation times while maintaining primary sensitivity.SignificanceOur findings may help to quantitatively identify the primary sources of each type of solid and sequential cancer.Graphical AbstractA new index was defined as full width i...
Source: Medical and Biological Engineering and Computing - December 15, 2023 Category: Biomedical Engineering Source Type: research

IoT-based COVID-19 detection using recalling-enhanced recurrent neural network optimized with golden eagle optimization algorithm
AbstractNew potential for healthcare has been made possible by the development of the Internet of Medical Things (IoMT) with deep learning. This is applied for a broad range of applications. Normal medical devices together with sensors can gather important data when connected to the Internet, and deep learning uses this data to reveal symptoms and patterns and activate remote care. In recent years, the COVID-19 pandemic caused more mortality. Millions of people have been affected by this virus, and the number of infections is continually rising daily. To detect COVID-19, researchers attempt to utilize medical imaging and d...
Source: Medical and Biological Engineering and Computing - December 14, 2023 Category: Biomedical Engineering Source Type: research

A multi-view assisted registration network for MRI registration pre- and post-therapy
AbstractImage registration of magnetic resonance imaging (MRI) pre- and post-therapy is an important part of evaluating the effect of therapy in tumor patients. The accuracy of evaluation results heavily relies on the alignment of the MRI image after registration. Although recent advancements have been made in medical image registration, applying these methods to MRI registration pre- and post-therapy remains challenging. Existing methods typically utilize single-view data for registration. However, when applied to MRI data where some slices are clear while others are blurred, these methods can be misled by erroneous spati...
Source: Medical and Biological Engineering and Computing - December 14, 2023 Category: Biomedical Engineering Source Type: research