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Adversarial attacks and adversarial training for burn image segmentation based on deep learning
AbstractDeep learning has been widely applied in the fields of image classification and segmentation, while adversarial attacks can impact the model ’s results in image segmentation and classification. Especially in medical images, due to constraints from factors like shooting angles, environmental lighting, and diverse photography devices, medical images typically contain various forms of noise. In order to address the impact of these physica lly meaningful disturbances on existing deep learning models in the application of burn image segmentation, we simulate attack methods inspired by natural phenomena and propose an ...
Source: Medical and Biological Engineering and Computing - May 2, 2024 Category: Biomedical Engineering Source Type: research

BraNet: a mobil application for breast image classification based on deep learning algorithms
This study aims to develop an open-source mobile app named “BraNet” for 2D breast imaging segmentation and classification using deep learning algorithms. During the phase off-line, an SNGAN model was previously trained for synthetic image generation, and subsequently, these images were used to pre-trained SAM and ResNet18 segmentation and classification models. During phase online, the BraNet app was developed using the react native framework, offering a modular deep-learning pipeline for mammography (DM) and ultrasound (US) breast imaging classification. This application operates on a client–server architecture and ...
Source: Medical and Biological Engineering and Computing - May 2, 2024 Category: Biomedical Engineering Source Type: research

Subject-specific trunk segmental masses prediction for musculoskeletal models using artificial neural networks
AbstractAccurate determination of body segment parameters is crucial for studying human movement and joint forces using musculoskeletal (MSK) models. However, existing methods for predicting segment mass have limited generalizability and sensitivity to body shapes. With recent advancements in machine learning, this study proposed a novel artificial neural network-based method for computing subject-specific trunk segment mass and center of mass (CoM) using only anthropometric measurements. We first developed, trained, and validated two artificial neural networks that used anthropometric measurements as input to predict body...
Source: Medical and Biological Engineering and Computing - May 2, 2024 Category: Biomedical Engineering Source Type: research

Efficient skin lesion segmentation with boundary distillation
AbstractMedical image segmentation models are commonly known for their complex structures, which often render them impractical for use on edge computing devices and compromising efficiency in the segmentation process. In light of this, the industry has proposed the adoption of knowledge distillation techniques. Nevertheless, the vast majority of existing knowledge distillation methods are focused on the classification tasks of skin diseases. Specifically, for the segmentation tasks of dermoscopy lesion images, these knowledge distillation methods fail to fully recognize the importance of features in the boundary regions of...
Source: Medical and Biological Engineering and Computing - May 1, 2024 Category: Biomedical Engineering Source Type: research

Obstructive sleep apnea detection during wakefulness: a comprehensive methodological review
AbstractObstructive sleep apnea (OSA) is a chronic condition affecting up to 1 billion people, globally. Despite this spread, OSA is still thought to be underdiagnosed. Lack of diagnosis is largely attributed to the high cost, resource-intensive, and time-consuming nature of existing diagnostic technologies during sleep. As individuals with OSA do not show many symptoms other than daytime sleepiness, predicting OSA while the individual is awake (wakefulness) is quite challenging. However, research especially in the last decade has shown promising results for quick and accurate methodologies to predict OSA during wakefulnes...
Source: Medical and Biological Engineering and Computing - April 17, 2024 Category: Biomedical Engineering Source Type: research

Reconstructive interpolation for pulse wave estimation to improve local PWV measurement of carotid artery
In conclusion, the reconstructive interpolation for the pulse wave estimation improves the accuracy and repeatability of the carotid local PWV measurement.Graphical abstractUltrasonic transit time-based local pulse wave velocity (PWV) measurement is defined as the distance between two beam positions on a segment of common carotid artery (CCA) divided by the transit time of the pulse wave (PW). However, PWs estimated from ultrasonic radio frequency (RF) signals with a limited number of frames using the motion tracking are typically discontinuous. In this work, a method that involves motion tracking combined with reconstruct...
Source: Medical and Biological Engineering and Computing - April 17, 2024 Category: Biomedical Engineering Source Type: research

Assessment of visual fatigue in SSVEP-based brain-computer interface: a comprehensive study
AbstractFatigue deteriorates the performance of a brain-computer interface (BCI) system; thus, reliable detection of fatigue is the first step to counter this problem. The fatigue evaluated by means of electroencephalographic (EEG) signals has been studied in many research projects, but widely different results have been reported. Moreover, there is scant research when considering the fatigue on steady-state visually evoked potential (SSVEP)-based BCI. Therefore, nowadays, fatigue detection is not a completely solved topic. In the current work, the issues found in the literature that led to the differences in the results a...
Source: Medical and Biological Engineering and Computing - April 17, 2024 Category: Biomedical Engineering Source Type: research

Clinical evaluation of a patient participation assessment system for upper extremity rehabilitation exercises
Abstract    In conventional and robotic rehabilitation, the patient ’s active participation in exercises is essential for the maximum functional output to be received from therapy. In rehabilitation exercises performed with robotic devices, the difficulty levels of therapy tasks and the device assistance are adjusted based on the patient’s therapy performance to improve active participation. However, the existing therapy performance evaluation methods are based on either some specific device designs or certain therapy tasks, which limits their widespread use. In this paper, the effectiveness of a participation assess...
Source: Medical and Biological Engineering and Computing - April 17, 2024 Category: Biomedical Engineering Source Type: research

A novel transformer-based aggregation model for predicting gene mutations in lung adenocarcinoma
AbstractIn recent years, predicting gene mutations on whole slide imaging (WSI) has gained prominence. The primary challenge is extracting global information and achieving unbiased semantic aggregation. To address this challenge, we propose a novel Transformer-based aggregation model, employing a self-learning weight aggregation mechanism to mitigate semantic bias caused by the abundance of features in WSI. Additionally, we adopt a random patch training method, which enhances model learning richness by randomly extracting feature vectors from WSI, thus addressing the issue of limited data. To demonstrate the model ’s eff...
Source: Medical and Biological Engineering and Computing - April 17, 2024 Category: Biomedical Engineering Source Type: research

Correction to: Computer simulation ‑based nanothermal field and tissue damage analysis for cardiac tumor ablation
(Source: Medical and Biological Engineering and Computing)
Source: Medical and Biological Engineering and Computing - April 17, 2024 Category: Biomedical Engineering Source Type: research

Study on mechanical properties of dual-channel cryogenic 3D printing scaffold for mandibular defect repair
AbstractMandibular defect repair has always been a clinical challenge, facing technical bottleneck. The new materials directly affect technological breakthroughs in mandibular defect repair field. Our aim is to fabricate a scaffold of advanced biomaterials for repairing of small mandibular defect. Therefore, a novel dual-channel scaffold consisting of silk fibroin/collagen type-I/hydroxyapatite (SCH) and polycaprolactone/hydroxyapatite (PCL/HA) was fabricated by cryogenic 3D printing technology with double nozzles. The mechanical properties and behaviors of the dual-channel scaffold were investigated by performing uniaxial...
Source: Medical and Biological Engineering and Computing - April 16, 2024 Category: Biomedical Engineering Source Type: research

From PDB files to protein features: a comparative analysis of PDB bind and STCRDAB datasets
AbstractUnderstanding protein structures is crucial for various bioinformatics research, including drug discovery, disease diagnosis, and evolutionary studies. Protein structure classification is a critical aspect of structural biology, where supervised machine learning algorithms classify structures based on data from databases such as Protein Data Bank (PDB). However, the challenge lies in designing numerical embeddings for protein structures without losing essential information. Although some effort has been made in the literature, researchers have not effectively and rigorously combined the structural and sequence-base...
Source: Medical and Biological Engineering and Computing - April 16, 2024 Category: Biomedical Engineering Source Type: research

Intelligent salivary biosensors for periodontitis: in vitro simulation of oral oxidative stress conditions
This study focused on hydrogen peroxide, lipopolysaccharide (LPS), and lactic acid as salivary non-protein biomarkers for oxidative stress conditions of periodontitis. Electrochemical analysis of artificial saliva was done using Gamry with increasing hydrogen peroxide, bLPS, and lactic acid concentrations. Electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV) were conducted. From EIS data, change in capacitance and CV plot area were calculated for each test condition. Hydrogen peroxide groups had a decrease in CV area and an increase in percentage change in capacitance, lipopolysaccharide groups had a de...
Source: Medical and Biological Engineering and Computing - April 13, 2024 Category: Biomedical Engineering Source Type: research

Lung pneumonia severity scoring in chest X-ray images using transformers
AbstractTo create robust and adaptable methods for lung pneumonia diagnosis and the assessment of its severity using chest X-rays (CXR), access to well-curated, extensive datasets is crucial. Many current severity quantification approaches require resource-intensive training for optimal results. Healthcare practitioners require efficient computational tools to swiftly identify COVID-19 cases and predict the severity of the condition. In this research, we introduce a novel image augmentation scheme as well as a neural network model founded on Vision Transformers (ViT) with a small number of trainable parameters for quantify...
Source: Medical and Biological Engineering and Computing - April 9, 2024 Category: Biomedical Engineering Source Type: research

Analysis of reading-task-based brain connectivity in dyslexic children using EEG signals
In conclusion, the present study identified distinct graph measures between groups when performing a reading task and showed possible evidence for compromised brain networks in dyslexic group.Graphical abstract (Source: Medical and Biological Engineering and Computing)
Source: Medical and Biological Engineering and Computing - April 8, 2024 Category: Biomedical Engineering Source Type: research