Australasian Physical and Engineering Sciences in Medicine Australasian Physical and Engineering Sciences in Medicine 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.

Evaluating the difference in walk patterns among normal-weight and overweight/obese individuals in real-world surfaces using statistical analysis and deep learning methods with inertial measurement unit data
The objective of this study was to statistically evaluate the variations in the walk patterns of individuals belonging to two BMI groups across a wide range of walking surfaces and to investigate whether a deep learning method could classify the BMI-specific walk patterns wi th similar variations. Data collected by wearable inertial measurement unit (IMU) sensors attached to individuals with two different BMI were collected while walking on real-world surfaces. In addition to traditional statistical analysis tools, an advanced deep learning-based neural network was used to evaluate and classify the BMI-specific walk patter...
Source: Australasian Physical and Engineering Sciences in Medicine - November 9, 2022 Category: Biomedical Engineering Source Type: research

Combined clustered scan-based metal artifact reduction algorithm (CCS-MAR) for ultrasound-guided cardiac radioablation
AbstractCardiac radioablation is a promising treatment for cardiac arrhythmias, but accurate dose delivery can be affected by heart motion. For this reason, real-time cardiac motion monitoring during radioablation is of paramount importance. Real-time ultrasound (US) guidance can be a solution. The US-guided cardiac radioablation workflow can be simplified by the simultaneous US and planning computed tomography (CT) acquisition, which can result in US transducer-induced metal artifacts on the planning CT scans. To reduce the impact of these artifacts, a new metal artifact reduction (MAR) algorithm (named: Combined Clustere...
Source: Australasian Physical and Engineering Sciences in Medicine - November 9, 2022 Category: Biomedical Engineering Source Type: research

Fluid dynamics of the upper airway in pediatric patients with severe laryngomalacia
AbstractLaryngomalacia is the top cause of pediatric laryngeal wheeze. We used computational fluid dynamics to study the inspiratory airflow dynamics in severe pediatric laryngomalacia. Computed tomography was performed on the upper airways of two infants, one with severe laryngomalacia and one with normal airway, and 3D models were reconstructed. ANSYS CFD-POST software was used to simulate airflow in these models to compare the volumetric flow rate, flow velocity, pressure, wall shear, and vortex. The volume flow rate in the laryngomalacia model was significantly reduced compared with the control model. Under inspiratory...
Source: Australasian Physical and Engineering Sciences in Medicine - November 3, 2022 Category: Biomedical Engineering Source Type: research

Phenomenological characterization of blood ’s intermediate shear rate: a new concept for hemorheology
In this study, the intermediate shear rate is introduced and defined when the effect of aggregation on the change of blood viscosity is diminished; and afterwards, the alteration in the blood viscosity is dominantly affected by the deformation of RBCs. With this respect, modeling the effective parameters on the blood shear-thinning behavior including hematocrit and plasma viscosity was performed for the two different shear regions discriminated by the proposed intermediate shear rates. The presented rheological model reflects a phenomenological approach to assess the human blood viscosity with an average error of ± 5% c...
Source: Australasian Physical and Engineering Sciences in Medicine - November 1, 2022 Category: Biomedical Engineering Source Type: research

The single-channel dry electrode SSVEP-based biometric approach: data augmentation techniques against overfitting for RNN-based deep models
AbstractBiometric studies based on electroencephalography (EEG) have received increasing attention because each individual has a dynamic and unique pattern. However, classic EEG-based biometrics have significant deficiencies, including noise-prone signals, gel-based electrodes, and the need for multi-training/multi-channel acquisition and high mental effort. In contrast, steady-state visually evoked potential (SSVEP)-based biometrics have the important advantages of high signal-to-noise ratio and untrained usage. Dynamic brain potential responses are a natural subconscious activity and can be elicited by flickering lights ...
Source: Australasian Physical and Engineering Sciences in Medicine - November 1, 2022 Category: Biomedical Engineering Source Type: research

Evaluating the effect of high-density measurement mode on patient-specific quality assurance for head and neck cancer with ArcCHECK
AbstractThe high-density measurement (HDm) mode of the ArcCHECK device can achieve a twofold resolution enhancement compared to the standard measurement (Sm) mode. The aim of this study was to evaluate the effect of HDm on the gamma passing rate (GPR) for the patient-specific quality assurance (PSQA) in head and neck cancer. We retrospectively evaluated 30 patients who underwent volumetric modulated arc therapy (VMAT) for head and neck cancer. Absolute gamma analysis was performed on Sm and HDm data. We also investigated correlations between the modulation complexity score for VMAT (MCSv) and differences in the GPR between...
Source: Australasian Physical and Engineering Sciences in Medicine - November 1, 2022 Category: Biomedical Engineering Source Type: research

Performance analyses of five neural network classifiers on nodule classification in lung CT images using WEKA: a comparative study
In this report, we are presenting our work on performance analyses of five different neural network classifiers viz. MLP, DL4JMLP, logistic regression, SGD and simple logistic classifier in lung nodule detection using WEKA interface. To the best of our knowledge, this report demonstrates first use of WEKA for comparative performance analyses of neural network classifiers in identifying lung nodules from lung CT-images. A total of 624 handcrafted features from 52 numbers of lung CT-images collected randomly from Lung Image Database Consortium (LIDC) were fed into WEKA to evaluate the performances of the classifiers under fo...
Source: Australasian Physical and Engineering Sciences in Medicine - October 31, 2022 Category: Biomedical Engineering Source Type: research

Intercomparison of S-Factor values calculated in Zubal voxelized phantom for eleven radionuclides commonly used in targeted prostate cancer therapy
In this study we aimed at comparing various radionuclides ordinarily used in targeted prostate cancer therapy, thereby evaluating S-Factor parameter in the prostate organs as well as in its surrounding healthy tissues, namely the urinary bladder and rectum. InterDosi code version 1.1 was used to estimate S-Factor values in Zubal voxelized phantom for 11 radionuclides, namely225Ac,21At,67Cu,125I,131I,212Pb,177Lu,223Ra,161 Tb,227Th and90Y. The prostate organ was considered the source of different ionizing radiation emitted by the radionuclides cited above. The results showed that among all studied alpha-emitting radionuclid...
Source: Australasian Physical and Engineering Sciences in Medicine - October 31, 2022 Category: Biomedical Engineering Source Type: research

SIZE-specific dose estimate for lower-limb CT
AbstractThe Computed Tomography Dose Index (CTDI) is an indicator for dose management in computed tomography (CT), but has limited use for patient dosimetry. To evaluate the patient dose, the size-specific dose estimate (SSDE), reported by the American Association of Physics in Medicine task groups 204, 220, and 293, must be calculated by the CTDIvol(z) displayed on the CT console, and the conversion factor f(D(z)) from the effective diameter (DEff) or water equivalent diameter (Dw). However, no reports have verified the appropriateness of using the 320-mm diameter phantom for dose assessment in CT examinations involving t...
Source: Australasian Physical and Engineering Sciences in Medicine - October 31, 2022 Category: Biomedical Engineering Source Type: research

Analysing the effects of metallic biomaterial design and imaging sequences on MRI interpretation challenges due to image artefacts
This study reveals that image artefacts directly depend on material content, implant volume, geometry, and imaging sequence selection. The minor artefact effect of T2SE provides more accurate MR images than T1GRE regarding the interpretation of the images of the patients with biometals. The higher magnetic susceptibility of biometals causes more deterioration of the images. (Source: Australasian Physical and Engineering Sciences in Medicine)
Source: Australasian Physical and Engineering Sciences in Medicine - October 28, 2022 Category: Biomedical Engineering Source Type: research

Accuracy of Acuros $$^{\text {TM}}$$ BV as determined from GATE monte-carlo simulation
In this study we have assessed the accuracy of ABV dose calculations within a range of materials relevant to high dose rate brachytherapy with an iridium-192 (\(^{\text {192}}\)Ir) source. Accuracy assessment has been achieved by implementing a modelled GamaMed Plus\(^{\text {192}}\)Ir source within a series of phantoms using the GEANT4 Application for Emission Tomography (GATE) to calculate dose for comparison with dose as determined by ABV. Comparisons between GATE and ABV were made using point-to-point profile comparisons and 1D gamma analysis. Source validation results yielded good agreement with published data. Spectr...
Source: Australasian Physical and Engineering Sciences in Medicine - October 27, 2022 Category: Biomedical Engineering Source Type: research

ACTNet: asymmetric convolutional transformer network for diabetic foot ulcers classification
AbstractMost existing image classification methods have achieved significant progress in the field of natural images. However, in the field of diabetic foot ulcer (DFU) where data is scarce and complex, the accurate classification of data is still a thorny problem. In this paper, we propose an Asymmetric Convolutional Transformer Network (ACTNet) for the multi-class (4-class) classification task of DFU. Specifically, in order to strengthen the expressive ability of the network, we design an asymmetric convolutional module in the front part of the network to model the relationship between local pixels, extract the underlyin...
Source: Australasian Physical and Engineering Sciences in Medicine - October 24, 2022 Category: Biomedical Engineering Source Type: research

Don ’t let Yoda or Bill and Ted write your papers: instead, here’s some tips from some editors on getting your paper published
(Source: Australasian Physical and Engineering Sciences in Medicine)
Source: Australasian Physical and Engineering Sciences in Medicine - October 17, 2022 Category: Biomedical Engineering Source Type: research

Clinical pilot study for EPID-based in vivo dosimetry using EPIgray ™ for head and neck VMAT
AbstractThis work details the clinical pilot study methodology used at Wellington Blood and Cancer Centre (WBCC) before the clinical release of in vivo dosimetry (IVD) system EPIgray ™ for head and neck (H&N) volumetric modulated arc therapy (VMAT) treatments. Clinical pilot studies make it possible to select appropriate, department-specific tolerance ranges for the treatment type and site under investigation. An IVD clinical pilot study of H&N VMAT treatments was conducted over 3  months at WBCC using EPIgray™ dose reconstruction software and included 12 patients and 32 individual treatment fractions. Statist...
Source: Australasian Physical and Engineering Sciences in Medicine - October 13, 2022 Category: Biomedical Engineering Source Type: research

Predictive gamma passing rate of 3D detector array-based volumetric modulated arc therapy quality assurance for prostate cancer via deep learning
AbstractTo predict the gamma passing rate (GPR) of the three-dimensional (3D) detector array-based volumetric modulated arc therapy (VMAT) quality assurance (QA) for prostate cancer using a convolutional neural network (CNN) with the 3D dose distribution. One hundred thirty-five VMAT plans for prostate cancer were selected: 110 plans were used for training and validation, and 25 plans were used for testing. Verification plans were measured using a helical 3D diode array (ArcCHECK). The dose distribution on the detector element plane of these verification plans was used as input data for the CNN model. The measured GPR (mGP...
Source: Australasian Physical and Engineering Sciences in Medicine - October 6, 2022 Category: Biomedical Engineering Source Type: research