Cloud based ensemble machine learning approach for smart detection of epileptic seizures using higher order spectral analysis
AbstractThe present paper proposes a smart framework for detection of epileptic seizures using the concepts of IoT technologies, cloud computing and machine learning. This framework processes the acquired scalp EEG signals by Fast Walsh Hadamard transform. Then, the transformed frequency-domain signals are examined using higher-order spectral analysis to extract amplitude and entropy-based statistical features. The extracted features have been selected by means of correlation-based feature selection algorithm to achieve more real-time classification with reduced complexity and delay. Finally, the samples containing selecte...
Source: Australasian Physical and Engineering Sciences in Medicine - January 12, 2021 Category: Biomedical Engineering Source Type: research

Detection of ventricular arrhythmia using hybrid time –frequency-based features and deep neural network
In this study, a VF/VT classification scheme has been proposed using a deep neural network (DNN) approach using hybrid time –frequency-based features. Two annotated public domain ECG databases (CUDB and VFDB) were used as training, test, and validation of datasets. The main motivation of this study was to implement a deep learning model for the classification of the VF/VT conditions and compared the results with other standard machine learning algorithms. The signal is decomposed with the wavelet transform, empirical mode decomposition (EMD) and variable mode decomposition (VMD) approaches and twenty-four are extract...
Source: Australasian Physical and Engineering Sciences in Medicine - January 8, 2021 Category: Biomedical Engineering Source Type: research

Detection of focal and non-focal EEG signals using non-linear features derived from empirical wavelet transform rhythms
AbstractSurgery is recommended for epilepsy diagnosis in cases where patients do not respond well to anti-epilepsy medications. Successful surgery is essentially dependent on the area suffered from epilepsy, i.e., focal area. Electroencephalogram (EEG) signals are considered a powerful tool to identify focal or non-focal (normal) areas. In this work, we propose an automated method for focal and non-focal EEG signal identification, taking into account non-linear features derived from rhythms in the empirical wavelet transform (EWT) domain. The research paradigm is related to the decomposition of EEG signals into the delta, ...
Source: Australasian Physical and Engineering Sciences in Medicine - January 8, 2021 Category: Biomedical Engineering Source Type: research

Hands-on engineering courses in the COVID-19 pandemic: adapting medical device design for remote learning
AbstractThe COVID-19 pandemic has challenged the status quo of engineering education, especially in highly interactive, hands-on design classes. Here, we present an example of how we effectively adjusted an intensive hands-on, group project-based engineering course, Medical Device Design& Innovation, to a remote learning curriculum. We first describe the modifications we made. Drawing from student pre and post feedback surveys and our observations, we conclude that our adaptations were overall successful. Our experience may guide educators who are transitioning their engineering design courses to remote learning. (Sour...
Source: Australasian Physical and Engineering Sciences in Medicine - January 7, 2021 Category: Biomedical Engineering Source Type: research

Automated detection of arrhythmia from electrocardiogram signal based on new convolutional encoded features with bidirectional long short-term memory network classifier
AbstractEarly detection of cardiac arrhythmia is needed to reduce mortality. Automatically detecting the cardiac arrhythmias is a very challenging task. In this paper, a new deep convolutional encoded feature (CEF) based on non-linear compression composition is applied to diminish the ECG signal segment size. Bidirectional long short-term memory (BLSTM) network classifier has been proposed to detect arrhythmias from the ECG signal, which is encoded by the convolutional encoder. These encoded features are used as the input to BLSTM network classifier. For performance comparison, three other classifiers, namely unidirectiona...
Source: Australasian Physical and Engineering Sciences in Medicine - January 6, 2021 Category: Biomedical Engineering Source Type: research

Shell properties and concentration stability of acoustofluidic delivery agents
AbstractThis paper investigates the shell elastic properties and the number-concentration stability of a new acoustofluidic delivery agent liposome in comparison to Definity ™, a monolayer ultrasonic contrast agent microbubble. The frequency dependent attenuation of an acoustic beam passing through a microbubble suspension was measured to estimate the shell parameters. The excitation voltage was adjusted to ensure constant acoustic pressure at all frequencies. The pre ssure was kept at the lowest possible magnitude to ensure that effects from nonlinear bubble behaviour which are not considered in the analytical model...
Source: Australasian Physical and Engineering Sciences in Medicine - January 4, 2021 Category: Biomedical Engineering Source Type: research

An alternative to the use of lead for patient treatment shielding in superficial radiotherapy
AbstractLead shielding is commonly used in the delivery of superficial radiotherapy albeit that the toxicity of this substance is of concern. The feasibility of using a non-toxic alternative, AttenuFlex ™, is assessed using Xstrahl and Sensus treatment units. A series of lead and AttenuFlex™ circular cut outs and applicators were used with superficial beams (1.0–8.5 mm Al HVL) to measure percentage depth dose (PDD), output factors (OF) and surface dose correction factors (DCF). X-ray transmi ssion for each material was determined for each beam quality. For these measurements an Advanced Markus chambe...
Source: Australasian Physical and Engineering Sciences in Medicine - January 4, 2021 Category: Biomedical Engineering Source Type: research

Sleep –wake stage detection with single channel ECG and hybrid machine learning model in patients with obstructive sleep apnea
This study aims to develop a new method based on hybrid machine learning with single-channel ECG for sleep –wake detection, which is an alternative to the sleep staging procedure used in hospitals today. For this purpose, the heart rate variability signal was derived using electrocardiography (ECG) signals of 10 OSA patients. Then, QRS components in different frequency bands were obtained from the ECG signal by digital filtering. In this way, nine more signals were obtained in total. 25 features from each of the 9 signals, a total of 225 features have been extracted. Fisher feature selection algorithm and principal c...
Source: Australasian Physical and Engineering Sciences in Medicine - January 4, 2021 Category: Biomedical Engineering Source Type: research

Hybrid-COVID: a novel hybrid 2D/3D CNN based on cross-domain adaptation approach for COVID-19 screening from chest X-ray images
In this study, a transfer learning-based hybrid 2D/3D CNN architecture for COVID-19 screening using CXRs has been developed. The proposed architecture consists of the incorporation of a pre-trained deep model (VGG16) and a shallow 3D CNN, combined with a depth-wise separable convolution layer and a spatial pyramid pooling module (SPP). Specifically, the depth-wise separable convolution helps to preserve the useful features while reducing the computational burden of the model. The SPP module is designed to extract multi-level representations from intermediate ones. Experimental results show that the proposed framework can a...
Source: Australasian Physical and Engineering Sciences in Medicine - December 10, 2020 Category: Biomedical Engineering Source Type: research

StackNet-DenVIS: a multi-layer perceptron stacked ensembling approach for COVID-19 detection using X-ray images
AbstractThe highly contagious nature of Coronavirus disease 2019 (Covid-19) resulted in a global pandemic. Due to the relatively slow and taxing nature of conventional testing for Covid-19, a faster method needs to be in place. The current researches have suggested that visible irregularities found in the chest X-ray of Covid-19 positive patients are indicative of the presence of the disease. Hence, Deep Learning and Image Classification techniques can be employed to learn from these irregularities, and classify accordingly with high accuracy. This research presents an approach to create a classifier model named StackNet-D...
Source: Australasian Physical and Engineering Sciences in Medicine - December 4, 2020 Category: Biomedical Engineering Source Type: research

Automated measurement of hip –knee–ankle angle on the unilateral lower limb X-rays using deep learning
This study retr ospectively selected 398 double lower limbs X-rays during 2018 and 2020 from Jilin University Second Hospital. The images (n = 398) were cropped into unilateral lower limb images (n = 796). The deep neural network was used to segment the head of hip, the knee, and the ankle in the same image, respectively. Then, the mean square error of distance between each internal point of each organ and the organ’s boundary was calculated. The point with the minimum mean square error was set as the central point of the organ. HKA was determined using the coordinates of three organs&rsqu...
Source: Australasian Physical and Engineering Sciences in Medicine - November 30, 2020 Category: Biomedical Engineering Source Type: research

Inadequate object positioning and improvement of automatic exposure control system calculations based on an empirical algorithm
AbstractWhen using automatic exposure control (AEC) systems in computed tomography (CT), miscalculation of tube current occurs when a patient is not aligned with the rotational center of the X-ray tube. A positioning compensation mechanism provides a corrective function when the patient is off-center; however, not all CT systems are equipped with this mechanism. AEC systems can broadly be divided into noise- and empirical-based. The authors studied empirical-based AEC systems to derive a compensation process to achieve an equivalent effect to that offered by the mechanism and to verify the accuracy of this process. A relat...
Source: Australasian Physical and Engineering Sciences in Medicine - November 30, 2020 Category: Biomedical Engineering Source Type: research

Heart rate variability time domain features in automated prediction of diabetes in rat
AbstractDiabetes is a very common occurring disease, diagnosed by hyperglycemia. The established mode of diagnosis is the analysis of blood glucose level with the help of a hand-held glucometer. Nowadays, it is also known for affecting multi-organ functions, particularly the microvasculature of the cardiovascular system. In this work, an alternative diagnostic system based on the heart rate variability (HRV) analysis and artificial neural network (ANN) and support vector machine (SVM) have been proposed. The experiment and data recording has been performed on male Wister rats of 10 –12 week of age and 200&thinsp...
Source: Australasian Physical and Engineering Sciences in Medicine - November 30, 2020 Category: Biomedical Engineering Source Type: research

Noise robust automatic heartbeat classification system using support vector machine and conditional spectral moment
AbstractHeartbeat classification is central to the detection of the arrhythmia. For the effective heartbeat classification, the noise-robust features are very significant. In this work, we have proposed a noise-robust support vector machine (SVM) based heartbeat classifier. The proposed classifier utilizes a novel noise-robust morphological feature which is based on the conditional spectral moment (CSM) of the heartbeat. In addition to the proposed CSM feature, we have also employed the existing RR interval, the wavelets, and the higher-order statistics (HOS) based temporal and morphological feature sets. The noise-robustn...
Source: Australasian Physical and Engineering Sciences in Medicine - November 24, 2020 Category: Biomedical Engineering Source Type: research

Technical evaluation of image quality in synthetic mammograms obtained from 15 ° and 40° digital breast tomosynthesis in a commercial system: a quantitative comparison
AbstractDigital breast tomosynthesis (DBT) has recently gained interest both for breast cancer screening and diagnosis. Its employment has increased also in conjunction with digital mammography (DM), to improve cancer detection and reduce false positive recall rate. Synthetic mammograms (SMs) reconstructed from DBT data have been introduced to replace DM in the DBT  + DM approach, for preserving the benefits of the dual-acquisition modality whilst reducing radiation dose and compression time. Therefore, different DBT models have been commercialized and the effective potential of each system has been investiga...
Source: Australasian Physical and Engineering Sciences in Medicine - November 23, 2020 Category: Biomedical Engineering Source Type: research

Winning images from the Photography in Medical Physics (PiMP) competition
(Source: Australasian Physical and Engineering Sciences in Medicine)
Source: Australasian Physical and Engineering Sciences in Medicine - November 23, 2020 Category: Biomedical Engineering Source Type: research

Verification system for intensity-modulated radiation therapy with scintillator
AbstractIn the preparation of intensity-modulated radiation therapy (IMRT), patient-specific verification is widely employed to optimize the treatment. To accurately estimate the accumulated dose and obtain the field-by-field or segment-by-segment verification, an original IMRT verification tool using scintillator light and an analysis workflow was developed in this study. The raw light distribution was calibrated with respect to the irradiated field size dependency and light diffusion in the water. The calibrated distribution was converted to dose quantity and subsequently compared with the results of the clinically emplo...
Source: Australasian Physical and Engineering Sciences in Medicine - November 18, 2020 Category: Biomedical Engineering Source Type: research

A phantom for testing Cone Beam CTs
AbstractCone Beam Computed Tomography (CBCT) scanners are becoming more common for dental and maxillofacial/head scanning, but performing image quality tests on these systems is difficult. There are quality assurance (QA) phantoms commercially available but they can be expensive, bulky and not optimised for CBCT imaging limits. Smaller phantoms often lack features that are recommended for testing CBCT systems. A custom made phantom can provide more useful test objects in a more convenient size and at a lower cost. The proposed phantom is called the “Karu” Cone Beam CT Phantom and is constructed with a 3D printe...
Source: Australasian Physical and Engineering Sciences in Medicine - November 16, 2020 Category: Biomedical Engineering Source Type: research

Stability analysis on the effects of heart rate variability and premature activation of atrial ECG dynamics using ARMAX model
This study developed an Autoregressive Moving Average with Exogenous Input (ARMAX) model to explore the roles of Heart Rate Variability (HRV) and Premature Activation (PA) in PTaI dynamics using PTaI and PP Interval (PPI) as exogenous inputs. Minute ECG signals were collected from twenty Normal Sinus Rhythm (NSR) and ten Atrial Tachycardia (AT) volunteers. The EDAN PC ECG system was used in the Modified Limb Lead (MLL)  configuration to evaluate instability. The instabilities of PTaI were found at the minimum model orders (Amin) of 10 and 11, in the NSR and AT groups, respectively. In the NSR group, the predominant re...
Source: Australasian Physical and Engineering Sciences in Medicine - November 9, 2020 Category: Biomedical Engineering Source Type: research

Citations are a good way to determine the quality of research
(Source: Australasian Physical and Engineering Sciences in Medicine)
Source: Australasian Physical and Engineering Sciences in Medicine - November 9, 2020 Category: Biomedical Engineering Source Type: research

Pathological discrimination of the phonocardiogram signal using the bispectral technique
AbstractPhonocardiography is a dynamic non-invasive and relatively low-cost technique used to monitor the state of the mechanical activity of the heart. The recordings generated by such a technique is called phonocardiogram (PCG) signals. When shown visually, PCG signals can provide more insights of heart sounds for medical doctors. Thus, several approaches have been proposed to analyse these sounds through PCG recordings. However, due to the complexity and the high nonlinear nature of these recordings, a computer-assisted technique based on higher-order statistics HOS is shown to be, among these techniques, an important t...
Source: Australasian Physical and Engineering Sciences in Medicine - November 9, 2020 Category: Biomedical Engineering Source Type: research

Citations equals research quality? If you agree then don ’t cite this stupid, totally terrible article
(Source: Australasian Physical and Engineering Sciences in Medicine)
Source: Australasian Physical and Engineering Sciences in Medicine - November 9, 2020 Category: Biomedical Engineering Source Type: research

Visualization of blurring process due to analog components in a digital radiography system using a simple method
This study describes the performance of a digital radiography (DR) system in detail and proposes a method for characterizing the blurring process due to the presence of analog components in an imaging system. Our method does not involve any specialized technique, such as a simulation that requires long computing time on a high-performance computer. The method is based on the concept of the modulation transfer function (MTF). The functions that corresponded to the MTF of the analog components of the system when the Fourier transform was performed were examined. Indirect conversion type flat-panel detectors (FPD) in the gene...
Source: Australasian Physical and Engineering Sciences in Medicine - November 5, 2020 Category: Biomedical Engineering Source Type: research

Development of a method for treating lower-eyelid carcinomas using superficial high dose rate brachytherapy
In this study, a method was developed for delivering high dose rate (HDR) brachytherapy treatments to basal cell carcinomas (BCCs) as well as squamous cell carcinomas (SCCs) of the lower eyelid via superficial catheters. Clinically-realistic BCC/SCC treatment areas were marked in the lower-eyelid region on a head phantom and several arrangements of catheters and bolus were trialled for treating those areas. The use of one or two catheters of different types was evaluated, and sources of dosimetric uncertainty (including air gaps) were evaluated and mitigated. Test treatments were planned for delivery with an iridium-192 so...
Source: Australasian Physical and Engineering Sciences in Medicine - October 29, 2020 Category: Biomedical Engineering Source Type: research

Classification of schizophrenia using general linear model and support vector machine via fNIRS
In this study, we designed an optimized data-preprocessing method accompanied with techniques of general linear model feature extraction, independent sample t-test feature selection and support vector machine to identify a set of robust fNIRS pattern features as a biomarker to discriminate schizophrenia patients and healthy people. Experimental results demonstrated that the proposed combination way of data preprocessing, feature extraction, feature selection and support vector machine classification can effectively identify schizophrenia patients and the healthy people with a leave-one-out-cross-validation classification a...
Source: Australasian Physical and Engineering Sciences in Medicine - October 28, 2020 Category: Biomedical Engineering Source Type: research

EEG-based deep learning model for the automatic detection of clinical depression
AbstractClinical depression is a neurological disorder that can be identified by analyzing the Electroencephalography (EEG) signals. However, the major drawback in using EEG to accurately identify depression is the complexity and variation that exist in the EEG of a depressed individual. There are several strategies for automated depression diagnosis, but they all have flaws, which make the diagnostic task inaccurate. In this paper, a deep  model is designed in which an integration of Convolution Neural Network (CNN) and Long Short Term Memory (LSTM) is implemented for the detection of depression. CNN and LSTM are use...
Source: Australasian Physical and Engineering Sciences in Medicine - October 22, 2020 Category: Biomedical Engineering Source Type: research

Assessing the suitability of a two-dimensional array for routine quality assurance checks of flatness and symmetry
This study examines the suitability of a commercially available two-dimensional ionization chamber array —the StarCheck array (PTW, Frieburg, Germany) to measure symmetry and flatness for both photon and electron beams. The study was conducted over a period of 4 years whereby the reliability of the array could be established. The reproducibility, uniformity of chamber response, and comparison of bot h photon and electron profiles acquired with the StarCheck array to that of the water-tank were examined. The most significant result was that across all profiles acquired using the StarCheck array, a defective chamb...
Source: Australasian Physical and Engineering Sciences in Medicine - October 19, 2020 Category: Biomedical Engineering Source Type: research

Time series and fractal analyses of wheezing: a novel approach
AbstractSince the outbreak of the pandemic Coronavirus Disease 2019, the world is in search of novel non-invasive methods for safer and early detection of lung diseases. The pulmonary pathological symptoms reflected through the lung sound opens a possibility of detection through auscultation and of employing spectral, fractal, nonlinear time series and principal component analyses. Thirty-five signals of vesicular and expiratory wheezing breath sound, subjected to spectral analyses shows a clear distinction in terms of time duration, intensity, and the number of frequency components. An investigation of the dynamics of air...
Source: Australasian Physical and Engineering Sciences in Medicine - October 14, 2020 Category: Biomedical Engineering Source Type: research

Evaluation of magnetic resonance angiography as a possible alternative to rotational angiography or computed tomography angiography for assessing cerebrovascular computational fluid dynamics
AbstractThe aim of this study was to conduct a flow experiment using a cerebrovascular phantom and investigate whether magnetic resonance angiography (MRA) could replace three-dimensional rotational angiography (RA) and computed tomography angiography (CTA) to construct vascular models for computational fluid dynamics (CFD). We performed MRA and 3D cine phase-contrast (PC) MR imaging with a silicone cerebrovascular phantom of an internal carotid artery-posterior communicating artery aneurysm with blood-mimicking fluid, and controlled flow with a flowmeter. We also obtained RA and CTA data for the phantom. Four analysts con...
Source: Australasian Physical and Engineering Sciences in Medicine - October 12, 2020 Category: Biomedical Engineering Source Type: research

Virtual digital subtraction angiography using multizone patch-based U-Net
In this study, the NMSE, PSNR, and SSIM indices were 8.58%, 33.86 dB, and 0.829, respectively. These results indicate that the proposed method can visualize blood vessels without mo tion artifacts from a single live image. (Source: Australasian Physical and Engineering Sciences in Medicine)
Source: Australasian Physical and Engineering Sciences in Medicine - October 6, 2020 Category: Biomedical Engineering Source Type: research

Issues associated with deploying CNN transfer learning to detect COVID-19 from chest X-rays
AbstractCovid-19 first occurred in Wuhan, China in December 2019. Subsequently, the virus spread throughout the world and as of June 2020 the total number of confirmed cases are above 4.7 million with over 315,000 deaths. Machine learning algorithms built on radiography images can be used as a decision support mechanism to aid radiologists to speed up the diagnostic process. The aim of this work is to conduct a critical analysis to investigate the applicability of convolutional neural networks (CNNs) for the purpose of COVID-19 detection in chest X-ray images and highlight the issues of using CNN directly on the whole imag...
Source: Australasian Physical and Engineering Sciences in Medicine - October 5, 2020 Category: Biomedical Engineering Source Type: research

Investigating beam matching for multi-room pencil beam scanning proton therapy
In conclusion, proton beam matching was quantified for three beam-matched rooms of an IBA ProteusPLUS system with a PBS dedicated nozzle. It is feasible to match the spot size and absolute dose within ± 5% and ± 2%, respective ly. Proton range can be matched within ± 0.5 mm. (Source: Australasian Physical and Engineering Sciences in Medicine)
Source: Australasian Physical and Engineering Sciences in Medicine - October 5, 2020 Category: Biomedical Engineering Source Type: research

Practical beam steering of X-ray beams on Elekta accelerators: The effect of focal spot alignment on beam (symmetry and position) and radiation isocentre (size and position)
AbstractAcceptance and commissioning of a linear accelerator is the process of preparing it for clinical use. One of the initial important dosimetric tasks for X-ray beam set-up and use is to optimise the trajectory of the electron beam before it hits the target (focal spot). The main purpose of this study is to characterise the effect of the focal spot position (offset) on the photon beam symmetry and centre position, as well as on linac radiation isocentre size and position for an Elekta Synergy ® linac. For this machine, the initial electron beam steering control items2T andBending F were altered to steer the beam i...
Source: Australasian Physical and Engineering Sciences in Medicine - September 29, 2020 Category: Biomedical Engineering Source Type: research

Radiation exposure of interventional cardiologists during coronary angiography: evaluation by phantom measurement and computer simulation
AbstractDuring interventional cardiological procedures, operators are exposed to patients ’ scatter radiation. Therefore, we measured the radiation exposure of the operator’s eyeball, thyroid, and chest wall during angiography. We used the optically stimulated luminescence dosimeter in the anthropomorphic phantom and developed Monte Carlo simulations using the Korean human voxel phan tom. At 15 frames/s, the radiation dose of the operator’s right eyeball (RE), left eyeball (LE), thyroid (T), and chest wall (CW) at the femoral artery puncture position (FAPP) with protective equipment (PE) was 0.015, 0.16, ...
Source: Australasian Physical and Engineering Sciences in Medicine - September 29, 2020 Category: Biomedical Engineering Source Type: research

Automatic glaucoma screening using optic nerve head measurements and random forest classifier on fundus images
AbstractGlaucoma is an optic neuropathy that gradually steals the patient's sight by damaging the optic nerve head (which is responsible for transferring images from the eye to the brain). Causing an estimated 12.3% of global blindness, glaucoma is considered as the first leading cause of irreversible blindness in the world. This paper presents a novel eye fundus image analysis algorithm for the automatic measurement of fundus related glaucoma indicators; Cup to Disc Ratio (CDR), verification of the ISNT rule, Disc Damage Likelihood Scale (DDLS), and the classification of the input fundus into glaucoma or non-glaucoma case...
Source: Australasian Physical and Engineering Sciences in Medicine - September 27, 2020 Category: Biomedical Engineering Source Type: research

In the future all accredited radiotherapy physicists should have a PhD
(Source: Australasian Physical and Engineering Sciences in Medicine)
Source: Australasian Physical and Engineering Sciences in Medicine - September 20, 2020 Category: Biomedical Engineering Source Type: research

Automated detection of diabetic retinopathy in fundus images using fused features
AbstractDiabetic retinopathy (DR) is one of the severe eye conditions due to diabetes complication which can lead to vision loss if left untreated. In this paper, a computationally simple, yet very effective, DR detection method is proposed. First, a segmentation independent two-stage preprocessing based technique is proposed which can effectively extract DR pathognomonic signs; both bright and red lesions, and blood vessels from the eye fundus image. Then, the performance of Local Binary Patterns (LBP), Local Ternary Patterns (LTP), Dense Scale-Invariant Feature Transform (DSIFT) and Histogram of Oriented Gradients (HOG) ...
Source: Australasian Physical and Engineering Sciences in Medicine - September 20, 2020 Category: Biomedical Engineering Source Type: research

Evaluation of exposure dose in fetal computed tomography using organ-effective modulation
AbstractOrgan-effective modulation (OEM) is a computed tomography scanning technique that reduces the exposure dose to organs at risk. Ultrasonography is commonly used for prenatal imaging, but its reliability is reported to be limited. Radiography and computed tomography (CT) are reliable but pose risk of radiation exposure to the pregnant woman and her fetus. Although there are many reports on the exposure dose associated with fetal CT scans, no reports exist on OEM use in fetal CT scans. We measured the basic characteristics of organ-effective modulation (X-ray output modulation angle, maximum X-ray output modulation ra...
Source: Australasian Physical and Engineering Sciences in Medicine - September 13, 2020 Category: Biomedical Engineering Source Type: research

Transfer learning with deep convolutional neural network for automated detection of schizophrenia from EEG signals
AbstractSchizophrenia (SZ) is a severe disorder of the human brain which disturbs behavioral characteristics such as interruption in thinking, memory, perception, speech and other living activities. If the patient suffering from SZ is not diagnosed and treated in the early stages, damage to human behavioral abilities in its later stages could become more severe. Therefore, early discovery of SZ may help to cure or limit the effects. Electroencephalogram (EEG) is prominently used to study brain diseases such as SZ due to having high temporal resolution information, and being a noninvasive and inexpensive method. This paper ...
Source: Australasian Physical and Engineering Sciences in Medicine - September 13, 2020 Category: Biomedical Engineering Source Type: research

Multi-class diagnosis of Alzheimer ’s disease using cascaded three dimensional-convolutional neural network
AbstractDementia is a social problem in the aging society of advanced countries. Presently, 46.8 million people affected with dementia worldwide, and it may increase to 130 million by 2050. Alzheimer ’s disease (AD) is the most common form of dementia. The cost of care for AD patients in 2015 was 818 billion US dollars and is expected to increase intensely due to the increasing number of patients due to the aging society. It isn’t easy to cure AD, but early detection is crucial. This paper p roposes a multi-class classification of AD, mild cognitive impairment (MCI), and normal control (NC) subjects using three...
Source: Australasian Physical and Engineering Sciences in Medicine - September 13, 2020 Category: Biomedical Engineering Source Type: research

A comparative study of photoplethysmogram and piezoelectric plethysmogram signals
AbstractThe Photoplethysmogram (PPG) signal is one of the most important vital signals in biomedical applications. The non-invasive property and the convenience in the acquisition of both PPG and Piezoelectric Plethysmogram (PZPG) signals are considered as powerful and accurate tools for biomedical diagnosing applications, such as oxygen saturation in blood, blood flow, and blood pressure measurements. In this paper, a number of features for PPG and PZPG signals (ex. first derivative, second derivative, area under the curve and the ratio of systolic area to the diastolic area) are acquired and compared. The results show th...
Source: Australasian Physical and Engineering Sciences in Medicine - August 30, 2020 Category: Biomedical Engineering Source Type: research

3D printed PLA/copper bowtie antenna for biomedical imaging applications
This study aims to increase the performance of the microwave antenna by using 3D printed conductive substrates, which is mainly used in biomedical imaging applications. Conventional antennas such as Horn and Vivaldi have coarse dimensions to integrate into the microwave imaging systems. Therefore, 3D printed Bowtie antenna structures were developed, which yield low cost and smaller sizes. PLA, PLA/copper, and PLA/carbon substrates were produced with a 3D printer. These materials were tested in terms of their dielectric constants between 1 and 10  GHz. The conductive part of the antenna was copper, with a thickness o...
Source: Australasian Physical and Engineering Sciences in Medicine - August 30, 2020 Category: Biomedical Engineering Source Type: research

Decoupling of bowtie and object effects for beam hardening and scatter artefact reduction in iterative cone-beam CT
AbstractCone-beam computed tomography (CBCT) is an important imaging modality for image-guided radiotherapy and adaptive radiotherapy. Feldkamp –Davis–Kress (FDK) method is widely adopted in clinical CBCT reconstructions due to its fast and robust application. While iterative algorithms have been shown to outperform FDK techniques in reducing noise and imaging dose, they are unable to correct projection-domain artefacts such as beam har dening and scatter. Empirical correction techniques require a holistic approach as beam hardening and scatter coexist in the measurement data. This multi-part proof of concept s...
Source: Australasian Physical and Engineering Sciences in Medicine - August 18, 2020 Category: Biomedical Engineering Source Type: research

Acoustic and ultrasonographic characterization of polychloroprene, beeswax, and carbomer-gel to mimic soft-tissue for diagnostic ultrasound
AbstractMaterials with acoustic properties similar to soft-tissue are essential as tissue-mimicking materials (TMMs) for diagnostic ultrasound (US). The velocity (cus), acoustic impedance (AI) and attenuation coefficient of US ( µ) in a material collectively define its acoustic property. In this work, the acoustic properties of polychloroprene rubber, beeswax, and Carbomer-gel are determined. The pulse-echo technique is used to estimatecus and µ. The product of a sample density (ρ) andcus gives its AI. Using a reference based on theInternational Commission on Radiation Units and Measurements Report-61,Tissu...
Source: Australasian Physical and Engineering Sciences in Medicine - August 17, 2020 Category: Biomedical Engineering Source Type: research

The future of radiotherapy is molecular
(Source: Australasian Physical and Engineering Sciences in Medicine)
Source: Australasian Physical and Engineering Sciences in Medicine - August 16, 2020 Category: Biomedical Engineering Source Type: research

Winning images from the Photography in Medical Physics (PiMP) competition
(Source: Australasian Physical and Engineering Sciences in Medicine)
Source: Australasian Physical and Engineering Sciences in Medicine - August 12, 2020 Category: Biomedical Engineering Source Type: research

Feasibility of using tungsten functional paper as a thin bolus for electron beam radiotherapy
AbstractContaining 80% tungsten by weight, tungsten functional paper (TFP) is a radiation-shielding material that is lightweight, flexible, disposable, and easy to cut. Through experimental measurements and Monte Carlo simulations, we investigated the feasibility of using TFP as a  bolus in electron beam radiotherapy. Commercial boluses of thickness 5 and 10 mm and from one to nine layers of TFPs (0.3–2.7 mm) were positioned on the surface of water-equivalent phantoms. The percentage depth dose curves and transverse dose profiles were measured using a 9-MeV electron beam from a clinical linear accelera...
Source: Australasian Physical and Engineering Sciences in Medicine - August 11, 2020 Category: Biomedical Engineering Source Type: research

Book Review: Hendee ’s Physics of Medical Imaging, Fifth edition edited by Ehsan Samei and Donald J. Peck
(Source: Australasian Physical and Engineering Sciences in Medicine)
Source: Australasian Physical and Engineering Sciences in Medicine - August 11, 2020 Category: Biomedical Engineering Source Type: research

Book Review: Hands-on Machine Learning with Scikit-Learn, Keras, and Tensorflow , 2nd edition by Aur élien Géron
(Source: Australasian Physical and Engineering Sciences in Medicine)
Source: Australasian Physical and Engineering Sciences in Medicine - August 11, 2020 Category: Biomedical Engineering Source Type: research

Clinical implementation of a Monte Carlo based independent TPS dose checking system
AbstractThe increase in complexity of treatment plans over time through modalities such as intensity modulated radiotherapy (IMRT) and volumetric modulated arc therapy (VMAT) has often not been met with an increase in capability of the secondary dose calculation checking systems typically used to verify the treatment planning system. Monte Carlo (MC) codes such as EGSnrc have become easily available and are capable of performing calculations of highly complex radiotherapy treatments. This educational note demonstrates a method for implementing and using a fully automated system for performing and analysing full MC calculat...
Source: Australasian Physical and Engineering Sciences in Medicine - August 10, 2020 Category: Biomedical Engineering Source Type: research