Paper Title, Authors, Abstract (Issue 1, Volume 6, 2012)

Pages

Radon Transform Based Local Tomography Algorithm for 3D Reconstruction
Kishore Rajendran, Karthikeyan B. R.

Abstract: An algorithm from Radon transform to obtain local tomography from multiple CT slices for localized 3D reconstruction is developed. The proposed method uses Radon transform to obtain projections for a region of interest. Reconstructing a particular cross section of a human body using local data will significantly reduce X-ray exposure during imaging. Image reconstruction is performed using filtered back projection technique. The property that distinguishes the developed algorithm from previous algorithms is the ability to track the Region of Interest (ROI) for every projection angle, computing projections along the lines intersecting the region of interest, and performing reconstruction using purely local data. Parallel beam projections are used and ROI is defined by a square or circular region. To reconstruct a local region of 20 pixel radius in a 256 x 256 image, 13% of the global data is required.
 

Mathematic Method to Calculate the Central Incisor Form Using Face Records and Vice Versa
Laith Mahmoud Abdulhadi, Hana Abbas Mohammed

Abstract: Selection of anterior teeth depends mainly on Leon William theory that hypothesizes the presence of harmony between the face and inverted central incisor forms. If this theory is approved mathematically then the central incisor form and width could be predicted and calculated with acceptable precision in clinical practice. The purpose of this study was to predict the tooth form and mesiodistal width from the facial measurements. 145 young volunteers from different ethnic groups (Malays, Chinese, and Middle easterners) were selected according to well-defined criteria. Frontal standardized digital photos were taken for each person face and left central incisor. Then, the face and central incisor image length and widths (at different levels) were measured using digital image analyzer. The results revealed the presence of high metric dependence between the face and the left central incisor widths. A linear regression analysis was used to formulate a general equation to predict the central incisor width and form outline from the face measurement successfully. On the other hand, the face form can be predicted from the central incisor records
 

Wavelet Transform Based Arterial Blood Pressure Waveform Delineator
Awadhesh Pachauri, Manabendra Bhuyan

Abstract: The proposed algorithm describes a novel wavelet transform based technique for extracting the features of arterial blood pressure (ABP) waveform. ABP waveform is rich in pathological information such as heart rate, systolic, mean and diastolic pressure thereby achieved an important aspect in cardiology. The multi-scale feature of wavelet transform enables systolic peaks to be detected from noise, base line drift, artifacts, irregular pressure waveform and arrhythmias. The first step in extracting ABP features starts from accurate detection of systolic peaks from ABP waveform. The algorithm is developed on the signals from MGH/MF waveform database, fantasia database, MIT-BIH Polysmographic database and CSL database. The wavelets used for waveform delineation are symmetric (sym4) and Daubechies (db4). The technique involves decomposition of ABP signal up to nine levels by selected wavelet. The algorithm does not require any preprocessing before implementing the detection process. Relevant detail coefficient is selected based on energy, frequency and cross-correlation analysis of detail coefficients at each scale. Finally, selected detail coefficients undergo window based amplitude and interval thresholding for valid maxima detection termed as systolic peaks. Further, average coefficient obtained at first level is utilized for extracting other features such as onsets, dicrotic notches and dicrotic peaks taking systolic peaks positions as reference.
 

Automatic Generation of Region of Interest for Kidney Ultrasound Images Using Texture Analysis
Wan M. Hafizah, Eko Supriyanto

Abstract: Kidney ultrasound imaging can be used to estimate kidney size and position, and help to diagnose structural abnormalities as well as the presence of cysts and stones. However, due to the presence of speckle noise in ultrasound images, performing the segmentation methods for the kidney images were very challenging and therefore, deleting and removing the complicated background will speeds up and increases the accuracy of the segmentation process. However, in previous studies, the ROI of the kidney is manually cropped. Therefore, this study proposed an automatic region of interest (ROI) generation for kidney ultrasound images. Firstly, some techniques of speckle noise reduction were implemented consist of median filter, Wiener filter and Gaussian low-pass filter. Then texture analysis was performed by calculating the local entropy of the image, continued with the threshold selection, morphological operations, object windowing, determination of seed point and last but not least the ROI generation. This method was performed to several kidney ultrasound images with different speckle noise reduction techniques and different threshold value selection. Based on the result, it shows that for median filter, threshold value of 0.6 gave the highest TRUE ROIs which were 70%. For Wiener filter, threshold value of 0.8 gave highest TRUE ROIs which were 80% and for Gaussian low-pass filter, threshold value of 0.7 gave highest TRUE ROIs which were 100%. By using the previous result, this method has been tested also to more than 200 kidney ultrasound images. As the result, for longitudinal kidney images, out of 120 images, 109 images generate true ROI (91%) and another 11 images generate false ROI (9%). For transverse kidney images, out of 100 images, 89 images generate true ROI (89%) and 11 images generate false ROI (11%). To conclude, the method in this study can be practically used for automatic generation of US kidney ROI.
 

Arterial Pulsations in the Blood Pressure Cuff: Are They Hemodynamic Pulses or Oscillations?
J. Jilek, M. Stork

Abstract: Automatic monitors for the determination of blood pressure frequently use the oscillometric method. Amplitudes of arterial pulsations evoked in the cuff are evaluated by software algorithms in order to determine the systolic and the diastolic pressures. The arterial pulses in the cuff are commonly called oscillations. Almost no attention has been paid to the contours of these pulses. Our objective was to demonstrate visually and numerically that the contours of pulses in the cuff are hemodynamic arterial waveforms rather than oscillations. We designed and constructed an experimental notebook-based system for wrist cuff and finger photoplethysmograph data acquisition and processing. The contours of wrist cuff pulses acquired at the point of diastolic pressure were compared to radial artery pulses acquired by other methods. Visual and numeric comparison revealed that wrist cuff waveforms are closely related to other hemodynamic waveforms acquired invasively and non-invasively. Comparison with age related waveforms acquired by applanation tonometry revealed similar prolongation of upstroke time with age. Values of left ventricular ejection time computed from wrist cuff waveforms obtained from 12 volunteers were close to normal values (0.6%). Our conclusion was that the wrist cuff waveforms are not oscillations and that they belong in the family of hemodynamic waveforms. We proposed new, more accurate terms “cuff-pulse method” in place of “oscillometric method” and “cuff pulses” in place of “oscillations”.
 

PROPER: a Pilot Study of the Role of Riboflavin Supplementation for the Prevention of Preeclampsia
Molina L., Rivas V., Sanchez R., Rivas-Echeverria C., Sahland K., Bogucki P., Pahl L., Wallinger R., Volz J., Wacker J., Fruehauf J. H., Elsen C.

Abstract: Preeclampsia remains a mayor obstetrical threat worldwide, but recently it has been shown that it could be a predictable and preventable disease. We have published that riboflavin (Vitamin B2) deficiency seems to be a possible risk factor for preeclampsia in developing countries. Here, we present some results of a pilot study, conducted in Venezuela, examining the usage of high dose riboflavin supplementation for the prevention of preeclampsia.
414 women were enrolled since around 20 weeks of gestation and were treated with 15 mg/d riboflavin supplementation or placebo until delivery. After a loss to follow up of 38.4%, due to political and social problems in Venezuela during the enrolment and follow up time frame of the study, results from 255 women were available for evaluation. Although no statistical difference was achieved related to the development of preeclampsia between groups, high dose riboflavin supplementation led to an approximate 75 percent (p < 0.05, RR 4.17 [95% CI 0.87-20,02]) decrease in the number of cases of severe preeclampsia. Women in the riboflavin group who developed any hypertensive disorder of pregnancy had statistically significant lower maximum diastolic blood pressures than corresponding women in the placebo group (diastolic BP 93,27 mmHg vs. 100,19 mmHg, p = 0,05). Unfortunately, The study suffered from a significant lost in follow-up, and did not have sufficient statistical power to detect a difference between groups; however, we consider the results encouraging in supporting further studies into the use of riboflavin, or other vitamins or antioxidants, to prevent preeclampsia.
 

AD Early Detection: Carotid Artery Reactivity Comparison between Healthy Young and Aged People
Mohd A. Jamlos, Eko Supriyanto

Abstract: Early detection of Alzheimer Disease (AD) is very important in order to have high chance to be cured from this disease. It could be done through assessing the carotid artery condition since the impairment of this artery leads to the central process of Alzheimer. Ability of the artery to dilate shows it is in a good shape. This kind of dilation is called carotid artery reactivity (CAR) where the more the artery able to dilate, the better the condition of the artery. The artery dilation could be measured using its blood flow velocity as the parameter. High blood flow velocity is the sign of wide dilation of the carotid artery. Healthy people and Alzheimer patient is believed to have different carotid artery reactivity value. At the same time, different age of healthy people also have different value. Hence, this study emphasize on finding the normal reactivity value belong to the group of young and aged healthy people. This normal value could be used to differentiate between healthy people and Alzheimer patient. All 40 subjects whose are less than 30 years old for young subjects and people aged more than 50 years old for aged people have been scanned with ultrasound machine using Doppler technique before and after having exercise to achieve 85% of their Maximal Heart Rate (MHR). Readings of carotid artery blood flow velocity before exercise (rest) and after exercise (stimulated) are taken to be compared to obtain its percentage increment value (reactivity). Based on the result, the young normal carotid artery reactivity value is 143.6% for male and 103.3% for female meanwhile for aged normal carotid artery reactivity value is 105% for male and 74% for female.
 

Development of Breast Cancer Diagnosis Tool Using Hybrid Magnetoacoustic Method and Artificial Neural Network
Maheza I. M. Salim, Abdul H. Ahmad, Ismail Ariffin, Bustanur Rosidi, Eko Supriyanto

Abstract: Breast cancer is a metabolic disease that causes the breast cells to acquire genetic alteration and allows them to grow beyond the normal tissue limit. With the yearly increasing trend in new cases and mortality rate, new approach in diagnosis and treatment of breast cancer is crucial to improve the existing management of breast cancer cases. This paper presents a new approach in breast cancer diagnosis by using Hybrid Magnetoacoustic Method (HMM) and artificial neural network. HMM is a newly developed one dimensional imaging system that combines the theory of acoustic and magnetism for breast imaging. It is capable to produce 2 outputs, the attenuation scale of ultrasound and the magnetoacoustic voltage. In this study, an artificial neural network is developed to automate the output of HMM for breast cancer classification. The ANN employs the steepest gradient descent with momentum back propagation algorithm with logsig and purelin transfer function. The best ANN architecture of 3-2-1 (3 network inputs, 2 neurons in the hidden layer, one network output) with learning rate of 0.3, iteration rate of 20000 and momentum constant of 0.3 was successfully developed with accuracy of 90.94% to testing data and 90% to validation data. The result shows the advantages of HMM outputs in providing a combination of bioelectric and acoustic information of tissue for a better breast cancer diagnosis consideration. The system’s high percentage of accuracy shows that the output of HMM is very useful in assisting diagnosis. This additional capability is hoped to improve the existing breast oncology diagnosis.
 

Computerized Decision Support in Liver Steatosis Investigation
Simona Moldovanu, Luminita Moraru, Dorin Bibicu

Abstract: Fractal analyses, Euler number and RF5 texture parameter have been successfully applied in the analysis of many types of ultrasound images. All features have been extracted from binary images. We focused our study on liver ultrasonic (US) images. The US experimental images were divided in two groups: healthy liver US images and steatosis US liver images. The goals of this study are both to develop an automatic system in order to investigate the correlation between certain features and the optimum threshold and to take into account an automatic decision support of the studied pathologies using the correlation results. The tool for this analysis is an Automatic Correlation System (ACS) that allows us to investigate the correlation between the optimum threshold (OT), fractal dimension (FD), Euler number (EN) and RF5 parameter. Finally, based on correlation results, the ACS software tool is extended in a Computer Automatic Diagnosis System (CADi), in order to provide a reliable discriminator tool of the liver steatosis as support for medical diagnosis. The features have been extracted from different regions of interest (ROIs) cropped in both classes of liver original images (healthy and fatty). In order to obtain OT, each selected ROI was transformed from a gray level image into a binary image using the Otsu method. The ACS proposed system uses the Box Counting Method (BCM), the Euler algorithm based on concavity and convexity and the algorithm which allows the obtaining of the iso-segments matrix. The Pearson coefficient is used to correlate the calculated FD, EN and RF5 data for each characteristic OT for both liver classes. The CADi software was developed using the artificial neural networks. Finally we investigated the CADi efficiency.
 

Improvement of Glucose Biosensor Performances Using Poly(hydroxyethyl methacrylate) Outer Membrane
Norhana Jusoh, Azila Abdul-Aziz, Eko Supriyanto

Abstract: A glucose biosensor was developed based on immobilization of glucose oxidase and poly(allylamine) ferrocene by layer-by-layer covalent attachment. Factors that can affect current response, response time, enzyme kinetics and membranes stability membrane were discussed. The apparent Michaelis-Menten constant, Kmapp obtained were quite low but was increased up to 28.68mM due to effect of nafion layer to the multilayer membrane. To further improve the glucose biosensor performances, a cross-linked poly(hydroxyethyl methacrylate) (pHEMA) membrane was attached to the multilayered-nafion membrane to extend the linearity of sensor response and also to protect the biosensor. Multilayered-nafion membrane with cross-linked pHEMA demonstrated acceptable Kmapp, which was around 40.58mM with high sensitivity and fast response time towards the glucose.
 

Automatic Classification of Muscle Condition based on Ultrasound Image Morphological Differences
Wan M. Hafizah, Joanne Z. E. Soh, Eko Supriyanto, Syed M. Nooh

Abstract: Myofascial Pain Syndrome is a form of chronic muscle pain centered on sensitive points in muscles called trigger points. These points are painful when pressure is applied on them and can produce referred pain, referred tenderness, motor dysfunction and autonomic phenomena. Currently, the location of trigger point is mostly determined through physical examination by clinicians, which is considered unreliable due to the dependency on the clinician’s discretion. This study had developed a system that quantifies the location of trigger point using ultrasound images to detect the presence of trigger point. Normal muscle and muscle with trigger point shown morphological difference in ultrasound images, in which, is accentuated through image processing and pattern recognition. Statistical properties of the final signal output were analyzed to determine the most optimum value used for classification. Two parameters were calculated which are the mean and the standard deviation. Upon observation, the value of standard deviation can be used in setting the threshold value for the classifier to differentiate between normal muscle and muscle with trigger point. Based on the results, classifier can be set between 9 to 12 for DUS 100 and 13 to 19 for Aplio MX in order to successfully classify the images. System performance testing shows that this system has high accuracy when detection was performed with the current collection of sample images.
 

Region Growing Method in Separation of Orthodontic Bodies Using Illuminated Models
Mohammadreza Yadollahi, Ales Prochazka, Martina Mudrova, Magdalena Kasparova, Tatjana Dostalova

Abstract: The paper presents a new method for detection of orthodontic bodies, their separation, enhancement and analysis using their plaster casts models illuminated by different light sources. The proposed method is based upon the processing of the set of two-dimensional images acquired in different illumination conditions using digital de-nosing and gradient image enhancement methods in the preliminary stage. The region growing method forms the main part of the paper with its results compared to the distance and watershed transforms. Mathematical methods studied include (i) selected computational tools for multi-dimensional analysis in the orthodontic treatment and (ii) segmentation methods based upon illuminated objects allowing the application of the region growing method for image regions classification. The proposed set of algorithms is then used for orthodontic bodies segmentation and for comparison of results achieved. All methods are applied in orthodontics for segmentation of specified objects to allow the efficient treatment and to simplify the organization of further analysis of treatment results in the electronic form accessible for all specialists in the given area.
 

Designing Medical Checkup Information System for the Navy Hospitals
Bens Pardamean, Shirley Louis, Leli Setyaningrum

Abstract: This research investigated the implementation of medical checkup conducted within the military health departments and Navy hospitals in the western region of Indonesia. Medical checkups conducted within the health departments and Navy hospitals still uses manual processes, resulting in various errors, such as assessment inaccuracies, difficulty in data search, and so on. Therefore, this study aimed to provide information system solutions in the form of a computerized medical checkup system design and integration, as well as health monitoring functions of personnel. The design of these systems produced a computerized medical checkup process and utilized an integrated database; the latter is network-supported by Internet, both in the health departments and Navy hospitals.
 

The Geometric Isomers of Caespitate: A Computational Study in Vacuo and in Solution
Liliana Mammino, Mwadham M. Kabanda

Abstract: Caespitate is an acylphloroglucinol isolated from a plant utilized in traditional medicine in South Africa and exhibiting antituberculosis, antibacterial and antifungal activities. The molecule is characterized by a COCH(CH3)2 acyl chain and by a prenyl chain ending with an acetic-acid ester group, in meta to the acyl chain. The double bond of the prenyl chain gives origin to Z and E isomers, with the former being the biologically active one. An extensive computational study of the conformational preferences of the two isomers was carried out in four media (vacuum, chloroform, acetonitrile and water) to try and identify significant differences. The main difference concerns the ability of the prenyl/ester chain to form an intramolecular hydrogen bond with one of the neighbouring OH: the ability is greater for the Z isomer and the corresponding hydrogen bond has greater conformation-stabilizing effect. The difference is also analysed in terms of the competition between intramolecular hydrogen bond engaging the O atoms of the ester function and the OΔ{HΕςΕςΕςΔω interaction between phenol OH and the double bond in the prenyl/ester chain.