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Fulltext Classification of Non-Severe Traumatic Brain Injury from Resting-State EEG Signal Using LSTM Network with ECOC-SVM

Lai CQ, Ibrahim H, Abd Hamid AI, Abdullah JM

Sensors (Basel), 2020 Sep 14;20(18).
PMID: 32937801 DOI: 10.3390/s20185234

Traumatic brain injury (TBI) is one of the common injuries when the human head receives an impact due to an accident or fall and is one of the most frequently submitted insurance claims. However, it is often always misused when individuals attempt an insurance fraud claim by providing false medical conditions. Therefore, there is a need for an instant brain condition classification system. This study presents a novel classification architecture that can classify non-severe TBI patients and healthy subjects employing resting-state electroencephalogram (EEG) as the input, solving the immobility issue of the computed tomography (CT) scan and magnetic resonance imaging (MRI). The proposed architecture makes use of long short term memory (LSTM) and error-correcting output coding support vector machine (ECOC-SVM) to perform multiclass classification. The pre-processed EEG time series are supplied to the network by each time step, where important information from the previous time step will be remembered by the LSTM cell. Activations from the LSTM cell is used to train an ECOC-SVM. The temporal advantages of the EEG were amplified and able to achieve a classification accuracy of 100%. The proposed method was compared to existing works in the literature, and it is shown that the proposed method is superior in terms of classification accuracy, sensitivity, specificity, and precision.

Matched MeSH terms: Tomography, X-Ray Computed
Fulltext Using 21st-Century Technologies to Determine the Cognitive Capabilities of a 11,000-Year-Old Perak Man Who Had Brachymesophalangia Type A2

Abdullah JY, Saidin M, Rajion ZA, Hadi H, Mohamad N, Moraes C, et al.

Malays J Med Sci, 2021 Feb;28(1):1-8.
PMID: 33679214 DOI: 10.21315/mjms2021.28.1.1

Perak Man, named after the state where the skeleton was found, was the most complete skeleton found in Southeast Asia. The funerary artefacts indicate that Perak Man was highly respected, as he was buried at the centre of the highest cave in Lenggong, and he was the only person buried there. A copy of the original skull was made using computed tomography (CT) and 3D printing. Based on the internal structure of the reconstructed skull, the estimated intracranial volume (ICV) is 1,204.91 mL. The hypothetical face of Perak Man was reconstructed according to established forensic methods. Based on his presumed status, Perak Man was likely a respected person in the group and, perhaps, a shaman and the most knowledgeable person in the group regarding survival, hunting, gathering and other aspects of Palaeolithic daily life.

Matched MeSH terms: Tomography, X-Ray Computed
Pseudoaneurysm of the renal artery associated with melioidosis

Noordin K, Abdullah MM, Natarajan C, Wahab YA, Abdullah K

Br J Urol, 1995 May;75(5):680-1.
PMID: 7613814
Matched MeSH terms: Tomography, X-Ray Computed
Computed tomographic measurement of cervical pedicles for transpedicular fixation in a Malay population

Yusof MI, Ming LK, Abdullah MS

J Orthop Surg (Hong Kong), 2007 Aug;15(2):187-90.
PMID: 17709859

To measure the cervical pedicles and assess the feasibility of transpedicular fixation in a Malay population.

Matched MeSH terms: Tomography, X-Ray Computed/methods*
Fulltext Computed Tomographic Morphometric Analysis of C1 and C2 for Lamina Cross Screw Placement in Malay Ethnicity

Chan AKH, Yusof MI, Abdullah MS

Asian Spine J, 2021 Feb;15(1):1-8.
PMID: 32252193 DOI: 10.31616/asj.2019.0242

STUDY DESIGN: This is an observational study of computed tomography (CT) data.
PURPOSE: The C1 and C2 laminas in the Malaysian Malay population were analyzed for the feasibility of fitting 3.5-mm laminar screws in a cross configuration.
OVERVIEW OF LITERATURE: Morphometric analysis of the C1 and C2 laminas has been performed for various populations but not for the Malaysian Malay population.
METHODS: A total of 330 CT cervical images were measured to establish the bicortical diameter of the C1 and C2 laminas as well as their height and length. The C1 posterior tubercle bicortical diameter and height were also determined from these images. All parameters were measured up to 0.1 mm, and statistical analysis was performed using IBM SPSS Statistics ver. 24.0 (IBM Corp., Armonk, NY, USA). An independent t -test and the Pearson chi-square test were used to determine the mean difference and screw acceptance.
RESULTS: The means of the C1 lamina measurements were 5.79±1.19 mm in diameter, 9.76±1.51 mm in height, and 20.70±1.86 mm in length. The means of the measurements of the posterior tubercle were 7.20±1.88 mm in diameter and 10.51±1.68 mm in height. The means of the C2 lamina measurements were 5.74±1.31 mm in diameter, 11.76±1.69 mm in height, and 24.96±2.56 mm in length. Overall 65.5% of C1 and 80.3% of C2 laminas are able to accept 3.5-mm screws in a cross configuration. Screw acceptability is similar between the right and left sides (p >0.05). However, males have a higher screw acceptability compared with females (p <0.05), except for the C2 left lamina.
CONCLUSIONS: It is feasible to insert a 3.5-mm screw in a cross configuration in the C1 and C2 laminas of the Malaysian Malay population, especially in males. However, a CT scan should be performed prior to the operation to determine screw acceptability and to estimate screw sizes.

Matched MeSH terms: Tomography, X-Ray Computed
A rare case of unilateral postaxial duplicated foot in a developmentally normal child

Sahdi H, Hoong CW, Rasit AH, Arianto F, Siong LK, Abdullah NA

J Orthop Surg (Hong Kong), 2017 01;25(1):2309499016684989.
PMID: 28166702 DOI: 10.1177/2309499016684989

Diplopodia, being a rare congenital disorder, is infrequently discussed in published texts. Most reported cases have accounted the involvement of duplicated preaxial digits with other associated organ system and physical deformities. Here, we present an unusual case of isolated diplopodia involving postaxial toes in a child with no other organ and physical abnormalities. Radiological studies revealed a set of 10-digit-duplicated foot over the lateral aspect of the native foot, complete with phalanges and its corresponding metatarsals as well as tarsals, supplied by an anomalous posterior branch of the popliteal artery. Definitive surgery was performed just before the child was learning to walk.

Matched MeSH terms: Tomography, X-Ray Computed/methods*
Two surgical methods used in 90 patients with intracranial subdural empyema

Mat Nayan SA, Mohd Haspani MS, Abd Latiff AZ, Abdullah JM, Abdullah S

J Clin Neurosci, 2009 Dec;16(12):1567-71.
PMID: 19793660 DOI: 10.1016/j.jocn.2009.01.036

We studied the efficacy of two surgical methods used for the treatment of intracranial subdural empyema (ISDE) at our centre. A cross-sectional study (1999-2005) of 90 patients with non-traumatic supratentorial ISDE revealed that the two surgical methods used for empyema removal were burr hole/s and drainage (50 patients, 55.6%) and a cranial bone opening procedure (CBOP) (40 patients, 44.4%). Patients in the CBOP group had a better result in terms of clinical improvement (chi-squared analysis, p=0.006) and clearance of empyema on brain CT scan (chi-squared analysis, p<0.001). Reoperation was more frequent among patients who had undergone burr hole surgery (multiple logistic regression, p<0.001). The outcome and morbidity of ISDE survivors were not related to the surgical method used (p>0.05). The only factor that significantly affected the morbidity of ISDE was level of consciousness at the time of surgery (multiple logistic regression, p<0.001). We conclude that CBOP and evacuation of the empyema is a better surgical method for ISDE than burr hole/s and drainage. Wide cranial opening and empyema evacuation improves neurological status, gives better clearance of the empyema and reduces the need for reoperation. Level of consciousness at the time of presentation is a predictor of the morbidity of ISDE. Thus, aggressive surgical treatment should occur as early as possible, before the patient deteriorates.

Matched MeSH terms: Tomography, X-Ray Computed
Intracerebral haematomas after deep brain stimulation surgery in a patient with Tourette syndrome and low factor XIIIA activity

Idris Z, Ghani AR, Mar W, Bhaskar S, Wan Hassan WN, Tharakan J, et al.

J Clin Neurosci, 2010 Oct;17(10):1343-4.
PMID: 20620064 DOI: 10.1016/j.jocn.2010.01.054

A 24-year-old male patient with refractory Tourette syndrome was treated with deep brain stimulation (DBS) and developed subsequent bilateral subcortical haematomas. Additional blood tests revealed abnormalities of plasma factor XIIIA and tryptophan levels, which may be associated with Tourette syndrome. Neurosurgeons who perform DBS surgery on patients with Tourette syndrome must be aware of possible disastrous complications resulting from factor XIIIA disorders of blood haemostasis. Routine screening for this condition is not typically performed prior to surgery in these patients.

Matched MeSH terms: Tomography, X-Ray Computed/methods
Fulltext Atypical Presentation of Takotsubo Cardiomyopathy: Stroke as a Predisposing Factor

Loong CW, Firdaus MAM, Said MRM, Abidin IZ

Medeni Med J, 2020;35(3):266-270.
PMID: 33110680 DOI: 10.5222/MMJ.2020.47374

Takotsubo syndrome is a rare disease and remained ambiguous with its etiology. The disease manifests in various clinical characteristics and even mimicking acute coronary syndrome. We are reporting a case of an elderly lady who manifested by unsteady gaits and recurrent falls. Subacute infarct of the right corona radiata was observed on the brain CT. In addition, coronary angiography and ventriculogram were performed because of dynamic ECG changes and elevated troponin I levels. The angiogram was normal while ventriculogram showed apical ballooning. She was diagnosed and treated as Takotsubo syndrome.

Matched MeSH terms: Tomography, X-Ray Computed
Multimodal 3-D reconstruction of human anatomical structures using SurLens Visualization System

Adeshina AM, Hashim R, Khalid NE, Abidin SZ

Interdiscip Sci, 2013 Mar;5(1):23-36.
PMID: 23605637 DOI: 10.1007/s12539-013-0155-z

In the medical diagnosis and treatment planning, radiologists and surgeons rely heavily on the slices produced by medical imaging devices. Unfortunately, these image scanners could only present the 3-D human anatomical structure in 2-D. Traditionally, this requires medical professional concerned to study and analyze the 2-D images based on their expert experience. This is tedious, time consuming and prone to error; expecially when certain features are occluding the desired region of interest. Reconstruction procedures was earlier proposed to handle such situation. However, 3-D reconstruction system requires high performance computation and longer processing time. Integrating efficient reconstruction system into clinical procedures involves high resulting cost. Previously, brain's blood vessels reconstruction with MRA was achieved using SurLens Visualization System. However, adapting such system to other image modalities, applicable to the entire human anatomical structures, would be a meaningful contribution towards achieving a resourceful system for medical diagnosis and disease therapy. This paper attempts to adapt SurLens to possible visualisation of abnormalities in human anatomical structures using CT and MR images. The study was evaluated with brain MR images from the department of Surgery, University of North Carolina, United States and CT abdominal pelvic, from the Swedish National Infrastructure for Computing. The MR images contain around 109 datasets each of T1-FLASH, T2-Weighted, DTI and T1-MPRAGE. Significantly, visualization of human anatomical structure was achieved without prior segmentation. SurLens was adapted to visualize and display abnormalities, such as an indication of walderstrom's macroglobulinemia, stroke and penetrating brain injury in the human brain using Magentic Resonance (MR) images. Moreover, possible abnormalities in abdominal pelvic was also visualized using Computed Tomography (CT) slices. The study shows SurLens' functionality as a 3-D Multimodal Visualization System.

Matched MeSH terms: Tomography, X-Ray Computed/methods*
Proptosis--Correlation and Agreement between Hertel Exophthalmometry and Computed Tomography

Ramli N, Kala S, Samsudin A, Rahmat K, Abidin ZZ

Orbit, 2015;34(5):257-62.
PMID: 26186249 DOI: 10.3109/01676830.2015.1057291

To determine the correlation and agreement between Hertel exophthalmometry and computed tomography (CT) of the orbits in measuring proptosis.

Matched MeSH terms: Tomography, X-Ray Computed/methods*
Fulltext Psychiatric aspects of the acquired immunodeficiency syndrome. A case report

Maniam T, Abu Bakar AK

Med J Malaysia, 1988 Jun;43(2):166-9.
PMID: 3237133
Matched MeSH terms: Tomography, X-Ray Computed
Fulltext Kidney Tumor Detection and Classification Based on Deep Learning Approaches: A New Dataset in CT Scans

Alzu'bi D, Abdullah M, Hmeidi I, AlAzab R, Gharaibeh M, El-Heis M, et al.

J Healthc Eng, 2022;2022:3861161.
PMID: 37323471 DOI: 10.1155/2022/3861161

Kidney tumor (KT) is one of the diseases that have affected our society and is the seventh most common tumor in both men and women worldwide. The early detection of KT has significant benefits in reducing death rates, producing preventive measures that reduce effects, and overcoming the tumor. Compared to the tedious and time-consuming traditional diagnosis, automatic detection algorithms of deep learning (DL) can save diagnosis time, improve test accuracy, reduce costs, and reduce the radiologist's workload. In this paper, we present detection models for diagnosing the presence of KTs in computed tomography (CT) scans. Toward detecting and classifying KT, we proposed 2D-CNN models; three models are concerning KT detection such as a 2D convolutional neural network with six layers (CNN-6), a ResNet50 with 50 layers, and a VGG16 with 16 layers. The last model is for KT classification as a 2D convolutional neural network with four layers (CNN-4). In addition, a novel dataset from the King Abdullah University Hospital (KAUH) has been collected that consists of 8,400 images of 120 adult patients who have performed CT scans for suspected kidney masses. The dataset was divided into 80% for the training set and 20% for the testing set. The accuracy results for the detection models of 2D CNN-6 and ResNet50 reached 97%, 96%, and 60%, respectively. At the same time, the accuracy results for the classification model of the 2D CNN-4 reached 92%. Our novel models achieved promising results; they enhance the diagnosis of patient conditions with high accuracy, reducing radiologist's workload and providing them with a tool that can automatically assess the condition of the kidneys, reducing the risk of misdiagnosis. Furthermore, increasing the quality of healthcare service and early detection can change the disease's track and preserve the patient's life.

Matched MeSH terms: Tomography, X-Ray Computed/methods
Machine learning-based coronary artery disease diagnosis: A comprehensive review

Alizadehsani R, Abdar M, Roshanzamir M, Khosravi A, Kebria PM, Khozeimeh F, et al.

Comput Biol Med, 2019 08;111:103346.
PMID: 31288140 DOI: 10.1016/j.compbiomed.2019.103346

Coronary artery disease (CAD) is the most common cardiovascular disease (CVD) and often leads to a heart attack. It annually causes millions of deaths and billions of dollars in financial losses worldwide. Angiography, which is invasive and risky, is the standard procedure for diagnosing CAD. Alternatively, machine learning (ML) techniques have been widely used in the literature as fast, affordable, and noninvasive approaches for CAD detection. The results that have been published on ML-based CAD diagnosis differ substantially in terms of the analyzed datasets, sample sizes, features, location of data collection, performance metrics, and applied ML techniques. Due to these fundamental differences, achievements in the literature cannot be generalized. This paper conducts a comprehensive and multifaceted review of all relevant studies that were published between 1992 and 2019 for ML-based CAD diagnosis. The impacts of various factors, such as dataset characteristics (geographical location, sample size, features, and the stenosis of each coronary artery) and applied ML techniques (feature selection, performance metrics, and method) are investigated in detail. Finally, the important challenges and shortcomings of ML-based CAD diagnosis are discussed.

Matched MeSH terms: Tomography, X-Ray Computed
ExHiF: Alzheimer's disease detection using exemplar histogram-based features with CT and MR images

Kaplan E, Baygin M, Barua PD, Dogan S, Tuncer T, Altunisik E, et al.

Med Eng Phys, 2023 May;115:103971.
PMID: 37120169 DOI: 10.1016/j.medengphy.2023.103971

PURPOSE: The classification of medical images is an important priority for clinical research and helps to improve the diagnosis of various disorders. This work aims to classify the neuroradiological features of patients with Alzheimer's disease (AD) using an automatic hand-modeled method with high accuracy.
MATERIALS AND METHOD: This work uses two (private and public) datasets. The private dataset consists of 3807 magnetic resonance imaging (MRI) and computer tomography (CT) images belonging to two (normal and AD) classes. The second public (Kaggle AD) dataset contains 6400 MR images. The presented classification model comprises three fundamental phases: feature extraction using an exemplar hybrid feature extractor, neighborhood component analysis-based feature selection, and classification utilizing eight different classifiers. The novelty of this model is feature extraction. Vision transformers inspire this phase, and hence 16 exemplars are generated. Histogram-oriented gradients (HOG), local binary pattern (LBP) and local phase quantization (LPQ) feature extraction functions have been applied to each exemplar/patch and raw brain image. Finally, the created features are merged, and the best features are selected using neighborhood component analysis (NCA). These features are fed to eight classifiers to obtain highest classification performance using our proposed method. The presented image classification model uses exemplar histogram-based features; hence, it is called ExHiF.
RESULTS: We have developed the ExHiF model with a ten-fold cross-validation strategy using two (private and public) datasets with shallow classifiers. We have obtained 100% classification accuracy using cubic support vector machine (CSVM) and fine k nearest neighbor (FkNN) classifiers for both datasets.
CONCLUSIONS: Our developed model is ready to be validated with more datasets and has the potential to be employed in mental hospitals to assist neurologists in confirming their manual screening of AD using MRI/CT images.

Matched MeSH terms: Tomography, X-Ray Computed
Fulltext Role of Artificial Intelligence in COVID-19 Detection

Gudigar A, Raghavendra U, Nayak S, Ooi CP, Chan WY, Gangavarapu MR, et al.

Sensors (Basel), 2021 Dec 01;21(23).
PMID: 34884045 DOI: 10.3390/s21238045

The global pandemic of coronavirus disease (COVID-19) has caused millions of deaths and affected the livelihood of many more people. Early and rapid detection of COVID-19 is a challenging task for the medical community, but it is also crucial in stopping the spread of the SARS-CoV-2 virus. Prior substantiation of artificial intelligence (AI) in various fields of science has encouraged researchers to further address this problem. Various medical imaging modalities including X-ray, computed tomography (CT) and ultrasound (US) using AI techniques have greatly helped to curb the COVID-19 outbreak by assisting with early diagnosis. We carried out a systematic review on state-of-the-art AI techniques applied with X-ray, CT, and US images to detect COVID-19. In this paper, we discuss approaches used by various authors and the significance of these research efforts, the potential challenges, and future trends related to the implementation of an AI system for disease detection during the COVID-19 pandemic.

Matched MeSH terms: Tomography, X-Ray Computed
Right aortic arch with isolation of the left subclavian artery: a rare association with airway obstruction

Yubbu P, Latiff HA, Adam Abbaker AM

Cardiol Young, 2017 Apr;27(3):613-616.
PMID: 27817752 DOI: 10.1017/S1047951116001840

We present two interesting cases of isolated left subclavian artery from the pulmonary artery with symptoms of upper airway obstruction. The first patient had tetralogy of Fallot, pulmonary artery sling, bilateral superior caval veins, and left bronchial isomerism, suggesting heterotaxy syndrome. The second patient had a right aortic arch, isolated left subclavian artery, and bilateral arterial ducts. These two cases are interesting because of their rarity and uncommon presentation.

Matched MeSH terms: Tomography, X-Ray Computed
Implication of CDKAL1 single-nucleotide polymorphism rs 9465871 in obese and non-obese Egyptian children

Ismail NA, Ragab S, Abd El Dayem SM, Baky ANAE, Hamed M, Ahmed Kamel S, et al.

Med J Malaysia, 2018 10;73(5):286-290.
PMID: 30350806

INTRODUCTION: CDKAL1 single-nucleotide polymorphism rs 9465871variant is a risk locus for Type 2 Diabetes (T2DM).The study evaluated the associations of CDKAL1- rs9465871 with glycosylated hemoglobin A1C Level (HbA1c), fasting insulin level, insulin resistance and metabolic syndrome among obese and non- obese Egyptian children.
MATERIALS AND METHODS: The study included 43 obese children and 40 normal weight children. Anthropometric body measurements, bio-specimen and biochemistry assays were done. Genotyping of rs9465871 (CDKAL1) was conducted.
RESULTS: The percentages of the CC, CT, and TT genotypes of rs9465871in the lean children were 15%, 42.5%, and 42.5%, respectively. Regarding obese children, the frequencies were 18.6%, 58.1% and 23.3% respectively with no significant statistical difference. Comparison between the CDKAL1 rs 9465871 polymorphism showed that the highest value of fasting insulin was recorded in CC genotype (22.80± 15.18 [uIU/mL] P

Matched MeSH terms: Tomography, X-Ray Computed
Fulltext Orbital rhabdomyosarcoma: a case series

Chen, C.Y., Nor Hidayah, A.B., Adil, H.

Malaysian Journal of Medicine and Health Sciences, 2013;9(2):69-72.
MyJurnal

In this paper, we report three cases of orbital rhabdomyosarcoma in different age groups with different histopathologic types. Case 1 is a 10-year old Malay boy who presented with painless proptosis of the left eye. Magnetic resonance imaging (MRI) showed soft tissue mass arising from the lateral rectus muscle. Tissue biopsy revealed rhabdomyosarcoma of embryonal type. Case 2 is a 32-year old Malay man who presented with a progressive left eye proptosis associated with pain and redness. Computed Tomography (CT) scan showed a retrobulbar mass extending medially in the left orbit. Meanwhile, biopsy showed rhabdomyosarcoma of pleomorphic type. Case 3 is a 67-year old Malay woman who presented with proptosis and fungating growth of left orbital region, epistaxis and nasal blockage. CT scan revealed an ill-defined mass filling up the left orbital cavity. Biopsy showed rhabdomyosarcoma of alveolar type. Rhabdomyosarcoma is the most common in childhood but it should be considered as a differential diagnosis of orbital tumours irrespective of age.

Matched MeSH terms: Tomography, X-Ray Computed
Fulltext Giant aneurysm or pituitary macroadenoma: a diagnostical misconstrue

Pany A, Sobri M, Valarmathi S, Nazihah M, Latif AZ, Adnan JS

Med J Malaysia, 2004 Mar;59(1):123-5.
PMID: 15535350

We describe a case of a giant thrombosed intrasellar internal carotid artery aneurysm initially diagnosed as pituitary macroadenoma. The differentiating neuroimaging features were discussed.

Matched MeSH terms: Tomography, X-Ray Computed

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