Displaying all 6 publications

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  1. Rahmatullah B, Besar R
    J Med Eng Technol, 2009;33(6):417-25.
    PMID: 19637083 DOI: 10.1080/03091900802451232
    The motivation of this paper is to analyse the efficiency and reliability of our proposed algorithm of femur length (FL) measurement for the estimation of gestational age. The automated methods are divided into the following components: threshold, segmentation and extraction. Each component is examined, and improvements are made with the objective of finding the optimal result for FL measurement. The methods are tested with a total of 200 different digitized ultrasound images from our database collection. Overall, the study shows that the watershed-based segmentation method combined with enhanced femur extraction algorithm and a 12 x 12 block averaging seed-point threshold method perform identically well with the expert measurements for every image tested and superior as compared to a previous method.
  2. Zhang B, Rahmatullah B, Wang SL, Liu Z
    Multimed Tools Appl, 2023;82(10):15735-15762.
    PMID: 36185323 DOI: 10.1007/s11042-022-13744-9
    Modern medical examinations have produced a large number of medical images. It is a great challenge to transmit and store them quickly and securely. Existing solutions mainly use medical image encryption algorithms, but these encryption algorithms, which were developed for ordinary images, are time-consuming and must cope with insufficient security considerations when encrypting medical images. Compared with ordinary images, medical images can be divided into the region of interest and the region of background. In this paper, based on this characteristic, a plain-image correlative semi-selective medical image encryption algorithm using the enhanced two dimensional Logistic map was proposed. First, the region of interest of a plain medical image is permuted at the pixel level, then for the whole medical image, substitution is performed pixel by pixel. An ideal compromise between encryption speed and security can be achieved by full-encrypting the region of interest and semi-encrypting the region of background. Several main types of medical images and some normal images were selected as the samples for simulation, and main image cryptanalysis methods were used to analyze the results. The results showed that the cipher-images have a good visual quality, high information entropy, low correlation between adjacent pixels, as well as uniformly distribute histogram. The algorithm is sensitive to the initial key and plain-image, and has a large keyspace and low time complexity. The time complexity is lower when compared with the current medical image full encryption algorithm, and the security performance is better when compared with the current medical image selective encryption algorithm.
  3. Zhang B, Rahmatullah B, Wang SL, Almutairi HM, Xiao Y, Liu X, et al.
    Med Biol Eng Comput, 2023 Nov;61(11):2971-3002.
    PMID: 37542682 DOI: 10.1007/s11517-023-02874-3
    Since the COVID-19 pandemic, telemedicine or non-face-to-face medicine has increased significantly. In practice, various types of medical images are essential to achieve effective telemedicine. Medical image encryption algorithms play an irreplaceable role in the fast and secure transmission and storage of these medical images. However, most of the existing medical image encryption algorithms are full encryption algorithms, which are inefficient and time-consuming, so they are not suitable for emergency medical scenarios. To improve the efficiency of encryption, a small number of works have focused on partial or selective encryption algorithms for medical images, in which different levels of encryption strategies were adopted for different information content regions of medical images. However, these encryption algorithms have inadequate security more or less. In this paper, based on the Logistic map, we designed an improved variable dimension map. Then, an encryption algorithm for medical images was proposed based on it. This algorithm has two modes: (1) full encryption mode and (2) semi-full encryption mode, which can better adapt to different medical scenarios, respectively. In full encryption mode, all pixels of medical images are encrypted by using the confusion-diffusion structure. In semi-full encryption mode, the region of interest of medical images is extracted. The confusion was first adopted to encrypt the region of interest, and then, the diffusion was adopted to encrypt the entire image. In addition, no matter which encryption mode is used, the algorithm provides the function of medical image integrity verification. The proposed algorithm was simulated and analyzed to evaluate its effectiveness. The results show that in semi-full encryption mode, the algorithm has good security performance and lower time consumption; while in full encryption mode, the algorithm has better security performance and is acceptable in time.
  4. Zhang B, Rahmatullah B, Wang SL, Zhang G, Wang H, Ebrahim NA
    J Appl Clin Med Phys, 2021 Oct;22(10):45-65.
    PMID: 34453471 DOI: 10.1002/acm2.13394
    PURPOSE: Medical images are important in diagnosing disease and treatment planning. Computer algorithms that describe anatomical structures that highlight regions of interest and remove unnecessary information are collectively known as medical image segmentation algorithms. The quality of these algorithms will directly affect the performance of the following processing steps. There are many studies about the algorithms of medical image segmentation and their applications, but none involved a bibliometric of medical image segmentation.

    METHODS: This bibliometric work investigated the academic publication trends in medical image segmentation technology. These data were collected from the Web of Science (WoS) Core Collection and the Scopus. In the quantitative analysis stage, important visual maps were produced to show publication trends from five different perspectives including annual publications, countries, top authors, publication sources, and keywords. In the qualitative analysis stage, the frequently used methods and research trends in the medical image segmentation field were analyzed from 49 publications with the top annual citation rates.

    RESULTS: The analysis results showed that the number of publications had increased rapidly by year. The top related countries include the Chinese mainland, the United States, and India. Most of these publications were conference papers, besides there are also some top journals. The research hotspot in this field was deep learning-based medical image segmentation algorithms based on keyword analysis. These publications were divided into three categories: reviews, segmentation algorithm publications, and other relevant publications. Among these three categories, segmentation algorithm publications occupied the vast majority, and deep learning neural network-based algorithm was the research hotspots and frontiers.

    CONCLUSIONS: Through this bibliometric research work, the research hotspot in the medical image segmentation field is uncovered and can point to future research in the field. It can be expected that more researchers will focus their work on deep learning neural network-based medical image segmentation.

  5. Mohamed NF, Ab Manan N, Muhammad Firdaus Chan MF, Rahmatullah B, Abd Wahab R, Baharudin SNA, et al.
    Clin Child Psychol Psychiatry, 2023 Oct;28(4):1420-1434.
    PMID: 36927134 DOI: 10.1177/13591045231164870
    Internet Gaming Disorder (IGD) has been placed under the conditions for further study segment in DSM-5. The purpose of the current study was to develop a preliminary psychosocial model as a reference for providing appropriate intervention, particularly for adolescents with IGD. A total of 5290 adolescents from secondary schools in seven states in Malaysia were recruited by using proportionate random sampling. A standardized set of validated questionnaires such as DASS-21, BIS-11, and IGDS9-SF were distributed to participants that fulfilled the inclusion criteria. The prevalence of IGD among Malaysian adolescents was 3.5%. The bivariate analysis summarized that factors such as stress, impulsivity, gender, time spent using the internet, and relationship with parents and friends; have statistically significant associations with IGD. The logistic regression model revealed that adolescents with IGD were 9 times more likely to experience extremely severe stress (p < 0.001). Several psychosocial factors were associated strongly with IGD in the current study, however, mental health shows the most significant issues among adolescents with IGD. Immediate intervention through a psychological approach to internet gaming is needed from parents, schools, and also respective stakeholders. IGD may become one of the addictions diseases that cause deterioration in many aspects of an adolescent's future life without serious intervention.
  6. Mohamed NF, Jiun Ting T, Ab Manan N, Mohd Senari IF, Muhammad Firdaus Chan MF, Rahmatullah B, et al.
    PMID: 38163335 DOI: 10.1177/13591045231206967
    This study aimed to investigate the prevalence of social anxiety disorder (SAD) among Malaysian secondary school students during the COVID-19 pandemic and to explore its correlations with demographic variables, impulsivity behavior, and internet gaming disorder (IGD). A total of 1574 participants from 12 government secondary schools across five Malaysian states, comprising 569 males and 1005 females, completed an online questionnaire containing validated Malay versions of the Social Interaction Anxiety Scale, Barratt Impulsiveness Scale, and Internet Gaming Disorder Scale - Short Form. The findings revealed a notable SAD prevalence rate of 40.53% among Malaysian adolescents. Logistic regression analysis unveiled significant associations between SAD and factors such as attention impulsiveness (OR = 2.58, p < .001), motor impulsiveness (OR = 1.47, p = .03), female gender (OR = 2, p < .001), Malay ethnicity, and IGD (OR = 1.08, p < .001). In conclusion, this study provides valuable insights into the extent of social anxiety experienced by Malaysian secondary school students during the pandemic, shedding light on the demographic and psychosocial factors linked to its emergence. Furthermore, the research underscores a robust link between IGD and SAD, emphasizing the need for comprehensive interventions addressing both issues concurrently. By recognizing the multifaceted nature of these associations, future interventions can be tailored to provide holistic support for adolescents' mental well-being.
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