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  • Open Access

    ARTICLE

    Detecting Tuberculosis from Vietnamese X-Ray Imaging Using Transfer Learning Approach

    Ha Manh Toan1, Lam Thanh Hien2, Ngo Duc Vinh3, Do Nang Toan1,*

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5001-5016, 2023, DOI:10.32604/cmc.2023.033429

    Abstract Deep learning created a sharp rise in the development of autonomous image recognition systems, especially in the case of the medical field. Among lung problems, tuberculosis, caused by a bacterium called Mycobacterium tuberculosis, is a dangerous disease because of its infection and damage. When an infected person coughs or sneezes, tiny droplets can bring pathogens to others through inhaling. Tuberculosis mainly damages the lungs, but it also affects any part of the body. Moreover, during the period of the COVID-19 (coronavirus disease 2019) pandemic, the access to tuberculosis diagnosis and treatment has become more difficult, so early and simple detection… More >

  • Open Access

    ARTICLE

    Deep Learning Based Classification of Wrist Cracks from X-ray Imaging

    Jahangir Jabbar1, Muzammil Hussain2, Hassaan Malik2,*, Abdullah Gani3, Ali Haider Khan2, Muhammad Shiraz4

    CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1827-1844, 2022, DOI:10.32604/cmc.2022.024965

    Abstract Wrist cracks are the most common sort of cracks with an excessive occurrence rate. For the routine detection of wrist cracks, conventional radiography (X-ray medical imaging) is used but periodically issues are presented by crack depiction. Wrist cracks often appear in the human arbitrary bone due to accidental injuries such as slipping. Indeed, many hospitals lack experienced clinicians to diagnose wrist cracks. Therefore, an automated system is required to reduce the burden on clinicians and identify cracks. In this study, we have designed a novel residual network-based convolutional neural network (CNN) for the crack detection of the wrist. For the… More >

  • Open Access

    ARTICLE

    Detecting Lumbar Implant and Diagnosing Scoliosis from Vietnamese X-Ray Imaging Using the Pre-Trained API Models and Transfer Learning

    Chung Le Van1, Vikram Puri1, Nguyen Thanh Thao2, Dac-Nhuong Le3,4,*

    CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 17-33, 2021, DOI:10.32604/cmc.2020.013125

    Abstract With the rapid growth of the autonomous system, deep learning has become integral parts to enumerate applications especially in the case of healthcare systems. Human body vertebrae are the longest and complex parts of the human body. There are numerous kinds of conditions such as scoliosis, vertebra degeneration, and vertebrate disc spacing that are related to the human body vertebrae or spine or backbone. Early detection of these problems is very important otherwise patients will suffer from a disease for a lifetime. In this proposed system, we developed an autonomous system that detects lumbar implants and diagnoses scoliosis from the… More >

  • Open Access

    ARTICLE

    A Flexible Approach for the Calibration of Biplanar Radiography of the Spine on Conventional Radiological Systems

    Daniel C. Moura1, Jorge G. Barbosa1, Ana M. Reis2, João Manuel R. S. Tavares3

    CMES-Computer Modeling in Engineering & Sciences, Vol.60, No.2, pp. 115-138, 2010, DOI:10.3970/cmes.2010.060.115

    Abstract This paper presents a new method for the calibration of biplanar radiography that makes possible performing 3D reconstructions of the spine using conventional radiological systems. A novel approach is proposed in which a measuring device is used for determining focal distance and have a rough estimation of translation parameters. Using these data, 3D reconstructions of the spine with correct scale were successfully obtained without the need of calibration objects, something that was not previously achieved. For superior results, two optional steps may be executed that involve an optimisation of the geometrical parameters, followed by a scale adjustment with a very… More >

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