Khadija Khan, Samabia Tehsin^*

Journal on Artificial Intelligence, Vol.4, No.1, pp. 1-13, 2022, DOI:10.32604/jai.2022.028092

Abstract Leukemia is the cancer that starts in the blood cells due to the excess production of immature leucocytes that replace the cells with normal blood cells. Physicians rely on their experience to determine the type and subtype of Leukemia from the blood sample. Most people are misdiagnosed when it comes to its subtypes, the error rates can be up to 40% during the classification process. That too depends on the expertise of the physician. This research represents a Convolutional Neural Network based medical image classifier. The proposed technique can classify Leukemia and its five subtypes. State of the art deep… More >

Mahmoud Ragab^1,2,3,*, Khalid Eljaaly⁴, Maha Farouk S. Sabir⁵, Ehab Bahaudien Ashary⁶, S. M. Abo-Dahab^7,8, E. M. Khalil^3,9

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5751-5764, 2022, DOI:10.32604/cmc.2022.024658

Abstract The recent developments in biological and information technologies have resulted in the generation of massive quantities of data it speeds up the process of knowledge discovery from biological systems. Due to the advancements of medical imaging in healthcare decision making, significant attention has been paid by the computer vision and deep learning (DL) models. At the same time, the detection and classification of colorectal cancer (CC) become essential to reduce the severity of the disease at an earlier stage. The existing methods are commonly based on the combination of textual features to examine the classifier results or machine learning (ML)… More >

CSS Anupama¹, T. J. Benedict Jose², Heba F. Eid³, Nojood O Aljehane⁴, Fahd N. Al-Wesabi^5,*, Marwa Obayya⁶, Anwer Mustafa Hilal⁷

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3969-3983, 2022, DOI:10.32604/cmc.2022.022701

Abstract Biomedical images are used for capturing the images for diagnosis process and to examine the present condition of organs or tissues. Biomedical image processing concepts are identical to biomedical signal processing, which includes the investigation, improvement, and exhibition of images gathered using x-ray, ultrasound, MRI, etc. At the same time, cervical cancer becomes a major reason for increased women's mortality rate. But cervical cancer is an identified at an earlier stage using regular pap smear images. In this aspect, this paper devises a new biomedical pap smear image classification using cascaded deep forest (BPSIC-CDF) model on Internet of Things (IoT)… More >

Mohamed Esmail Karar^1,2, Marwa Ahmed Shouman³, Claire Chalopin^4,*

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1683-1697, 2022, DOI:10.32604/cmc.2022.018564

Abstract The novel Coronavirus disease 2019 (COVID-19) pandemic has begun in China and is still affecting thousands of patient lives worldwide daily. Although Chest X-ray and Computed Tomography are the gold standard medical imaging modalities for diagnosing potentially infected COVID-19 cases, applying Ultrasound (US) imaging technique to accomplish this crucial diagnosing task has attracted many physicians recently. In this article, we propose two modified deep learning classifiers to identify COVID-19 and pneumonia diseases in US images, based on generative adversarial neural networks (GANs). The proposed image classifiers are a semi-supervised GAN and a modified GAN with auxiliary classifier. Each one includes… More >

Nazish Naheed¹, Muhammad Shaheen¹, Sajid Ali Khan¹, Mohammed Alawairdhi^2,*, Muhammad Attique Khan^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 315-344, 2020, DOI:10.32604/cmes.2020.011380

Abstract In the area of pattern recognition and machine learning, features play a key role in prediction. The famous applications of features are medical imaging, image classification, and name a few more. With the exponential growth of information investments in medical data repositories and health service provision, medical institutions are collecting large volumes of data. These data repositories contain details information essential to support medical diagnostic decisions and also improve patient care quality. On the other hand, this growth also made it difficult to comprehend and utilize data for various purposes. The results of imaging data can become biased because of… More >

Lufeng Yuan^∗, Erlin Yao, Guangming Tan

Computer Systems Science and Engineering, Vol.33, No.2, pp. 105-113, 2018, DOI:10.32604/csse.2018.33.105

Abstract This paper proposes a machine learning based method which can detect certain events automatically and precisely in biomedical imaging. We detect one important and not well-defined event, which is called flash, in fluorescence images of Escherichia coli. Given a time series of images, first we propose a scheme to transform the event detection on region of interest (ROI) in images to a classification problem. Then with supervised human labeling data, we develop a feature selection technique to utilize support vector machine (SVM) to solve this classification problem. To reduce the time in training SVM model, a parallel version of SVM… More >

Zhiyong Li^1,2,*

Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 29-30, 2019, DOI:10.32604/mcb.2019.06308

Abstract In this article, we summarize our previous work in imaging-based computational modelling and simulation of the interaction between blood flow and atherosclerotic plaque. We also discussed our recent developments in multiphysical modelling of plaque progression and destabilization. Significance and translation of the modelling study to clinical practice are discussed in order to better assess plaque vulnerability and accurately predict a possible rupture. More >

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 >

Yongjie Zhang¹, Wenyan Wang¹, Xinghua Liang¹, Yuri Bazilevs², Ming-Chen Hsu², Trond Kvamsdal³, Reidar Brekken⁴, Jørgen Isaksen⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.42, No.2, pp. 131-150, 2009, DOI:10.3970/cmes.2009.042.131

Abstract This paper describes a comprehensive and high-fidelity finite element meshing approach for patient-specific arterial geometries from medical imaging data, with emphasis on cerebral aneurysm configurations. The meshes contain both the blood volume and solid arterial wall, and are compatible at the fluid-solid interface. There are four main stages for this meshing method: 1) Image segmentation and geometric model construction; 2) Tetrahedral mesh generation for the fluid volume using the octree-based method; 3) Mesh quality improvement stage, in which edge-contraction, pillowing, optimization, geometric flow smoothing, and mesh cutting are applied to the fluid mesh; and 4) Mesh generation for the blood… More >