Yanyun Jiang¹, Yuanjie Zheng^1,2,*, Xiaodan Sui¹, Wanzhen Jiao³, Yunlong He⁴, Weikuan Jia¹

Computer Systems Science and Engineering, Vol.36, No.3, pp. 537-549, 2021, DOI:10.32604/csse.2021.014578

Abstract Multispectral imaging (MSI) technique is often used to capture images of the fundus by illuminating it with different wavelengths of light. However, these images are taken at different points in time such that eyeball movements can cause misalignment between consecutive images. The multispectral image sequence reveals important information in the form of retinal and choroidal blood vessel maps, which can help ophthalmologists to analyze the morphology of these blood vessels in detail. This in turn can lead to a high diagnostic accuracy of several diseases. In this paper, we propose a novel semi-supervised end-to-end deep learning framework called “Adversarial Segmentation… More >

Marrium Anam¹, Vasaki a/p Ponnusamy^2,*, Muzammil Hussain³, Muhammad Waqas Nadeem^2,4, Mazhar Javed³, Hock Guan Goh², Sadia Qadeer³

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 89-105, 2021, DOI:10.32604/cmc.2021.013159

Abstract Trabecular bone holds the utmost importance due to its significance regarding early bone loss. Diseases like osteoporosis greatly affect the structure of the Trabecular bone which results in different outcomes like high risk of fracture. The objective of this paper is to inspect the characteristics of the Trabecular Bone by using the Magnetic Resonance Imaging (MRI) technique. These characteristics prove to be quite helpful in studying different studies related to Trabecular bone such as osteoporosis. The things that were considered before the selection of the articles for the systematic review were language, research field, and electronic sources. Only those articles… More >

Dongfang Yu, Jinwei Wang^*

Journal of Information Hiding and Privacy Protection, Vol.2, No.4, pp. 165-174, 2020, DOI:10.32604/jihpp.2020.010466

Abstract Chemical spectral analysis is contemporarily undergoing a revolution and drawing much attention of scientists owing to machine learning algorithms, in particular convolutional networks. Hence, this paper outlines the major machine learning and especially deep learning methods contributed to interpret chemical images, and overviews the current application, development and breakthrough in different spectral characterization. Brief categorization of reviewed literatures is provided for studies per application apparatus: X-Ray spectra, UV-Vis-IR spectra, Micro-scope, Raman spectra, Photoluminescence spectrum. End with the overview of existing circumstances in this research area, we provide unique insight and promising directions for the chemical imaging field to fully couple… More >

Qi Chen, Wei Cui^*, Jianqiu Sun, Xingguang Li, Xuyu Tian

Intelligent Automation & Soft Computing, Vol.27, No.1, pp. 115-126, 2021, DOI:10.32604/iasc.2021.011617

Abstract The existing range-Doppler algorithms for SAR imaging are affected by a fast-time Doppler effect so they cannot be directly applied to FMCW SAR. Moreover, range migration is more evident in squint mode. To reveal the influence of the continuous motion of FMCW SAR in the squint mode on the echo signal and optimize the imaging process, an improved range-Doppler algorithm is based on squint FMCW SAR imaging is proposed in this paper. Firstly, the imaging geometry model and echo signal model of FMCW SAR are analyzed and deduced. The problem of Doppler center offset under squint mode is eliminated by… More >

Chung Le Van¹, Vikram Puri¹, Nguyen Thanh Thao², Dac-Nhuong Le^3,4,*

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 >

Mo Hou^1,*, Weiyu Kevin Chiang^2,*, Weiqiang Hong¹, Maoyun Yang¹, Wenhua Yu^3,4

Molecular & Cellular Biomechanics, Vol.17, No.4, pp. 165-178, 2020, DOI:10.32604/mcb.2020.010805

Abstract To achieve the image registration/fusion and perfect the quality of the integration, with dual modality contrast agent (DMCA), a novel multi-scale representation registration method between ultrasound imaging (US) and magnetic resonance imaging (MRI) is presented in the paper, and how DMCA influence on registration accuracy is chiefly discussed. Owing to US’s intense speckle noise, it is a tremendous challenge to register US with any other modality images. How to improve the algorithms for US processing has become the bottleneck, and in the short term it is difficult to have a breakthrough. In that case, DMCA is employed in both US… 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 >

Lan Yang¹, Shun Qi^2,3,#, Chen Qiao^1,*, Yanmei Kang¹

CMES-Computer Modeling in Engineering & Sciences, Vol.125, No.1, pp. 215-237, 2020, DOI:10.32604/cmes.2020.010796

Abstract Schizophrenia (SZ) is one of the most common mental diseases. Its main characteristics are abnormal social behavior and inability to correctly understand real things. In recent years, the magnetic resonance imaging (MRI) technique has been popularly utilized to study SZ. However, it is still a great challenge to reveal the essential information contained in the MRI data. In this paper, we proposed a biomarker selection approach based on the multiple hypothesis testing techniques to explore the difference between SZ and healthy controls by using both functional and structural MRI data, in which biomarkers represent both abnormal brain functional connectivity and… More >

Zhenli Wang^{1, *}, Qun Wang¹, Jiayin Liu¹, Zheng Liang¹, Jingsong Xu²

CMC-Computers, Materials & Continua, Vol.65, No.3, pp. 2351-2363, 2020, DOI:10.32604/cmc.2020.011909

Abstract To address the low-resolution imaging problem in relation to traditional Range Doppler (RD) algorithm, this paper intends to propose a new algorithm based on Fractional Fourier Transform (FrFT), which proves highly advantageous in the acquisition of high-resolution Synthetic Aperture Radar (SAR) images. The expression of the optimal order of SAR range signals using FrFT is deduced in detail, and the corresponding expression of the azimuth signal is also given. Theoretical analysis shows that, the optimal order in range (azimuth) direction, which turns out to be very unique, depends on the known imaging parameters of SAR, therefore the engineering practicability 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 >