Kandasamy Kittusamy^*, Latha Shanmuga Vadivu Sampath Kumar

Computer Systems Science and Engineering, Vol.44, No.3, pp. 1989-2005, 2023, DOI:10.32604/csse.2023.026501

Abstract Medical Image Fusion is the synthesizing technology for fusing multimodal medical information using mathematical procedures to generate better visual on the image content and high-quality image output. Medical image fusion represents an indispensible role in fixing major solutions for the complicated medical predicaments, while the recent research results have an enhanced affinity towards the preservation of medical image details, leaving color distortion and halo artifacts to remain unaddressed. This paper proposes a novel method of fusing Computer Tomography (CT) and Magnetic Resonance Imaging (MRI) using a hybrid model of Non Sub-sampled Contourlet Transform (NSCT) and Joint Sparse Representation (JSR). This… More >

Mesfer Al Duhayyim^1,*, Areej A. Malibari², Marwa Obayya³, Mohamed K. Nour⁴, Ahmed S. Salama⁵, Mohamed I. Eldesouki⁶, Abu Sarwar Zamani⁷, Mohammed Rizwanullah⁷

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5473-5489, 2022, DOI:10.32604/cmc.2022.031976

Abstract The skeletal bone age assessment (BAA) was extremely implemented in development prediction and auxiliary analysis of medicinal issues. X-ray images of hands were detected from the estimation of bone age, whereas the ossification centers of epiphysis and carpal bones are important regions. The typical skeletal BAA approaches remove these regions for predicting the bone age, however, few of them attain suitable efficacy or accuracy. Automatic BAA techniques with deep learning (DL) methods are reached the leading efficiency on manual and typical approaches. Therefore, this study introduces an intellectual skeletal bone age assessment and classification with the use of metaheuristic with… More >

Vicky Mudeng^1,2, Jin-woo Jeong³, Se-woon Choe^1,4,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4677-4693, 2022, DOI:10.32604/cmc.2022.031046

Abstract A lump growing in the breast may be referred to as a breast mass related to the tumor. However, not all tumors are cancerous or malignant. Breast masses can cause discomfort and pain, depending on the size and texture of the breast. With an appropriate diagnosis, non-cancerous breast masses can be diagnosed earlier to prevent their cultivation from being malignant. With the development of the artificial neural network, the deep discriminative model, such as a convolutional neural network, may evaluate the breast lesion to distinguish benign and malignant cancers from mammogram breast masses images. This work accomplished breast masses classification… More >

C. S. S. Anupama¹, Raed Alsini², N. Supriya³, E. Laxmi Lydia⁴, Seifedine Kadry⁵, Sang-Soo Yeo⁶, Yongsung Kim^7,*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3219-3233, 2022, DOI:10.32604/cmc.2022.030267

Abstract Internet of Things (IoT) and blockchain receive significant interest owing to their applicability in different application areas such as healthcare, finance, transportation, etc. Medical image security and privacy become a critical part of the healthcare sector where digital images and related patient details are communicated over the public networks. This paper presents a new wind driven optimization algorithm based medical image encryption (WDOA-MIE) technique for blockchain enabled IoT environments. The WDOA-MIE model involves three major processes namely data collection, image encryption, optimal key generation, and data transmission. Initially, the medical images were captured from the patient using IoT devices. Then,… More >

Walid El-Shafai^1,2, Amira A. Mahmoud¹, Anas M. Ali^1,3, El-Sayed M. El-Rabaie¹, Taha E. Taha¹, Osama F. Zahran¹, Adel S. El-Fishawy¹, Naglaa F. Soliman⁴, Amel A. Alhussan^5,*, Fathi E. Abd El-Samie¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3795-3814, 2022, DOI:10.32604/cmc.2022.029134

Abstract In the literature, numerous techniques have been employed to decrease noise in medical image modalities, including X-Ray (XR), Ultrasonic (Us), Computed Tomography (CT), Magnetic Resonance Imaging (MRI), and Positron Emission Tomography (PET). These techniques are organized into two main classes: the Multiple Image (MI) and the Single Image (SI) techniques. In the MI techniques, images usually obtained for the same area scanned from different points of view are used. A single image is used in the entire procedure in the SI techniques. SI denoising techniques can be carried out both in a transform or spatial domain. This paper is concerned… More >

Walid El-Shafai^1,2, Amira A. Mahmoud¹, El-Sayed M. El-Rabaie¹, Taha E. Taha¹, Osama F. Zahran¹, Adel S. El-Fishawy¹, Naglaa F. Soliman³, Amel A. Alhussan^4,*, Fathi E. Abd El-Samie¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3119-3135, 2022, DOI:10.32604/cmc.2022.028935

Abstract This paper presents a study of the segmentation of medical images. The paper provides a solid introduction to image enhancement along with image segmentation fundamentals. In the first step, the morphological operations are employed to ensure image detail protection and noise-immunity. The objective of using morphological operations is to remove the defects in the texture of the image. Secondly, the Fuzzy C-Means (FCM) clustering algorithm is used to modify membership function based only on the spatial neighbors instead of the distance between pixels within local spatial neighbors and cluster centers. The proposed technique is very simple to implement and significantly… More >

Walid El-Shafai^1,2, Hayam A. Abd El-Hameed³, Ashraf A. M. Khalaf³, Naglaa F. Soliman⁴, Amel A. Alhussan^5,*, Fathi E. Abd El-Samie¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2713-2730, 2022, DOI:10.32604/cmc.2022.028739

Abstract Authentication of the digital image has much attention for the digital revolution. Digital image authentication can be verified with image watermarking and image encryption schemes. These schemes are widely used to protect images against forgery attacks, and they are useful for protecting copyright and rightful ownership. Depending on the desirable applications, several image encryption and watermarking schemes have been proposed to moderate this attention. This framework presents a new scheme that combines a Walsh Hadamard Transform (WHT)-based image watermarking scheme with an image encryption scheme based on Double Random Phase Encoding (DRPE). First, on the sender side, the secret medical… More >

Walid El-Shafai^1,2, Amira A. Mahmoud¹, El-Sayed M. El-Rabaie¹, Taha E. Taha¹, Osama F. Zahran¹, Adel S. El-Fishawy¹, Naglaa F. Soliman³, Amel A. Alhussan^4,*, Fathi E. Abd El-Samie¹

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3455-3472, 2022, DOI:10.32604/cmc.2022.028722

Abstract The segmentation process requires separating the image region into sub-regions of similar properties. Each sub-region has a group of pixels having the same characteristics, such as texture or intensity. This paper suggests an efficient hybrid segmentation approach for different medical image modalities based on particle swarm optimization (PSO) and improved fast fuzzy C-means clustering (IFFCM) algorithms. An extensive comparative study on different medical images is presented between the proposed approach and other different previous segmentation techniques. The existing medical image segmentation techniques incorporate clustering, thresholding, graph-based, edge-based, active contour, region-based, and watershed algorithms. This paper extensively analyzes and summarizes the… More >

Prasanalakshmi Balaji^1,*, B. Sri Revathi², Praveetha Gobinathan³, Shermin Shamsudheen³, Thavavel Vaiyapuri⁴

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2275-2291, 2022, DOI:10.32604/cmc.2022.028560

Abstract Recently medical image classification plays a vital role in medical image retrieval and computer-aided diagnosis system. Despite deep learning has proved to be superior to previous approaches that depend on handcrafted features; it remains difficult to implement because of the high intra-class variance and inter-class similarity generated by the wide range of imaging modalities and clinical diseases. The Internet of Things (IoT) in healthcare systems is quickly becoming a viable alternative for delivering high-quality medical treatment in today’s e-healthcare systems. In recent years, the Internet of Things (IoT) has been identified as one of the most interesting research subjects in… More >

Xiaowei Gu^1,#, Shuwen Chen^1,2,#,*, Huisheng Zhu¹, Mackenzie Brown^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 507-530, 2022, DOI:10.32604/cmes.2022.018948

Abstract Coronavirus disease 2019 brings a huge burden on the medical industry all over the world. In the background of artificial intelligence (AI) and Internet of Things (IoT) technologies, chest computed tomography (CT) and chest X-ray (CXR) scans are becoming more intelligent, and playing an increasingly vital role in the diagnosis and treatment of diseases. This paper will introduce the segmentation of methods and applications. CXR and CT diagnosis of COVID-19 based on deep learning, which can be widely used to fight against COVID-19. More >