Guimin Hou¹, Jiaohua Qin^1,*, Xuyu Xiang¹, Yun Tan¹, Neal N. Xiong²

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1877-1891, 2021, DOI:10.32604/cmc.2021.017481 - 21 July 2021

Abstract Medical image segmentation is an important application field of computer vision in medical image processing. Due to the close location and high similarity of different organs in medical images, the current segmentation algorithms have problems with mis-segmentation and poor edge segmentation. To address these challenges, we propose a medical image segmentation network (AF-Net) based on attention mechanism and feature fusion, which can effectively capture global information while focusing the network on the object area. In this approach, we add dual attention blocks (DA-block) to the backbone network, which comprises parallel channels and spatial attention branches, More >

K. Muthumayil¹, S. Manikandan², S. Srinivasan³, José Escorcia-Gutierrez^4,*, Margarita Gamarra⁵, Romany F. Mansour⁶

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2031-2044, 2021, DOI:10.32604/cmc.2021.017116 - 21 July 2021

Abstract White Blood Cell (WBC) cancer or leukemia is one of the serious cancers that threaten the existence of human beings. In spite of its prevalence and serious consequences, it is mostly diagnosed through manual practices. The risks of inappropriate, sub-standard and wrong or biased diagnosis are high in manual methods. So, there is a need exists for automatic diagnosis and classification method that can replace the manual process. Leukemia is mainly classified into acute and chronic types. The current research work proposed a computer-based application to classify the disease. In the feature extraction stage, we… More >

V. Sudha^1,*, T. R. Ganesh Babu², N. Vikram¹, R. Raja²

Molecular & Cellular Biomechanics, Vol.18, No.3, pp. 139-145, 2021, DOI:10.32604/mcb.2021.016056 - 15 July 2021

Abstract Diabetic Retinopathy (DR) is a disease that occurs in the eye which results in blindness as it passes to proliferative stage. Diabetes can significantly result in symptoms like blurring of vision, kidney failure, nervous damage. Hence it has become necessary to identify retinal damage that occurs in diabetic eye due to raised glucose level in its initial stage itself. Hence automated detection of anamoly has become very essential. The appearance of crimson and yellow lesions is considered as the earliest symptoms of DR which are called as hemorrhages and exudates. If DR is analysed at… More >

Yousef Sanajalwe^1,2,*, Mohammed Anbar¹, Salam Al-E’mari¹

Computer Systems Science and Engineering, Vol.39, No.1, pp. 15-35, 2021, DOI:10.32604/csse.2021.017191 - 10 June 2021

Abstract The novel coronavirus disease 2019 (COVID-19) is a pandemic disease that is currently affecting over 200 countries around the world and impacting billions of people. The first step to mitigate and control its spread is to identify and isolate the infected people. But, because of the lack of reverse transcription polymerase chain reaction (RT-CPR) tests, it is important to discover suspected COVID-19 cases as early as possible, such as by scan analysis and chest X-ray by radiologists. However, chest X-ray analysis is relatively time-consuming since it requires more than 15 minutes per case. In this… More >

Jehyeok Rew, Hyungjoon Kim, Eenjun Hwang^*

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 801-817, 2021, DOI:10.32604/cmc.2021.017892 - 04 June 2021

Abstract Objective and quantitative assessment of skin conditions is essential for cosmeceutical studies and research on skin aging and skin regeneration. Various handcraft-based image processing methods have been proposed to evaluate skin conditions objectively, but they have unavoidable disadvantages when used to analyze skin features accurately. This study proposes a hybrid segmentation scheme consisting of Deeplab v3+ with an Inception-ResNet-v2 backbone, LightGBM, and morphological processing (MP) to overcome the shortcomings of handcraft-based approaches. First, we apply Deeplab v3+ with an Inception-ResNet-v2 backbone for pixel segmentation of skin wrinkles and cells. Then, LightGBM and MP are used More >

Walid El-Shafai¹, Noha A. El-Hag², Ghada M. El-Banby³, Ashraf A. M. Khalaf², Naglaa F. Soliman^4,*, Abeer D. Algarni⁴, Fathi E. Abd El-Samie^1,4

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1323-1341, 2021, DOI:10.32604/cmc.2021.017385 - 04 June 2021

Abstract Corona Virus Disease-2019 (COVID-19) continues to spread rapidly in the world. It has dramatically affected daily lives, public health, and the world economy. This paper presents a segmentation and classification framework of COVID-19 images based on deep learning. Firstly, the classification process is employed to discriminate between COVID-19, non-COVID, and pneumonia by Convolutional Neural Network (CNN). Then, the segmentation process is applied for COVID-19 and pneumonia CT images. Finally, the resulting segmented images are used to identify the infected region, whether COVID-19 or pneumonia. The proposed CNN consists of four Convolutional (Conv) layers, four batch More >

Javeria Naz¹, Muhammad Attique Khan¹, Majed Alhaisoni², Oh-Young Song^3,*, Usman Tariq⁴, Seifedine Kadry⁵

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 607-625, 2021, DOI:10.32604/cmc.2021.017101 - 04 June 2021

Abstract An automated system is proposed for the detection and classification of GI abnormalities. The proposed method operates under two pipeline procedures: (a) segmentation of the bleeding infection region and (b) classification of GI abnormalities by deep learning. The first bleeding region is segmented using a hybrid approach. The threshold is applied to each channel extracted from the original RGB image. Later, all channels are merged through mutual information and pixel-based techniques. As a result, the image is segmented. Texture and deep learning features are extracted in the proposed classification task. The transfer learning (TL) approach… More >

Osama S. Faragallah^1,*, Ghada Abdel-Aziz², Walid El-Shafai³, Hala S. El-sayed⁴, S.F. El-Zoghdy⁵, Gamal G.N. Geweid^6,7

Intelligent Automation & Soft Computing, Vol.29, No.1, pp. 15-29, 2021, DOI:10.32604/iasc.2021.017616 - 12 May 2021

Abstract The process of segmentation of the cardiac image aims to limit the inner and outer walls of the heart to segment all or portions of the organ’s boundaries. Due to its accurate morphological information, magnetic resonance (MR) images are typically used in cardiac segmentation as they provide the best contrast of soft tissues. The data acquired from the resulting cardiac images simplifies not only the laboratory assessment but also other conventional diagnostic techniques that provide several useful measures to evaluate and diagnose cardiovascular disease (CVD). Therefore, scientists have offered numerous segmentation schemes to remedy these More >

Mohamed Abdel-Basset¹, Reda Mohamed¹, Mohamed Abouhawwash^2,3, Ripon K. Chakrabortty⁴, Michael J. Ryan⁴, Yunyoung Nam^5,*

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2961-2977, 2021, DOI:10.32604/cmc.2021.016956 - 06 May 2021

Abstract Image segmentation is vital when analyzing medical images, especially magnetic resonance (MR) images of the brain. Recently, several image segmentation techniques based on multilevel thresholding have been proposed for medical image segmentation; however, the algorithms become trapped in local minima and have low convergence speeds, particularly as the number of threshold levels increases. Consequently, in this paper, we develop a new multilevel thresholding image segmentation technique based on the jellyfish search algorithm (JSA) (an optimizer). We modify the JSA to prevent descents into local minima, and we accelerate convergence toward optimal solutions. The improvement is… More >

Saleem Ibraheem Saleem^*, Adnan Mohsin Abdulazeez

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3353-3372, 2021, DOI:10.32604/cmc.2021.016342 - 06 May 2021

Abstract Writer identification (WI) based on handwritten text structures is typically focused on digital characteristics, with letters/strokes representing the information acquired from the current research in the integration of individual writing habits/styles. Previous studies have indicated that a word’s attributes contribute to greater recognition than the attributes of a character or stroke. As a result of the complexity of Arabic handwriting, segmenting and separating letters and strokes from a script poses a challenge in addition to WI schemes. In this work, we propose new texture features for WI based on text. The histogram of oriented gradient… More >