K. Yuvaraj^*, U. S. Ragupathy

Computer Systems Science and Engineering, Vol.40, No.3, pp. 823-834, 2022, DOI:10.32604/csse.2022.018837

Abstract This research implements a novel segmentation of mammographic mass. Three methods are proposed, namely, segmentation of mass based on iterative active contour, automatic region growing, and fully automatic mask selection-based active contour techniques. In the first method, iterative threshold is performed for manual cropped preprocessed image, and active contour is applied thereafter. To overcome manual cropping in the second method, an automatic seed selection followed by region growing is performed. Given that the result is only a few images owing to over segmentation, the third method uses a fully automatic active contour. Results of the segmentation techniques are compared with… More >

Yu-Dong Zhang¹, Muhammad Attique Khan², Ziquan Zhu³, Shui-Hua Wang^4,*

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3145-3162, 2021, DOI:10.32604/cmc.2021.018040

Abstract (Aim) COVID-19 is an ongoing infectious disease. It has caused more than 107.45 m confirmed cases and 2.35 m deaths till 11/Feb/2021. Traditional computer vision methods have achieved promising results on the automatic smart diagnosis. (Method) This study aims to propose a novel deep learning method that can obtain better performance. We use the pseudo-Zernike moment (PZM), derived from Zernike moment, as the extracted features. Two settings are introducing: (i) image plane over unit circle; and (ii) image plane inside the unit circle. Afterward, we use a deep-stacked sparse autoencoder (DSSAE) as the classifier. Besides, multiple-way data augmentation is chosen… More >

Harshit Kaushik¹, Dilbag Singh², Shailendra Tiwari³, Manjit Kaur², Chang-Won Jeong⁴, Yunyoung Nam^5,*, Muhammad Attique Khan⁶

CMC-Computers, Materials & Continua, Vol.69, No.3, pp. 3459-3475, 2021, DOI:10.32604/cmc.2021.017337

Abstract In March 2020, the World Health Organization declared the coronavirus disease (COVID-19) outbreak as a pandemic due to its uncontrolled global spread. Reverse transcription polymerase chain reaction is a laboratory test that is widely used for the diagnosis of this deadly disease. However, the limited availability of testing kits and qualified staff and the drastically increasing number of cases have hampered massive testing. To handle COVID-19 testing problems, we apply the Internet of Things and artificial intelligence to achieve self-adaptive, secure, and fast resource allocation, real-time tracking, remote screening, and patient monitoring. In addition, we implement a cloud platform for… More >

Mohammed Baz^1,*, Hatem Zaini¹, Hala S. El-sayed², Matokah AbuAlNaja³, Heba M. El-Hoseny⁴, Osama S. Faragallah⁵

Intelligent Automation & Soft Computing, Vol.30, No.1, pp. 97-111, 2021, DOI:10.32604/iasc.2021.018265

Abstract In the era of medical technology, automatic scan detection can be considered a charming tool in medical diagnosis, especially with rapidly spreading diseases. In light of the prevalence of the current Coronavirus disease (COVID-19), which is characterized as highly contagious and very complicated, it is urgent and necessary to find a quick way that can be practically implemented for diagnosing COVID-19. The danger of the virus lies in the fact that patients can spread the disease without showing any symptoms. Moreover, several vaccines have been produced and vaccinated in large numbers but, the outbreak does not stop. Therefore, it is… More >