Jian Liu¹, Wantao Wang¹, Jie Chen^{2, *}, Guozhong Sun³, Alan Yang⁴

CMC-Computers, Materials & Continua, Vol.62, No.3, pp. 1187-1200, 2020, DOI:10.32604/cmc.2020.05883

Abstract Classification of skin lesions is a complex identification challenge. Due to the wide variety of skin lesions, doctors need to spend a lot of time and effort to judge the lesion image which zoomed through the dermatoscopy. The diagnosis which the algorithm of identifying pathological images assists doctors gets more and more attention. With the development of deep learning, the field of image recognition has made longterm progress. The effect of recognizing images through convolutional neural network models is better than traditional image recognition technology. In this work, we try to classify seven kinds of lesion images by various models… More >

Fan Liu¹, Jianwei Yan², Wantao Wang², Jian Liu^{2, *}, Junying Li³, Alan Yang⁴

CMC-Computers, Materials & Continua, Vol.62, No.2, pp. 801-816, 2020, DOI:10.32604/cmc.2020.07039

Abstract Skin lesion recognition is an important challenge in the medical field. In this paper, we have implemented an intelligent classification system based on convolutional neural network. First of all, this system can classify whether the input image is a dermascopic image with an accuracy of 99%. And then diagnose the dermoscopic image and the non-skin mirror image separately. Due to the limitation of the data, we can only realize the recognition of vitiligo by non-skin mirror. We propose a vitiligo recognition based on the probability average of three structurally identical CNN models. The method is more efficient and robust than… More >

Frederick H. Silver^1,*, Ruchit G. Shah², Dominick Benedetto³

Molecular & Cellular Biomechanics, Vol.16, Suppl.2, pp. 73-73, 2019, DOI:10.32604/mcb.2019.08150

Abstract Previous literature reports suggest that tissue stiffness is a predictor of cancer and metastatic behavior of lesions. We have used optical coherence tomography and vibrational analysis (VOCT) to characterize normal skin, scar, a verrucous carcinoma (a squamous cell carcinoma subtype), a basal cell carcinoma and benign skin lesions non-invasively and non-destructively. The results suggest that epidermal thickening and increased keratin and basal cell production occur in malignant lesions and lead to increases in surface hills and valleys as well as subsequent increases in epidermal stiffness values. Increased stiffness of the epidermis is a result of increased keratin and basal cell… More >

Muyi Guo¹, Yan Cai¹, Zhiyong Li^1,2,*

Molecular & Cellular Biomechanics, Vol.16, Suppl.1, pp. 49-49, 2019, DOI:10.32604/mcb.2019.05727

Abstract Observational studies have identified angiogenesis from the adventitial vasa vasorum and intraplaque hemorrhage (IPH) as critical factors in atherosclerotic plaque progression and destabilization. Here we propose a mathematical model incorporating intraplaque neovascularization and hemodynamic calculation for the quantitative evaluation of atherosclerotic plaque hemorrhage. An angiogenic microvasculature based on histology of a patient’s carotid plaque is generated by two-dimensional nine-point model of endothelial cell migration. Three key cells (endothelial cells, smooth muscle cells and macrophages) and three key chemicals (vascular endothelial growth factors, extracellular matrix and matrix metalloproteinase) are involved in the intraplaque angiogenesis model, and described by the reaction-diffusion partial… More >

Abdulkareem Younis SULEIMAN¹, Intisar Salim PITY², Mohammed R MOHAMMED², Bashar Abduljabar HASSAWI²

BIOCELL, Vol.43, No.3, pp. 175-181, 2019, DOI:10.32604/biocell.2019.06884

Abstract Ovarian lesions are commonly encountered pathologies that cannot be categorized clinicoradiologically. Definite diagnosis is of great importance for therapeutic and prognostic purposes. Histopathology gives accurate diagnosis in most cases. Few cases need supportive tests like immunohistochemistry. Objective: to study the histomorphological diversity of ovarian lesions, their age and location in North of Iraq (Mosul and Duhok). Patients and methods: In the period extended from January 2008 to December 2011, 161 cases of ovarian lesions were collected from pathology departments in Azadi General Hospital “Duhok” and Al-Jamhori Teaching Hospital “Mosul”. Automated tissue processor was used for histologic study and Streptavidin-biotin method… More >

Qunqun Hao^1,#, Bo Lyu^2,#, Yuhan Tang^1,#, Deya Wang¹, Yuanyuan Li¹, Qingliang Li¹, Yuhai Wang^1,* and Wenqiang Wang^1,*

Phyton-International Journal of Experimental Botany, Vol.88, No.2, pp. 109-117, 2019, DOI:10.32604/phyton.2019.06734

Abstract A barley mutant, 194, was observed to exhibit a leaf spot phenotype over the whole course of its growing period. In this study, the phenotype and antioxidant competence were studied in the lesion mimic mutant 194. Plant height was slightly higher in mutant 194 than in the wild type (WT). In addition, leaf spot per plant in mutant 194 was significantly higher than in WT. Antioxidant competence, as indicated by reactive oxygen species (ROS) accumulation, antioxidant enzyme activity, and the expression of antioxidant enzyme-encoding genes was also assessed in mutant 194. Compared to the WT, mutant 194 displayed a relatively… More >

Xingxing Xiao¹, Yang^1,*, Rui Li², Weiming Zhang³

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 101-115, 2019, DOI:10.32604/cmc.2019.05293

Abstract The medical industry develops rapidly as science and technology advance. People benefit from medical resource sharing, but suffer from privacy leaks at the same time. In order to protect patients’ privacy and improve quality of medical images, a novel reversible data hiding (RDH) scheme based on lesion extraction and with contrast enhancement is proposed. Furthermore, the proposed scheme can enhance the contrast of medial image's lesion area directly and embed high-capacity privacy data reversibly. Different from previous segmentation methods, this scheme first adopts distance regularized level set evolution (DRLSE) to extract lesion and targets at the lesion area accurately for… More >

Foued Derraz¹, Laurent Peyrodie², Antonio PINTI³, Abdelmalik Taleb-Ahmed³, Azzeddine Chikh⁴, Patrick Hautecoeur⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.67, No.2, pp. 95-118, 2010, DOI:10.3970/cmes.2010.067.095

Abstract We propose a new semi-automatic segmentation based Active Contour Model and statistic prior knowledge of Multiple Sclerosis (MS) Lesions in Regions Of Interest (RIO) within brain Magnetic Resonance Images(MRI). Reliable segmentation of MS lesion is important for at least three types of practical applications: pharmaceutical trails, making decision for drug treatment, patient follow-up. Manual segmentation of the MS lesions in brain MRI by well qualified experts is usually preferred. However, manual segmentation is hard to reproduce and can be highly cost and time consuming in the presence of large volume of MRI data. In other hand, automated segmentation methods are… More >