Mostafa Elbaz^1,2,*, Haitham Elwahsh¹, Ibrahim Mahmoud El-Henawy²

CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 2927-2944, 2023, DOI:10.32604/cmc.2023.033111

Abstract Computer vision is one of the significant trends in computer science. It plays as a vital role in many applications, especially in the medical field. Early detection and segmentation of different tumors is a big challenge in the medical world. The proposed framework uses ultrasound images from Kaggle, applying five diverse models to denoise the images, using the best possible noise-free image as input to the U-Net model for segmentation of the tumor, and then using the Convolution Neural Network (CNN) model to classify whether the tumor is benign, malignant, or normal. The main challenge faced by the framework in… More >

Venkata Sunil Srikanth^*, S. Krithiga

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 63-78, 2023, DOI:10.32604/iasc.2023.023474

Abstract Deep neural network (DNN) based computer-aided breast tumor diagnosis (CABTD) method plays a vital role in the early detection and diagnosis of breast tumors. However, a Brightness mode (B-mode) ultrasound image derives training feature samples that make closer isolation toward the infection part. Hence, it is expensive due to a meta-heuristic search of features occupying the global region of interest (ROI) structures of input images. Thus, it may lead to the high computational complexity of the pre-trained DNN-based CABTD method. This paper proposes a novel ensemble pre-trained DNN-based CABTD method using global- and local-ROI-structures of B-mode ultrasound images. It conveys… More >

Jing Lu¹, Yan Wu^2,#, Mingyan Hu¹, Yao Xiong¹, Yapeng Zhou¹, Ziliang Zhao¹, Liutong Shang^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 365-377, 2022, DOI:10.32604/cmes.2021.017897

Abstract Background: The main cause of breast cancer is the deterioration of malignant tumor cells in breast tissue. Early diagnosis of tumors has become the most effective way to prevent breast cancer. Method: For distinguishing between tumor and non-tumor in MRI, a new type of computer-aided detection CAD system for breast tumors is designed in this paper. The CAD system was constructed using three networks, namely, the VGG16, Inception V3, and ResNet50. Then, the influence of the convolutional neural network second migration on the experimental results was further explored in the VGG16 system. Result: CAD system built based on VGG16, Inception… More >

Ishu Anand¹, Himani Negi¹, Deepika Kumar¹, Mamta Mittal², Tai-hoon Kim^3,*, Sudipta Roy⁴

CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 3107-3127, 2021, DOI:10.32604/cmc.2021.014229

Abstract Breast cancer positions as the most well-known threat and the main source of malignant growth-related morbidity and mortality throughout the world. It is apical of all new cancer incidences analyzed among females. Two features substantially influence the classification accuracy of malignancy and benignity in automated cancer diagnostics. These are the precision of tumor segmentation and appropriateness of extracted attributes required for the diagnosis. In this research, the authors have proposed a ResU-Net (Residual U-Network) model for breast tumor segmentation. The proposed methodology renders augmented, and precise identification of tumor regions and produces accurate breast tumor segmentation in contrast-enhanced MR images.… More >

Bingbing ZHANG^{1, 2}, Ying ZHANG^{1, 2}, Xiaomei ZHANG^{1, 2}, Yonggang LV^{1, 2}

BIOCELL, Vol.42, No.1, pp. 17-24, 2018, DOI:10.32604/biocell.2018.06115

Abstract Mechanical microenvironment can strongly affect the metastatic efficiency of circulating tumor cells. However, the effect of suspension state on their extravasation and the mechanisms involved are still unclear. To explore the influence of suspension state on extravasation (including adhesion, spreading and transendothelial migration) of breast tumor cells and its relevant molecular mechanism, MDA-MB-231 cells were cultured on poly (2-hydroxyethyl methacrylate) coated 6-well plates to minic the suspension state. Suspension state promoted adhesion, spreading and transendothelial migration of MDA-MB-231 cells to EAhy926 endothelial cells (ECs) monolayer under both the static condition and 0.5 dyne/cm² flow shear stress (FSS). The number of… More >

Junhao Yang¹, Chunxiao Chen^1,*, Qingyang Zang¹, Jianfei Li¹

Molecular & Cellular Biomechanics, Vol.15, No.4, pp. 203-214, 2018, DOI:10.32604/mcb.2018.03824

Abstract Pathological slide is increasingly applied in the diagnosis of breast tumors despite the issues of large amount of data, slow viewing and high subjectivity. To overcome these problems, a micrograph recognition method based on convolutional neural network is proposed for pathological slide of breast tumor. Combined with multi-channel threshold and watershed segmentation, a sample database including single cell, adhesive cell and invalid cell was established. Then, the convolution neural network with six layers is constructed, which has ability to classify the stained breast tumor cells with accuracy of more than 90%, and evaluate the proliferation level with relative error of… More >