R. Rajakumari^1,*, L. Kalaivani²

Intelligent Automation & Soft Computing, Vol.32, No.2, pp. 1089-1107, 2022, DOI:10.32604/iasc.2022.020178 - 17 November 2021

Abstract Breast cancer is a commonly diagnosed disease in women. Early detection, a personalized treatment approach, and better understanding are necessary for cancer patients to survive. In this work, a deep learning network and traditional convolution network were both employed with the Digital Database for Screening Mammography (DDSM) dataset. Breast cancer images were subjected to background removal followed by Wiener filtering and a contrast limited histogram equalization (CLAHE) filter for image restoration. Wavelet packet decomposition (WPD) using the Daubechies wavelet level 3 (db3) was employed to improve the smoothness of the images. For breast cancer recognition,… More >

S. Prakash^1,*, M. Vinoth Kumar², R. Saravana Ram³, Miodrag Zivkovic⁴, Nebojsa Bacanin⁴, Milos Antonijevic⁴

Computer Systems Science and Engineering, Vol.41, No.2, pp. 735-749, 2022, DOI:10.32604/csse.2022.020533 - 25 October 2021

Abstract Breast cancer has become the second leading cause of death among women worldwide. In India, a woman is diagnosed with breast cancer every four minutes. There has been no known basis behind it, and detection is extremely challenging among medical scientists and researchers due to unknown reasons. In India, the ratio of women being identified with breast cancer in urban areas is 22:1. Symptoms for this disease are micro calcification, lumps, and masses in mammogram images. These sources are mostly used for early detection. Digital mammography is used for breast cancer detection. In this study,… More >

PRIYANKA THAKUR¹, REENA V. SAINI^2,3,*, ANIL K. CHHILLAR⁴, NEERAJ K. SAINI⁵, VIJAY KUMAR THAKUR⁶, SAMARJEET SINGH SIWAL⁷, ADESH K. SAINI^2,3,*

BIOCELL, Vol.46, No.2, pp. 309-324, 2022, DOI:10.32604/biocell.2022.016916 - 20 October 2021

Abstract Breast cancer, also recognized as the principal cause of cancer-related deaths among women, is the second most familiar and prevalent form of cancer. New diagnostic and prognostic biomarkers that are highly specific are urgently needed for its early prognosis. MicroRNAs (miRNAs), a class of non-coding RNAs, are known to control the biological processes involving transcription, post-transcriptional and covalent modifications, splicing, translation, cell differentiation, proliferation, apoptosis, cancer progression, and invasion. Any dysregulation in miRNA expression, demonstrating their oncogenic and tumor-suppressive functions, contributes to cancer progression. MicroRNA-21 (miR-21), an ‘onco-miR’ in breast cancer, is involved in tumor… More >

S. Sathiya Devi¹, S. Vidivelli^2,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3049-3066, 2022, DOI:10.32604/cmc.2022.019917 - 27 September 2021

Abstract Breast cancer is one of the common invasive cancers and stands at second position for death after lung cancer. The present research work is useful in image processing for characterizing shape and gray-scale complexity. The proposed Modified Differential Box Counting (MDBC) extract Fractal features such as Fractal Dimension (FD), Lacunarity, and Succolarity for shape characterization. In traditional DBC method, the unreasonable results obtained when FD is computed for tumour regions with the same roughness of intensity surface but different gray-levels. The problem is overcome by the proposed MDBC method that uses box over counting and… More >

Hanan A. Hosni Mahmoud, Amal H. Alharbi, Norah S. Alghamdi^*

Intelligent Automation & Soft Computing, Vol.31, No.2, pp. 1273-1286, 2022, DOI:10.32604/iasc.2022.020662 - 22 September 2021

Abstract In this paper we propose a computerized breast cancer detection and breast masses classification system utilizing mammograms. The motivation of the proposed method is to detect breast cancer tumors in early stages with more accuracy and less negative false cases. Our proposed method utilizes clustering of different features by segmenting the breast mammogram and then extracts deep features using the presented Convolution Neural Network (CNN). The extracted features are then combined with subjective features such as shape, texture and density. The combined features are then utilized by the Extreme Learning Machine Clustering (ELMC) algorithm to… More >

G. Jayandhi^1,*, J.S. Leena Jasmine², S. Mary Joans²

Computer Systems Science and Engineering, Vol.40, No.2, pp. 491-503, 2022, DOI:10.32604/csse.2022.016376 - 09 September 2021

Abstract The most common form of cancer for women is breast cancer. Recent advances in medical imaging technologies increase the use of digital mammograms to diagnose breast cancer. Thus, an automated computerized system with high accuracy is needed. In this study, an efficient Deep Learning Architecture (DLA) with a Support Vector Machine (SVM) is designed for breast cancer diagnosis. It combines the ideas from DLA with SVM. The state-of-the-art Visual Geometric Group (VGG) architecture with 16 layers is employed in this study as it uses the small size of 3 × 3 convolution filters that reduces… More >

Naglaa F. Soliman^1,2, Naglaa S. Ali², Mahmoud I. Aly^2,3, Abeer D. Algarni^1,*, Walid El-Shafai⁴, Fathi E. Abd El-Samie^1,4

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1315-1334, 2022, DOI:10.32604/cmc.2022.017001 - 07 September 2021

Abstract Breast cancer is the most common type of cancer, and it is the reason for cancer death toll in women in recent years. Early diagnosis is essential to handle breast cancer patients for treatment at the right time. Screening with mammography is the preferred examination for breast cancer, as it is available worldwide and inexpensive. Computer-Aided Detection (CAD) systems are used to analyze medical images to detect breast cancer, early. The death rate of cancer patients has decreased by detecting tumors early and having appropriate treatment after operations. Processing of mammogram images has four main… More >

Qingzhu Song¹, Fenglan Zhang², Tian Yuan², Yulong Wei²

European Cytokine Network, Vol.32, No.2, pp. 39-47, 2021, DOI:10.1684/ecn.2021.0468

Abstract Breast cancer is by far the most common malignancy found in women and causes a significant public health problem around the world. Early diagnosis of cancer plays an important role in successful treatment and survival of patients. This study aims to investigate the possibility of plasma Tie2 to be used as a biomarker for diagnosis of breast cancer. In total, 20 healthy volunteers and 33 breast cancer patients were considered for this study. The level of Tie2 in plasma was detected using the ELISA technique and immunohistochemistry was performed to measure the expression of Tie2… More >

MOTAWA E. EL-HOUSEINI¹, MOSTAFA S. ARAFAT², AHMED M. EL-HUSSEINY³, ISLAM M. KASEM², MAHMOUD M. KAMEL⁴, AHMED H. EL-HABASHY⁵, MEDHAT M. KHAFAGY⁶, ENAS M. RADWAN⁴, MAHA H. HELAL⁷, MONA S. ABDELLATEIF^1,*

Oncology Research, Vol.29, No.5, pp. 319-329, 2021, DOI:10.32604/or.2022.025249 - 10 October 2022

Abstract Immunotherapy becomes a promising line of treatment for breast cancer (BC) however, its success rate is still limited. Methods: The study was designed to optimize the condition for producing an effective dendritic cell (DCs) based immunotherapy by using DCs and T lymphocytes together with tumor-infiltrating lymphocytes (TILs) and tumor-infiltrating DCs (TIDCs), treated with anti-PD1 and anti-CTLA4 monoclonal antibodies. This mixture of immune cells was co-cultured with autologous breast cancer cells (BCCs) isolated from 26 BC females. Results: There was a significant upregulation of CD86 and CD83 on DCs (P = 0.001 and 0.017, respectively), similarly upregulation of… More >

LIMIN ZHOU¹, LIANBO ZHANG², XIN GUAN³, YI DONG¹, TAO LIU^1,*

Oncology Research, Vol.29, No.4, pp. 251-262, 2021, DOI:10.32604/or.2022.03582 - 31 August 2022

Abstract Long noncoding RNA PPP1R14B antisense RNA 1 (PPP1R14B-AS1) has emerged as a critical modulator of liver cancer and lung adenocarcinoma progression. However, the functional importance and biological relevance of PPP1R14B-AS1 in breast cancer remain unclear. Therefore, this study was designed to detect PPP1R14B-AS1 levels in breast cancer cells using qRT–PCR and elucidate the influence of PPP1R14B-AS1 on aggressive phenotypes. Furthermore, molecular events mediating the action of PPP1R14B-AS1 were characterized in detail. Functional experiments addressed the impacts of PPP1R14B-AS1 knockdown on breast cancer cells. In this study, PPP1R14B-AS1 was found to be overexpressed in breast cancer,… More >