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  • Open Access

    ARTICLE

    Residual U-Network for Breast Tumor Segmentation from Magnetic Resonance Images

    Ishu Anand1, Himani Negi1, Deepika Kumar1, Mamta Mittal2, Tai-hoon Kim3,*, 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… More >

  • Open Access

    ARTICLE

    Intelligent Breast Cancer Prediction Empowered with Fusion and Deep Learning

    Shahan Yamin Siddiqui1,2, Iftikhar Naseer3, Muhammad Adnan Khan4, Muhammad Faheem Mushtaq5, Rizwan Ali Naqvi6,*, Dildar Hussain7, Amir Haider8

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1033-1049, 2021, DOI:10.32604/cmc.2021.013952

    Abstract Breast cancer is the most frequently detected tumor that eventually could result in a significant increase in female mortality globally. According to clinical statistics, one woman out of eight is under the threat of breast cancer. Lifestyle and inheritance patterns may be a reason behind its spread among women. However, some preventive measures, such as tests and periodic clinical checks can mitigate its risk thereby, improving its survival chances substantially. Early diagnosis and initial stage treatment can help increase the survival rate. For that purpose, pathologists can gather support from nondestructive and efficient computer-aided diagnosis… More >

  • Open Access

    ARTICLE

    Machine Learning Enabled Early Detection of Breast Cancer by Structural Analysis of Mammograms

    Mavra Mehmood1, Ember Ayub1, Fahad Ahmad1,6,*, Madallah Alruwaili2, Ziyad A. Alrowaili3, Saad Alanazi2, Mamoona Humayun2, Muhammad Rizwan1, Shahid Naseem4, Tahir Alyas5

    CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 641-657, 2021, DOI:10.32604/cmc.2021.013774

    Abstract Clinical image processing plays a significant role in healthcare systems and is currently a widely used methodology. In carcinogenic diseases, time is crucial; thus, an image’s accurate analysis can help treat disease at an early stage. Ductal carcinoma in situ (DCIS) and lobular carcinoma in situ (LCIS) are common types of malignancies that affect both women and men. The number of cases of DCIS and LCIS has increased every year since 2002, while it still takes a considerable amount of time to recommend a controlling technique. Image processing is a powerful technique to analyze preprocessed… More >

  • Open Access

    ARTICLE

    Multi-Level Fusion in Ultrasound for Cancer Detection Based on Uniform LBP Features

    Diyar Qader Zeebaree1, Adnan Mohsin Abdulazeez2, Dilovan Asaad Zebari3,*, Habibollah Haron4, Haza Nuzly Abdull Hamed4

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3363-3382, 2021, DOI:10.32604/cmc.2021.013314

    Abstract Collective improvement in the acceptable or desirable accuracy level of breast cancer image-related pattern recognition using various schemes remains challenging. Despite the combination of multiple schemes to achieve superior ultrasound image pattern recognition by reducing the speckle noise, an enhanced technique is not achieved. The purpose of this study is to introduce a features-based fusion scheme based on enhancement uniform-Local Binary Pattern (LBP) and filtered noise reduction. To surmount the above limitations and achieve the aim of the study, a new descriptor that enhances the LBP features based on the new threshold has been proposed.… More >

  • Open Access

    ARTICLE

    Fully Automatic Segmentation of Gynaecological Abnormality Using a New Viola–Jones Model

    Ihsan Jasim Hussein1, M. A. Burhanuddin2, Mazin Abed Mohammed3,*, Mohamed Elhoseny4, Begonya Garcia-Zapirain5, Marwah Suliman Maashi6, Mashael S. Maashi7

    CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3161-3182, 2021, DOI:10.32604/cmc.2021.012691

    Abstract One of the most complex tasks for computer-aided diagnosis (Intelligent decision support system) is the segmentation of lesions. Thus, this study proposes a new fully automated method for the segmentation of ovarian and breast ultrasound images. The main contributions of this research is the development of a novel Viola–James model capable of segmenting the ultrasound images of breast and ovarian cancer cases. In addition, proposed an approach that can efficiently generate region-of-interest (ROI) and new features that can be used in characterizing lesion boundaries. This study uses two databases in training and testing the proposed… More >

  • Open Access

    ARTICLE

    Loss of Fingerprints as a Side Effect of Capecitabine Therapy: Case Report and Literature Review

    Jian Zhao*1, Xia Zhang†1, Xiaonan Cui*, Di Wang*, Bin Zhang*‡, Liying Ban*

    Oncology Research, Vol.28, No.1, pp. 103-106, 2020, DOI:10.3727/096504019X15605078731913

    Abstract Hand–foot syndrome (HFS) is the main side effect of capecitabine and affects the compression zones of the body such as the palms and soles, causing numbness, paresthesias, skin swelling or erythema, scaling, chapping, hard nodule-like blisters, and severe pain. Loss of fingerprints is also observed in some cases. Severe cases of HFS are common in the review of clinical reports. However, loss of fingerprints has not received significant attention. Two reported cases of loss of fingerprints in The New England Journal of Medicine and The BMJ have drawn attention to this side effect of capecitabine. Loss of More >

  • Open Access

    ARTICLE

    Changes in DNA Damage Repair Gene Expression and Cell Cycle Gene Expression Do Not Explain Radioresistance in Tamoxifen-Resistant Breast Cancer

    Annemarie E. M. Post*†, Johan Bussink*, Fred C. G. J. Sweep, Paul N. Span*

    Oncology Research, Vol.28, No.1, pp. 33-40, 2020, DOI:10.3727/096504019X15555794826018

    Abstract Tamoxifen-induced radioresistance, reported in vitro, might pose a problem for patients who receive neoadjuvant tamoxifen treatment and subsequently receive radiotherapy after surgery. Previous studies suggested that DNA damage repair or cell cycle genes are involved, and could therefore be targeted to preclude the occurrence of cross-resistance. We aimed to characterize the observed cross-resistance by investigating gene expression of DNA damage repair genes and cell cycle genes in estrogen receptor-positive MCF-7 breast cancer cells that were cultured to tamoxifen resistance. RNA sequencing was performed, and expression of genes characteristic for several DNA damage repair pathways was… More >

  • Open Access

    ARTICLE

    Pathway Mutations in Breast Cancer Using Whole-Exome Sequencing

    Ya-Sian Chang*†‡§, Chieh-Min Chang†‡, Chien-Yu Lin¶#, Dy-San Chao, Hsi-Yuan Huang, Jan-Gowth Chang*†‡**††

    Oncology Research, Vol.28, No.2, pp. 107-116, 2020, DOI:10.3727/096504019X15698362825407

    Abstract The genomic landscape of breast cancer (BC) is complex. The purpose of this study was to decipher the mutational profiles of Taiwanese patients with BC using next-generation sequencing. We performed whole-exome sequencing on DNA from 24 tumor tissue specimens from BC patients. Sanger sequencing was used to validate the identified variants. Sanger sequencing was also performed on paired adjacent nontumor tissues. After genotype calling and algorithmic annotations, we identified 49 deleterious variants in canonical cancer-related genes in our BC cohort. The most frequently mutated genes were PIK3CA (16.67%), FKBP9 (12.5%), TP53 (12.5%), ATM (8.33%), CHEK2 (8.33%), FOXO3 (8.33%), NTRK1More >

  • Open Access

    ARTICLE

    Fzd2 Contributes to Breast Cancer Cell Mesenchymal-Like Stemness and Drug Resistance

    Ping Yin*, Wei Wang*, Jian Gao, Yu Bai*, Zhuo Wang*, Lei Na*, Yu Sun*, Chenghai Zhao*

    Oncology Research, Vol.28, No.3, pp. 273-284, 2020, DOI:10.3727/096504020X15783052025051

    Abstract Cancer cell stemness is responsible for cancer relapse, distal metastasis, and drug resistance. Here we identified that Frizzled 2 (Fzd2), one member of Wnt receptor Frizzled family, induced human breast cancer (BC) cell stemness via noncanonical Wnt pathways. Fzd2 was overexpressed in human BC tissues, and Fzd2 overexpression was associated with an unfavorable outcome. Fzd2 knockdown (KD) disturbed the mesenchymallike phenotype, migration, and invasion of BC cells. Moreover, Fzd2 KD impaired BC cell mammosphere formation, reduced Lgr5+ BC cell subpopulation, and enhanced sensitivity of BC cells to chemical agents. Mechanistically, Fzd2 modulated and bound with More >

  • Open Access

    ARTICLE

    Pyrotinib Sensitizes 5-Fluorouracil-Resistant HER2+ Breast Cancer Cells to 5-Fluorouracil

    Jianing Yi*, Shuai Chen*, Pingyong Yi, Jinlin Luo*, Meng Fang*, Yang Du*, Lianhong Zou*, Peizhi Fan*

    Oncology Research, Vol.28, No.5, pp. 519-831, 2020, DOI:10.3727/096504020X15960154585410

    Abstract 5-Fluorouracil (5-FU) is a widely used chemotherapeutic agent for breast cancer. However, acquired chemoresistance leads to a loss of its efficacy; methods to reverse are urgently needed. Some studies have shown that pyrotinib, an ErbB receptor tyrosine kinase inhibitor, is effective against HER2+ breast cancer. However, whether pyrotinib sensitizes 5-FU-resistant breast cancer cells to 5-FU is unknown. We hypothesized that the combination of pyrotinib and 5-FU would show synergistic antitumor activity, and pyrotinib could reverse 5-FU resistance in HER2+ breast cancer cells in vitro and in vivo. Our data showed that pyrotinib inhibited the growth… More >

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