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13 results for “Benign and Malignant”
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Research ArticleOpen accessIn the keywordsGAUSSIAN MIXTURE MODEL BASED CLASSIFICATION OF MICROCALCIFICATION IN MAMMOGRAMS USING DYADIC WAVELET TRANSFORMSuman Mishra, Hariharan RanganathanBreast cancer is a serious health related issue for women in the world. Cancer detected at premature stages has a higher probability of being cured, whereas at advanced stages chances of survival are bleak. Screening programs aid in detecting potential breast cancer at early stages of the disease. Among the various screening programs, mammography is the proven standard for screening … …Journal of Computer Science, Vol. 9, Issue 10 · 5 Sep 2013 · 6,867 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA robust Approach to Classify Microcalcification in Digital Mammograms Using Contourlet Transform and Support Vector MachineJ. S. Leena Jasmine, S. Baskaran, A. GovardhanMammogram is the best available radiographic method to detect breast cancer in the early stage. However detecting a microcalcification clusters in the early stage is a tough task for the radiologist. Herein we present a novel approach for classifying microcalcification in digital mammograms using Nonsubsampled Contourlet Transform (NSCT) and Support Vector Machine (SVM). The classification of microcalcification is achieved by … …American Journal of Engineering and Applied Sciences, Vol. 6, Issue 1 · 28 Feb 2013 · 7,856 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage Pre-Processing Techniques to Improve DBT Classification Accuracy With CNN ResNet-50Qodri Aziz, Slamet Riyadi et al.Digital Breast Tomosynthesis (DBT) is a three-dimensional imaging technology that is meant to determine breast cancer more accurately than regular mammograms. But low contrast and noise can make DBT images less clear, which can make deep learning-based classification less accurate. This study seeks to assess the impact of diverse preprocessing techniques on breast cancer classification outcomes utilizing the ResNet-50 Convolutional … …Journal of Computer Science, Vol. 22, Issue 10 · 21 Oct 2026 · 349 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid CNN-Based Transformer Pipeline With Radiomic Fusion for Multi-Class Lung Cancer DetectionAanchal Vij, Kuldeep Singh Kaswan, Anand NayyarEarly detection of lung cancer remains challenging due to high intra-class variation and inter-class similarity in Computed Tomography (CT) images. In this paper, we propose a hybrid deep learning model that combines convolutional, attention-based, and transformer-guided representations to address these challenges in multi-class lung cancer classification. For deep feature extraction, we use the EfficientNetV2-S architecture augmented with a Convolutional Block … …Journal of Computer Science, Vol. 22, Issue 6 · 3 Jun 2026 · 1,528 accessesView PDFCite
Research ArticleOpen accessIn the abstractCuckoo Search Optimized Random Forest for Breast Cancer PrognosisPrasad S. Sase, Debabrata Swain, Shailesh KumarBreast cancer remains a major global health concern due to its high mortality rate, particularly when diagnosis occurs at an advanced stage. Accurate and early differentiation between benign and malignant tumors is therefore critical for improving patient outcomes. Conventional diagnostic practices largely depend on manual assessment and clinical expertise, which may lead to subjective variability in decision-making. To overcome this … …Journal of Computer Science, Vol. 22, Issue 1 · 31 Jan 2026 · 2,098 accessesView PDFCite
Review ArticleOpen accessIn the abstractUnveiling Skin Cancer: A Review of Deep Learning Techniques for DetectionGoutham Lal Shanmughamadom Harilal, Tamilselvi PanneerselvamEarly identification is essential for successful treatment and better patient outcomes since skin cancer is caused by damage to DNA in skin cells, which can result in genetic abnormalities and the possibility of metastasis. The present systematic review scrutinizes the efficacy and obstacles of early detection techniques, which differentiate between benign and malignant lesions by examining lesion attributes such as … …Journal of Computer Science, Vol. 21, Issue 9 · 23 Oct 2025 · 2,602 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrevalence and Histopathologic Analyses of Mammary Tumors in Female Dogs in the Northeast of AlgeriaZahra GABLI, Leila BEDDAR, Amir Agabou et al.Cancers development and complications are a major cause of death in dogs all over the world. The current study attempts to describe the prevalence and anatomo-pathologic traits of mammary gland tumors (MGTs) in bitches in northeast Algeria. From November 2013 to April 2016, a total of 215 bitches originating from four provinces (Constantine, Oum El Bouaghi, Annaba and Skikda) were … …OnLine Journal of Biological Sciences, Vol. 17, Issue 3 · 26 Sep 2017 · 7,546 accessesView PDFCite
Research ArticleOpen accessIn the abstractCLASSIFICATION OF MICROCALCIFICATION BASED ON WAVE ATOM TRANSFORMA. Rajesh, Mohan EllappanBreast cancer is a serious problem for women in the world. It is the most common form of cancer diagnosed in woman, with one in nine women expected to be diagnosed with some form of cancer in their life-time. It is second only to lung cancer in cancer related deaths. Statistics shows that the case of breast cancer in the … …Journal of Computer Science, Vol. 10, Issue 8 · 5 Apr 2014 · 6,517 accessesView PDFCite
Research ArticleOpen accessIn the abstractMass Classification in Digital Mammograms based on Discrete Shearlet TransformJ. Amjath Ali, J. JanetThe most significant health problem in the world is breast cancer and early detection is the key to predict it. Mammography is the most reliable method to diagnose breast cancer at the earliest. The classification of the two most findings in the digital mammograms, micro calcifications and mass are valuable for early detection. Since, the appearance of the masses are … …Journal of Computer Science, Vol. 9, Issue 6 · 1 Jun 2013 · 6,549 accessesView PDFCite
Research ArticleOpen accessIn the abstractNovel Fuzzy Technique for Cancer Detection in Noisy Breast Ultrasound ImagesN. Alamelumangai, J. DeviShreeProblem statement: Detecting tumor areas in breast Ultrasound (US) images is a challenging task. The occurrence of benign areas in breast may result in false identification of malignant areas which may have serious outcome. Approach: The CAD system could act as a major function in the early detection of breast cancer and could decrease the death rate among women with … …American Journal of Applied Sciences, Vol. 9, Issue 5 · 12 Mar 2012 · 6,959 accessesView PDFCite