15 results for “Computer Aided Diagnosis (CAD)”

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Research ArticleOpen accessIn the abstractNovel Preprocessing Technique in the Computer Aided Detection of Breast CancerSenthilkumar Balasubramaniam, Umamaheswari GovindaswamyAnalyzing medical images is the most challenging task in medical image processing. Computer Aided Detection (CAD) tool is the aid for the radiologists in analyzing such images for the effective detection and diagnosis of the disease. Such a CAD tool consists of Preprocessing, Segmentation and detection processes. In this study we have improved the preprocessing by using the Selective Median … …Journal of Computer Science, Vol. 8, Issue 12 · 8 Nov 2012 · 6,650 accessesView PDF Cite

Research ArticleOpen accessIn the abstractMammogram Analysis Based on Pixel Intensity Mean FeaturesR. Nithya, B. SanthiProblem statement: In the recent years, Computer Aided Diagnosis (CAD) can be very useful for detection of breast cancer. Mammography can be used as an efficient tool for breast cancer diagnosis. A computer based diagnosis and classification system can reduce unnecessary biopsy. Approach: This study investigates a new approach to the classification of mammogram images based on pixel intensity mean … …Journal of Computer Science, Vol. 8, Issue 3 · 7 Jan 2012 · 7,666 accessesView PDF Cite

Research ArticleOpen accessIn the abstractEfficient Technique to Detect the Region of Interests in Mammogram ImagesMoussa H. Abdallah, Ayman A. AbuBaker, Rami S. Qahwaji, Mohammed H. SalehProblem Statement: Breast cancer is the second leading cause of cancer deaths in women today after lung cancer and is the most common cancer among women. The development of efficient technique to early detect the region of microcalcifications mammogram images is a must. Approach: The method proposed in this paper is to enhance the Computer Aided Diagnosis (CAD) performance. This … …Journal of Computer Science, Vol. 4, Issue 8 · 31 Aug 2008 · 6,629 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordA Metaheuristic-Optimized Feature Selection for Early-Stage Diabetes Prediction With SHAP-Guided Insight into Inﬂuential AttributesEsmay Azam Rochy, Jannatul Ferdaus, Uzzal Biswas et al.Diabetes is a metabolic disorder that causes elevated blood glucose. This long-term health condition can lead to cardiovascular diseases, stroke, kidney failure, visual impairment, neuropathy, and even death in critical cases. So, a Computer-Aided Diagnostic (CAD) system is necessary to diagnose diabetes automatically. A clinician can utilize a machine learning-based CAD system that automatically diagnoses many people. This paper will … …Journal of Computer Science, Vol. 22, Issue 2 · 24 Feb 2026 · 1,736 accessesView PDF Cite

Research ArticleOpen accessAll words, across the recordOptiCNN: Local thresholding segmentation and CNN with SVM Approach for Diabetic Retinopathy Detection and Classification of Fundus ImagesAnju Mishra, Mrinal Pandey, Laxman SinghDiabetic Retinopathy (DR) is a progressive eye disease that can lead to vision loss and blindness if left untreated. Ophthalmologists diagnose DR using medical imaging modalities such as fundus photography and optical coherence tomography (OCT); however, manual interpretation of these images is time-consuming and subject to inter-observer variability. While DR is irreversible, vision loss can be prevented through early detection … …Journal of Computer Science, Vol. 21, Issue 10 · 15 Dec 2025 · 2,153 accessesView PDF Cite