Using Machine Learning to Automate Mammogram Images Analysis [PDF]
IEEE International Conference on Bioinformatics and Biomedicine, 2020 Breast cancer is the second leading cause of cancer-related death after lung cancer in women. Early detection of breast cancer in X-ray mammography is believed to have effectively reduced the mortality rate since 1989.
Xuejiao Tang +8 more
semanticscholar +1 more source
Mammographic Diagnosis of Breast Carcinoma: An Institutional Experience
Journal of Nepal Medical Association, 2008 Mammogram is a common diagnostic modality for breast carcinoma. Diagnostic mammogram is available at only few centers in Nepal. The aim of this study was to determine the accuracy of diagnostic mammogram in Nepalese women suffering from breast carcinoma.
Dr Sidharth +4 more
doaj +1 more source
Journal of Cancer and Allied Specialties, 2018 Purpose: The purpose of this study was to detect diagnostic accuracy of mammography and ultrasound combined versus ultrasound alone in early evaluation of symptomatic breast lesions.
Razia Bano +5 more
doaj +1 more source
Multicriteria Evaluation of Deep Neural Networks for Semantic Segmentation of Mammographies
Axioms, 2021 Breast segmentation plays a vital role in the automatic analysis of mammograms. Accurate segmentation of the breast region increments the probability of a correct diagnostic and minimizes computational cost.
Yoshio Rubio, Oscar Montiel
doaj +1 more source
A hybrid de-noising method for mammogram images
, 2021 In general, mammogram images contaminated with noise which directly affect images quality. Several methods have been proposed to de-noise these images, however, there is always a risk of losing valuable information.
Saima Anwar Lashari +5 more
semanticscholar +1 more source
A scalable Computer-Aided Detection system for microcalcification cluster identification in a pan-European distributed database of mammograms [PDF]
, 2006 A computer-aided detection (CADe) system for microcalcification cluster identification in mammograms has been developed in the framework of the EU-founded MammoGrid project.
A. Preite Martinez +17 more
core +1 more source
Turnaround times in breast cancer: From screening to diagnosis to treatment
Journal of Acute Disease, 2013 Objective: To compare our institution with national benchmark times, and identify rate-limiting steps in the process by conducte a retrospective review of the turnaround times in 2009 at the Carilion Clinic Breast Care Center (CCBCC). To evaluate patient
Kaylene J Logan +3 more
doaj +1 more source
A roadside units positioning framework in the context of vehicle-to-infrastructure based on integrated AHP-entropy and group-VIKOR [PDF]
, 2021 The positioning of roadside units (RSUs) in a vehicle-to-infrastructure (V2I) communication system may have an impact on network performance. Optimal RSU positioning is required to reduce cost and maintain the quality of service. However, RSU positioning
Malik, Rami Qays
core
Imaging Characteristics of Breast Lymphoma; a Case Series
Journal of Cancer and Allied Specialties, 2020 Introduction: Breast involvement by lymphoma is rare. It can occur as a primary breast tumour or as an extranodal manifestation of the systemic disease. The imaging features of breast lymphoma (BL) are not characteristic.
Sara Rehman +2 more
doaj +1 more source
Deep Multi-instance Networks with Sparse Label Assignment for Whole Mammogram Classification [PDF]
bioRxiv, 2016 Mammogram classification is directly related to computer-aided diagnosis of breast cancer. Traditional methods requires great effort to annotate the training data by costly manual labeling and specialized computational models to detect these annotations ...
Wentao Zhu +3 more
semanticscholar +1 more source