Improving Mass Detection in Mammography Images: A Study of Weakly Supervised Learning and Class Activation Map Methods [PDF]
arXiv, 2023 In recent years, weakly supervised models have aided in mass detection using mammography images, decreasing the need for pixel-level annotations. However, most existing models in the literature rely on Class Activation Maps (CAM) as the activation method, overlooking the potential benefits of exploring other activation techniques.
arxiv
Does mammographic screening and a negative result affect attitudes towards future breast screening? [PDF]
, 2001 OBJECTIVES:To investigate the impact of an experience of a benign mammographic result on intention to seek medical help immediately in the case of breast abnormalities, and on intentions and thoughts about future participation in screening.
Boer, H. +2 more
core +4 more sources
Physical and technical aspects of quality assurance in mammography in the Republic of Srpska [PDF]
Nuclear Technology and Radiation Protection, 2011 Breast cancer is the most frequent malignant neoplasm affecting the female population. In order to reduce its morbidity and mortality rate, a mammography screening campaign has been established in both entities of Bosnia and Herzegovina. In this paper,
Ciraj-Bjelac Olivera F. +3 more
doaj +1 more source
Frontiers in Oncology, 2021 ObjectiveTo build radiomics models using features extracted from DCE-MRI and mammography for diagnosis of breast cancer.Materials and Methods266 patients receiving MRI and mammography, who had well-enhanced lesions on MRI and histologically confirmed ...
You-Fan Zhao +12 more
doaj +1 more source
A New Computer-Aided Diagnosis System with Modified Genetic Feature Selection for BI-RADS Classification of Breast Masses in Mammograms [PDF]
, 2020 Mammography remains the most prevalent imaging tool for early breast cancer screening. The language used to describe abnormalities in mammographic reports is based on the breast Imaging Reporting and Data System (BI-RADS). Assigning a correct BI-RADS category to each examined mammogram is a strenuous and challenging task for even experts.
arxiv +1 more source
Quantum medical images processing foundations and applications
IET Quantum Communication, Volume 3, Issue 4, Page 201-213, December 2022., 2022 Abstract Medical imaging is considered one of the most important areas within scientific imaging due to the rapid and ongoing development in computer‐aided medical image visualisation, advances in analysis approaches, and computer‐aided diagnosis.
Ahmed Elaraby
wiley +1 more source
Supervised Machine Learning Algorithm for Detecting Consistency between Reported Findings and the Conclusions of Mammography Reports [PDF]
arXiv, 2022 Objective. Mammography reports document the diagnosis of patients' conditions. However, many reports contain non-standard terms (non-BI-RADS descriptors) and incomplete statements, which can lead to conclusions that are not well-supported by the reported findings.
arxiv
Cancer Medicine, 2020 Background Mammography use is affected by multiple factors that may change as public health interventions are implemented. We examined two nationally representative, population‐based surveys to seek consensus and identify inconsistencies in factors ...
Lihua Li +8 more
doaj +1 more source
A comparative study of the diagnostic value of contrast-enhanced breast MR imaging and mammography on patients with BI-RADS 3-5 microcalcifications. [PDF]
PLoS ONE, 2014 OBJECTIVE: To retrospectively investigate the diagnostic value of breast MRI in patients with BI-RADS 3-5 microcalcifications in mammography. METHODS: Eighty-four patients with BI-RADS 3-5 microcalcifications on mammography underwent breast MR exams ...
Erni Li +4 more
doaj +1 more source
M&M: Tackling False Positives in Mammography with a Multi-view and Multi-instance Learning Sparse Detector [PDF]
arXiv, 2023 Deep-learning-based object detection methods show promise for improving screening mammography, but high rates of false positives can hinder their effectiveness in clinical practice. To reduce false positives, we identify three challenges: (1) unlike natural images, a malignant mammogram typically contains only one malignant finding; (2) mammography ...
arxiv