In this paper, we present a two-stage algorithm for mammogram registration, the geometrical alignment of mammogram sequences. The rationale behind this paper stems from the intrinsic difficulties in comparing mammogram sequences. Mammogram comparison is a valuable tool in national breast screening programs as well as in frequent monitoring and hormone replacement therapy (HRT). The method presented in this paper aims to improve mammogram comparison by estimating the underlying geometric transformation for any mammogram sequence. It takes into consideration the various temporal changes that may occur between successive scans of the same woman and is designed to overcome the inconsistencies of mammogram image formation.
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http://dx.doi.org/10.1109/TMI.2005.848374 | DOI Listing |
Front Immunol
December 2024
Third Hospital of Shanxi Medical University, Shanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Tongji Shanxi Hospital, Taiyuan, China.
Objective: To explore the value of combined radiomics and deep learning models using different machine learning algorithms based on mammography (MG) and magnetic resonance imaging (MRI) for predicting axillary lymph node metastasis (ALNM) in breast cancer (BC). The objective is to provide guidance for developing scientifically individualized treatment plans, assessing prognosis, and planning preoperative interventions.
Methods: A retrospective analysis was conducted on clinical and imaging data from 270 patients with BC confirmed by surgical pathology at the Third Hospital of Shanxi Medical University between November 2022 and April 2024.
Ther Adv Med Oncol
December 2024
Clinic for Gynecology and Obstetrics, University Hospital RWTH Aachen, Aachen, Germany.
Background And Objectives: Breast cancer is the most common cancer in women, with one in eight women suffering from this disease in her lifetime. The implementation of centrally organized mammography screening for women between 50 and 69 years of age was a major step in the direction of early detection. However, the participation rate reaches approximately 50% of the eligible women, one reason being the painful compression of the breast, cited as a major issue for not participating in this very important program.
View Article and Find Full Text PDFGenet Med Open
November 2023
Prevent Breast Cancer Centre, Wythenshawe Hospital Manchester Universities Foundation Trust, Wythenshawe, Manchester, United Kingdom.
Purpose: To assess the contribution of germline pathogenic variants (PVs) in population-based series of breast cancers and the best strategy to improve detection rates.
Methods: Three cohort studies were utilized, including a hospital-based series identified from new UK mainstream testing criteria (group-1), offering testing to all women (group-2-BReast CAncer [BRCA]-DIRECT), and a Greater Manchester cohort study recruited from the mammography screening population (group-3-Predicting Risk of Cancer at Screening). DNA samples from women with breast cancer were sequenced for PVs in , , and Partner and Localiser of BRCA2 ().
Clin Epigenetics
November 2024
Institute for Molecular Medicine Finland (FIMM), HiLIFE, University of Helsinki, Tukholmankatu 8, 00290, Helsinki, Finland.
Background: Assessment of breast cancer (BC) risk generally relies on mammography, family history, reproductive history, and genotyping of major mutations. However, assessing the impact of environmental factors, such as lifestyle, health-related behavior, or external exposures, is still challenging. DNA methylation (DNAm), capturing both genetic and environmental effects, presents a promising opportunity.
View Article and Find Full Text PDFRadiology
November 2024
From the Department of Psychological and Brain Sciences, University of California-Santa Barbara, Santa Barbara, Calif (C.K.A.); Department of Biostatistics, University of Pittsburgh, Pittsburgh, Pa (A.I.B.); Department of Radiology, University of Pittsburgh Medical Center, Magee-Womens Hospital, 300 Halket St, Pittsburgh, PA 15213 (A.I.B., M.L.Z.); and Department of Psychology, University of Nevada-Reno, Reno, Nev (M.K.P., M.A.W.).
Background Studies suggest that readers experience perceptual adaptation when interpreting batched screening mammograms, which may serve as a mechanism for improved performance. Purpose To analyze clinical digital breast tomosynthesis (DBT) screening data to evaluate changes in reader performance during sequential batch reading. Materials and Methods This observational retrospective study used data from the radiology information system collected for screening DBT examinations performed from January 2018 to December 2019.
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