This work analyzes the influence of the set of mammograms used in the training processes of a computer aided diagnosis system on the overall performance. We used the mammograms provided by the Digital Database for Screening Mammography, one of the most extended research database. The obtained results seem to suggest an effect on the performance values obtained in a CAD system with different database subsets. Therefore, in order to make valid comparisons between CAD systems, the specification of the mammogram set used to test the system is of the utmost importance.
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http://dx.doi.org/10.1109/IEMBS.2008.4650281 | DOI Listing |
Appl Radiat Isot
January 2025
School of Artificial Intelligence, Wenzhou Polytechnic, Wenzhou, 325035, China. Electronic address:
For the purpose of assessing image quality and calculating patient X-ray dosage in radiology, computed tomography (CT), fluoroscopy, mammography, and other fields, it is necessary to have prior knowledge of the X-ray energy spectrum. The main components of an X-ray tube are an electron filament, also known as the cathode, and an anode, which is often made of tungsten or rubidium and angled at a certain angle. At the point where the electrons generated by the cathode and the anode make contact, a spectrum of X-rays with energies spanning from zero to the maximum energy value of the released electrons is created.
View Article and Find Full Text PDFAcad Radiol
January 2025
Department of Bioengineering, University of Pittsburgh, Pittsburgh, PA 15213 (C.L., S.W.); Department of Radiology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15213 (D.A., M.Z., J.S., S.W.); Department of Biomedical Informatics, University of Pittsburgh, Pittsburgh, PA 15213 (S.W.); Intelligent Systems Program, University of Pittsburgh, Pittsburgh, PA 15213 (S.W.). Electronic address:
Rationale And Objectives: In the USA over 1 million breast biopsies are performed annually. Approximately 9.6% diagnostic exams were given Breast Imaging Reporting and Data System (BI-RADS) ≥4A, most of which are 4A/4B.
View Article and Find Full Text PDFEur J Radiol
January 2025
Department of Radiology, Affiliated Hospital of Jiangnan University, Wuxi City, Jiangsu Province 214062, China. Electronic address:
Purpose: To construct a nomogram combining Kaiser score (KS), synthetic MRI (syMRI) parameters, apparent diffusion coefficient (ADC), and clinical features to distinguish benign and malignant breast lesions better.
Methods: From December 2022 to February 2024, a retrospective cohort of 168 patients with breast lesions diagnosed as Breast Imaging Reporting and Data System (BI-RADS) category 4 by ultrasound and/or mammography was included. The research population was divided into the training set (n = 117) and the validation set (n = 51) by random sampling with a ratio of 7:3.
Front Oncol
December 2024
Newcastle Magnetic Resonance Centre, Translational and Clinical Research Institute, Faculty of Medical Sciences, Newcastle University, Newcastle, United Kingdom.
Introduction: Ductal carcinoma (DCIS) accounts for 25% of newly diagnosed breast cancer cases with only 14%-53% developing into invasive ductal carcinoma (IDC), but currently overtreated due to inadequate accuracy of mammography. Subtypes of calcification, discernible from histology, has been suggested to have prognostic value in DCIS, while the lipid composition of saturated and unsaturated fatty acids may be altered in synthesis with potential sensitivity to the difference between DCIS and IDC. We therefore set out to examine calcification using ultra short echo time (UTE) MRI and lipid composition using chemical shift-encoded imaging (CSEI), as markers for histological calcification classification, in the initial step towards application.
View Article and Find Full Text PDFFront 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.
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