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Enhancing diagnostic accuracy in breast cancer: integrating novel machine learning approaches with enhanced image preprocessing for improved mammography analysis.
Pol J Radiol
December 2024
Nuclear Fuel Research School, Nuclear Science and Technology Research Institute, Tehran, Iran.
Purpose: This study explored the use of computer-aided diagnosis (CAD) systems to enhance mammography image quality and identify potentially suspicious areas, because mammography is the primary method for breast cancer screening. The primary aim was to find the best combination of preprocessing algorithms to enable more precise classification and interpretation of mammography images because the selected preprocessing algorithms significantly impact the effectiveness of later classification and segmentation processes.
Material And Methods: The study utilised the mini-MIAS database of mammography images and examined the impact of applying various preprocessing method combinations to differentiate between malignant and benign breast lesions.
Primary breast osteosarcoma: A case report highlighting the importance of radiologic-pathologic correlation.
Radiol Case Rep
March 2025
Department of Radiology, Sanford USD Medical Center, Sioux Falls, SD, USA.
Osteosarcoma of primary breast origin is a rare form of malignancy. Imaging findings are nonspecific and often overlap with other differential considerations reinforcing the importance of radiologic-pathologic correlation for an accurate diagnosis. This case report details the clinical presentation, imaging findings, histopathological features, and therapeutic approach that transpired to diagnose and treat this rare malignancy.
View Article and Find Full Text PDF[Personalized profiling in the field of senology].
Radiologie (Heidelb)
January 2025
Universitätsklinikum Erlangen, Frauenklinik, Comprehensive Cancer Center Erlangen-EMN (CCC ER-EMN), Friedrich-Alexander-Universität Erlangen-Nürnberg, Universitätsstraße 21-23, 91054, Erlangen, Deutschland.
Background: The concept of personalized medicine is becoming increasingly important. The possibilities of diagnostics include not only genetic and molecular tumor profiles, but also the use of precise and individual imaging techniques.
Objectives: The development and implementation of suitable diagnostic procedures with high sensitivity and specificity, which are at the same time tailored to the individual risk factors and biological characteristics of the patient, remain a challenge.
Comparison of AAPM TG282 and Dance breast dosimetry models: Impact on estimates of average MGD for the United Kingdom breast screening programmes.
Phys Med
January 2025
National Co-ordinating Centre for the Physics of Mammography (NCCPM), Medical Physics Department, Royal Surrey NHS Foundation Trust, Guildford GU2 7XX UK.
Background: The American Association of Physicists in Medicine (AAPM) Task group 282 (TG282) in collaboration with the European Federation for Organisations of Medical Physics (EFOMP) have developed a novel breast dosimetry model intended as a single international standard.
Purpose: To explore the impact of TG282 dosimetry on estimates of average Mean Glandular Dose (MGD) in the United Kingdom (UK) National Health Service (NHS) Breast Screening Programmes (BSP).
Methods: MGDs were estimated, using the TG282 dosimetry model, for the most recent UK NHSBSP dose survey.
Classifying the molecular subtype of breast cancer using vision transformer and convolutional neural network features.
Breast Cancer Res Treat
January 2025
Department of Radiological Technology, Faculty of Medical Technology, Niigata University of Health and Welfare, 1398 Shimamichou, Kita-Ku, Niigata, Japan.
Purpose: Identification of the molecular subtypes in breast cancer allows to optimize treatment strategies, but usually requires invasive needle biopsy. Recently, non-invasive imaging has emerged as promising means to classify them. Magnetic resonance imaging is often used for this purpose because it is three-dimensional and highly informative.
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