AIMC Topic: Breast

Clear Filters Showing 261 to 270 of 627 articles

Deep learning for image classification in dedicated breast positron emission tomography (dbPET).

Annals of nuclear medicine
OBJECTIVE: This study aimed to investigate and determine the best deep learning (DL) model to predict breast cancer (BC) with dedicated breast positron emission tomography (dbPET) images.

Breast lesions classifications of mammographic images using a deep convolutional neural network-based approach.

PloS one
Breast cancer is one of the worst illnesses, with a higher fatality rate among women globally. Breast cancer detection needs accurate mammography interpretation and analysis, which is challenging for radiologists owing to the intricate anatomy of the...

Two-phase learning-based 3D deblurring method for digital breast tomosynthesis images.

PloS one
In digital breast tomosynthesis (DBT) systems, projection data are acquired from a limited number of angles. Consequently, the reconstructed images contain severe blurring artifacts that might heavily degrade the DBT image quality and cause difficult...

Breast Cancer Classification from Ultrasound Images Using Probability-Based Optimal Deep Learning Feature Fusion.

Sensors (Basel, Switzerland)
After lung cancer, breast cancer is the second leading cause of death in women. If breast cancer is detected early, mortality rates in women can be reduced. Because manual breast cancer diagnosis takes a long time, an automated system is required for...

Characterizing breast masses using an integrative framework of machine learning and CEUS-based radiomics.

Journal of ultrasound
AIMS: We evaluated the performance of contrast-enhanced ultrasound (CEUS) based on radiomics analysis to distinguish benign from malignant breast masses.

Multimodal Imaging of Target Detection Algorithm under Artificial Intelligence in the Diagnosis of Early Breast Cancer.

Journal of healthcare engineering
This study aimed to analyze the diagnostic value of multimodal images based on artificial intelligence target detection algorithms for early breast cancer, so as to provide help for clinical imaging examinations of breast cancer. This article combine...

Artificial intelligence for breast cancer analysis: Trends & directions.

Computers in biology and medicine
Breast cancer is one of the leading causes of death among women. Early detection of breast cancer can significantly improve the lives of millions of women across the globe. Given importance of finding solution/framework for early detection and diagno...

Deep Learning Using Multiple Degrees of Maximum-Intensity Projection for PET/CT Image Classification in Breast Cancer.

Tomography (Ann Arbor, Mich.)
Deep learning (DL) has become a remarkably powerful tool for image processing recently. However, the usefulness of DL in positron emission tomography (PET)/computed tomography (CT) for breast cancer (BC) has been insufficiently studied. This study in...

Breast Tumor Detection and Classification in Mammogram Images Using Modified YOLOv5 Network.

Computational and mathematical methods in medicine
Breast cancer incidence has been rising steadily during the past few decades. It is the second leading cause of death in women. If it is diagnosed early, there is a good possibility of recovery. Mammography is proven to be an excellent screening tech...

Updates in Artificial Intelligence for Breast Imaging.

Seminars in roentgenology
Artificial intelligence (AI) for breast imaging has rapidly moved from the experimental to implementation phase. As of this writing, Food and Drug Administration (FDA)-approved mammographic applications are available for triage, lesion detection and ...