Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039861
Automatic segmentation in Breast Ultrasound (BUS) imaging is vital to BUS computer-aided diagnostic systems. Fully supervised learning approaches can attain high accuracy, yet they depend on pixel-level annotations that are challenging to obtain. As ...
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
40039274
Automatic breast tumor ultrasound segmentation is one of the most critical components in the development of tools for breast cancer diagnosis. Several deep learning algorithms have been tested with public and private datasets but none of them has bee...
Technology in cancer research & treatment
40241520
IntroductionThe study aims to evaluate the performance of an interpretable machine learning model in predicting preoperative axillary lymph node metastasis using primary breast cancer and lymph node features derived from contrast-enhanced mammography...
Accurate segmentation of nodules in both 2D breast ultrasound (BUS) and 3D automated breast ultrasound (ABUS) is crucial for clinical diagnosis and treatment planning. Therefore, developing an automated system for nodule segmentation can enhance user...
Applying deep learning algorithms to mine ultrasound features of breast cancer and construct a machine learning model that accurately predicts Ki-67 expression level. This multi-center retrospective study analyzed clinical and ultrasound data from 92...
Breast cancer is the most prevalent cancer and the second cause of cancer related death among women in the United States. Accurate and early detection of breast cancer can reduce the number of mortalities. Recent works explore deep learning technique...
To investigate the potential of employing artificial intelligence (AI) -driven breast ultrasound analysis models for the classification of glandular tissue components (GTC) in dense breast tissue. A total of 1,848 healthy women with mammograms classi...
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
40184647
PURPOSE: Breast cancer remains a significant cause of mortality among women globally, highlighting the critical need for accurate diagnosis. Although Convolutional Neural Networks (CNNs) have shown effectiveness in segmenting breast ultrasound images...
Cancer imaging : the official publication of the International Cancer Imaging Society
40340752
OBJECTIVE: Phyllodes tumors (PTs) are rare breast tumors with high recurrence rates, current methods relying on post-resection pathology often delay detection and require further surgery. We propose a deep-learning-based Phyllodes Tumors Hierarchical...
BACKGROUND: This study aimed to develop a BI-RADS network (DL-UM) via integrating ultrasound (US) and mammography (MG) images and explore its performance in improving breast lesion diagnosis and management when collaborating with radiologists, partic...