Related papers: Breast shape estimation and correction in CESM bio…
In the case of breast cancer, as with most cancers, early detection can significantly improve a person's chances of survival. This makes it important for there to be an effective and accessible means of regularly checking for manifestations…
Computer-aided detection systems based on deep learning have shown good performance in breast cancer detection. However, high-density breasts show poorer detection performance since dense tissues can mask or even simulate masses. Therefore,…
Accurate identification of breast cancer types plays a critical role in guiding treatment decisions and improving patient outcomes. This paper presents an artificial intelligence enabled tool designed to aid in the identification of breast…
Objective: To develop an automatic image normalization algorithm for intensity correction of images from breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) acquired by different MRI scanners with various imaging…
A biopsy is the only diagnostic procedure for accurate histological confirmation of breast cancer. When sonographic placement is not feasible, a Magnetic Resonance Imaging(MRI)-guided biopsy is often preferred. The lack of real-time imaging…
Breast cancer ranks as the most prevalent form of cancer diagnosed in women, and diagnosis faces several challenges, a change in the size, shape and appearance of breasts, dense breast tissue, lumps or thickening in the breast especially if…
This paper presents a tumor detection algorithm from mammogram. The proposed system focuses on the solution of two problems. One is how to detect tumors as suspicious regions with a very weak contrast to their background and another is how…
Convolutional Neural Networks (CNN) have had a huge success in many areas of computer vision and medical image analysis. However, there is still an immense potential for performance improvement in mammogram breast cancer detection…
Knowledge of x-ray attenuation is essential for developing and evaluating x-ray imaging technologies. For instance, techniques to distinguish between cysts and solid tumours at mammography screening would be highly desirable to reduce…
Breast cancer is one of the most common cancers among women worldwide, with early detection significantly increasing survival rates. Ultrasound imaging is a critical diagnostic tool that aids in early detection by providing real-time…
In this paper, we would like to quantitatively measure the tumor volume contained in the breast imaged by the Digital Breast Tomosynthesis (DBT), a reconstructed 3D image. The estimated volume will add to the prognostic value of risk…
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is essential for breast cancer diagnosis due to its ability to characterize tissue through contrast agent kinetics. However, traditional DCE-MRI protocols require multiple…
Deep learning object detection algorithm has been widely used in medical image analysis. Currently all the object detection tasks are based on the data annotated with object classes and their bounding boxes. On the other hand, medical…
Accurate diagnosis of breast cancer in histopathology images is challenging due to the heterogeneity of cancer cell growth as well as of a variety of benign breast tissue proliferative lesions. In this paper, we propose a practical and…
Background and Objective: Accurate detection of breast masses in mammography images is critical to diagnose early breast cancer, which can greatly improve the patients survival rate. However, it is still a big challenge due to the…
Morphological features play an important role in breast mass classification in sonography. While benign breast masses tend to have a well-defined ellipsoidal contour, shape of malignant breast masses is commonly ill-defined and highly…
Objective: In this work, we perform margin assessment of human breast tissue from optical coherence tomography (OCT) images using deep neural networks (DNNs). This work simulates an intraoperative setting for breast cancer lumpectomy.…
Mammographic breast density is a well-established risk factor for breast cancer. Recently there has been interest in breast MRI as an adjunct to mammography, as this modality provides an orthogonal and highly quantitative assessment of…
A well-known diagnostic imaging modality, termed ultrasound tomography, was quickly developed for the detection of very small tumors whose sizes are smaller than the wavelength of the incident pressure wave without ionizing radiation,…
The clinical management of breast cancer depends on an accurate understanding of the tumor and its anatomical context to adjacent tissues and landmark structures. This context may be provided by semantic segmentation methods; however,…