We propose a framework for localization and classification of masses in breast ultrasound
images. We have experimentally found that training convolutional neural network-based …

Deep learning methods, especially convolutional neural networks, have advanced the
breast lesion classification task using breast ultrasound (BUS) images. However …

This paper summarizes the presentations given in the special ICMB2010 session on state-of-
the-art of computer-aided detection/diagnosis (CAD). The topics are concerned with the …

Automated breast ultrasound (ABUS) is a three-dimensional (3D) imaging technique with
accelerating importance for breast cancer screening and diagnostic imaging in …

Breast cancer is the second leading cause of death after lung cancer in women all over the
world. The survival rate of breast cancer patients depends on the stage of diagnosis; …

Ultrasound is one of the most frequently used methods for early detection of breast cancer.
Currently, the accuracy of Computer Aided Diagnosis (CAD) systems based on ultrasound …

In this paper, we propose a statistical temporal change scheme for early breast cancer
detection. Temporal mammographic data have been found useful to detect changes in the …

The aim of this paper is to investigate a 2.5-dimensional approach in classifying masses as
benign or malignant in volumetric anisotropic voxel whole breast ultrasound data. In this …

抄録 The need for utilizing image diagnosis has become important because of the recent
increase in the number of screening cases in the aging population and the number of …