Mass Detection on Automated Breast Ultrasound Volume Scans Using Convolutional Neural Network

被引：0

作者：

Muramatsu, Chisako ^{[1
]}

Hiramatsu, Yuya ^{[1
]}

Fujita, Hiroshi ^{[1
]}

Kobayashi, Hironobu ^{[2
]}

机构：

[1] Gifu Univ, Dept Elect Elect & Comp Engn, Gifu, Japan

[2] Nagoya Cent Hosp, Dept Breast & Endocrine Surg, Nagoya, Aichi, Japan

来源：

2018 INTERNATIONAL WORKSHOP ON ADVANCED IMAGE TECHNOLOGY (IWAIT) | 2018年

基金：

日本学术振兴会;

关键词：

breast masses; automated ultrasound volume scans; detection; convolutional neural network;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Automated ultrasound volume scan is useful for screening breast cancer as it records the whole breast data allowing longitudinal comparisons and double reading. Unlike examinations with handheld probes, it is less operator independent. However, the number of acquired images is large, which increases radiologists' workload. In this study, we propose a mass detection method on ultrasound volume scans using convolutional neural network (CNN). Using CNN, detection performance greatly improved compared with the conventional filter based method.

引用

页数：2

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