Development of a Computer-aided Diagnosis System to Distinguish between Benign and Malignant Mammary Tumors in Dynamic Magnetic Resonance Images: Automatic Detection of the Position with the Strongest Washout Effect in the Tumor

DOI Web Site Web Site PubMed 11 References
  • Miyazaki Yoshiaki
    Department of Radiological Technology, National Hospital Organization Kyushu Cancer Center
  • Tabata Nobuyuki
    Department of Radiological Technology, National Hospital Organization Kyushu Cancer Center
  • Taroura Tomomi
    Department of Radiological Technology, National Hospital Organization Kyushu Cancer Center
  • Shinozaki Kenji
    Department of Diagnostic Radiology, National Hospital Organization Kyushu Cancer Center
  • Kubo Yuichiro
    Department of Diagnostic Radiology, National Hospital Organization Kyushu Cancer Center
  • Tokunaga Eriko
    Department of Breast Surgery, National Hospital Organization Kyushu Cancer Center
  • Taguchi Kenichi
    Department of Diagnostic Pathology, National Hospital Organization Kyushu Cancer Center

Bibliographic Information

Other Title
  • Dynamic MR 画像における乳腺腫瘍良悪性判定のためのコンピュータ支援診断システムの開発─腫瘍内washout 部分の自動検出─
  • Dynamic MR画像における乳腺腫瘍良悪性判定のためのコンピュータ支援診断システムの開発 : 腫瘍内washout部分の自動検出
  • Dynamic MR ガゾウ ニ オケル ニュウセン シュヨウ リョウ アクセイ ハンテイ ノ タメ ノ コンピュータ シエン シンダン システム ノ カイハツ : シュヨウ ナイ washout ブブン ノ ジドウ ケンシュツ

Search this article

Abstract

<p>We propose a computer-aided diagnostic (CAD) system that uses time-intensity curves to distinguish between benign and malignant mammary tumors. Many malignant tumors show a washout pattern in time-intensity curves. Therefore, we designed a program that automatically detects the position with the strongest washout effect using the technique, such as the subtraction technique, which extracts only the washout area in the tumor, and by scanning data in 2×2 pixel region of interest (ROI). Operation of this independently developed program was verified using a phantom system that simulated tumors. In three cases of malignant tumors, the washout pattern detection rate in images with manually set ROI was ≤6%, whereas the detection rate with our novel method was 100%. In one case of a benign tumor, when the same method was used, we checked that there was no washout effect and detected the persistent pattern. Thus, the distinction between benign and malignant tumors using our method was completely consistent with the pathological diagnoses made. Our novel method is therefore effective for differentiating between benign and malignant mammary tumors in dynamic magnetic resonance images.</p>

Journal

References(11)*help

See more

Keywords

Details 詳細情報について

Report a problem

Back to top