| 大会名称 |
|---|
| 2016年 情報科学技術フォーラム(FIT) |
| 大会コ－ド |
| F |
| 開催年 |
| 2016 |
| 発行日 |
| 2016-08-23 |
| セッション番号 |
| 4F |
| セッション名 |
| 医用画像 |
| 講演日 |
| 2016/09/08 |
| 講演場所(会議室等) |
| 共通教育棟E棟4階E43 |
| 講演番号 |
| G-008 |
| タイトル |
| Automatic Mass Detection for Breast Cancer from Mammography with Texture Analysis Technique and Statistical features |
| 著者名 |
| Somchanok Tivatansakul, Keiichi Uchimura, |
| キーワード |
| Breast mass detection, Texture Analysis, Gray-level co-occurrence matrix, Statistical features, Mammography images |
| 抄録 |
| This study focuses on precise detection of mass boundary from mammography. We apply gray-level co-occurrence matrix (GLCM) with statistical features. We also improve it using preprocessing and GLCM iteration to distinguish, remove and detect mass regions from other breast areas. The evaluation results with a mini-MIAS database of mammograms (MIAS) indicate that the method is more suitable for detection of well-defined, circumscribed, ill-defined and other mass types. However, it has some difficulty to accurately detect any masses in high dense breast area with unclear margin. This case will be taken into account as our future works. |
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