| Presentation | 2020-01-29 [Poster Presentation] Computerized Classification Method of Benign and Malignant Masses in Multiple MRI Sequences using Convolutional Neural Network Yuichi Mima, Akiyoshi Hizukuri, Ryohei Nakayama, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Breast magnetic resonance imaging (MRI) has a higher sensitivity of early breast cancer than mammography and ultrasonography, but the specificity is lower. The purpose of this study was to develop a computerized classification method for distinguishing between benign and malignant masses by analyzing multiple MRI sequences with convolutional neural networks (CNNs). Our database consisted of multiple MRI sequences for 43 patients with masses. In our proposed method, the CNNs were first trained independently for each MRI sequence. The outputs of the middle layers in the trained CNNs were then inputted to a support vector machine (SVM) for distinguishing between benign and malignant masses. With the proposed method, the classification accuracy, the sensitivity, the specificity, the positive predictive value, and the negative predictive value were 88.4% (38/43), 90.0% (27/30), 84.6% (11/13), 76.9% (10/13), and 93.3% (28/30), respectively. The proposed method achieved high classification performance and would be useful in differential diagnoses of masses as diagnostic aid. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Breast magnetic resonance imaging / Multiple sequences, / Mass / Convolutional neural network |
| Paper # | MI2019-77 |
| Date of Issue | 2020-01-22 (MI) |
| Conference Information | |
| Committee | MI |
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| Conference Date | 2020/1/29(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | OKINAWAKEN SEINENKAIKAN |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Medical Image Engineering, Analysis, Recognition, etc. |
| Chair | Yoshiki Kawata(Tokushima Univ.) |
| Vice Chair | Takayuki Kitasaka(Aichi Inst. of Tech.) / Hidekata Hontani(Nagoya Inst. of Tech.) |
| Secretary | Takayuki Kitasaka(Yamaguchi Univ.) / Hidekata Hontani(Univ. of Hyogo) |
| Assistant | Hotaka Takizawa(Tsukuba Univ.) / Yoshito Otake(NAIST) |
| Paper Information | |
| Registration To | Technical Committee on Medical Imaging |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | [Poster Presentation] Computerized Classification Method of Benign and Malignant Masses in Multiple MRI Sequences using Convolutional Neural Network |
| Sub Title (in English) | |
| Keyword(1) | Breast magnetic resonance imaging |
| Keyword(2) | Multiple sequences, |
| Keyword(3) | Mass |
| Keyword(4) | Convolutional neural network |
| 1st Author's Name | Yuichi Mima |
| 1st Author's Affiliation | Ritsumeikan University(Ritsumeikan Univer) |
| 2nd Author's Name | Akiyoshi Hizukuri |
| 2nd Author's Affiliation | Ritsumeikan University(Ritsumeikan Univer) |
| 3rd Author's Name | Ryohei Nakayama |
| 3rd Author's Affiliation | Ritsumeikan University(Ritsumeikan Univer) |
| Date | 2020-01-29 |
| Paper # | MI2019-77 |
| Volume (vol) | vol.119 |
| Number (no) | MI-399 |
| Page | pp.pp.57-59(MI), |
| #Pages | 3 |
| Date of Issue | 2020-01-22 (MI) |