| Presentation | 2021-03-16 Tuberculosis in Chest CT Image Analysis based on multi-axis projections using Deep learning Tetsuya Asakawa, Masaki Aono, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | The purpose of this research is to make accurate estimates for the six labels (Left affected, Right affected, Light pleurisy, Right pleurisy, Left caverns, Right caverns) for each of the lungs. We describe the tuberculosis task and approach for chest CT image analysis, then perform multi-label CT image analysis using the task dataset. We propose finetuning deep neural network model that uses inputs from multiple CNN features. In addition, this paper presents two approaches for applying mask data to the extracted 2D image data and for extracting a set of 2D projection images along multi-axis based on the 3D chest CT data removed bone, space, fat, and skin except for the lungs that could help to classify the samples. Our submissions on the task test dataset reached a mean AUC value of 0.792 and a minimum AUC value of 0.716. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Computed Tomography / Tuberculosis / Deep Learning / Multi-label classification |
| Paper # | MI2020-64 |
| Date of Issue | 2021-03-08 (MI) |
| Conference Information | |
| Committee | MI |
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| Conference Date | 2021/3/15(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Medical Imaging |
| 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) | Tuberculosis in Chest CT Image Analysis based on multi-axis projections using Deep learning |
| Sub Title (in English) | |
| Keyword(1) | Computed Tomography |
| Keyword(2) | Tuberculosis |
| Keyword(3) | Deep Learning |
| Keyword(4) | Multi-label classification |
| 1st Author's Name | Tetsuya Asakawa |
| 1st Author's Affiliation | Toyohashi University of Technology(Toyohashi Univ) |
| 2nd Author's Name | Masaki Aono |
| 2nd Author's Affiliation | Toyohashi University of Technology(Toyohashi Univ) |
| Date | 2021-03-16 |
| Paper # | MI2020-64 |
| Volume (vol) | vol.120 |
| Number (no) | MI-431 |
| Page | pp.pp.74-79(MI), |
| #Pages | 6 |
| Date of Issue | 2021-03-08 (MI) |